CN104881847A - Match video image enhancement method based on wavelet analysis and pseudo-color processing - Google Patents

Abstract

The present invention discloses a match video image enhancement method based on wavelet analysis and pseudo-color processing. The method comprises the steps of a, utilizing the orthogonal wavelet transformation of images to carry out the transformation processing on the football match video images; b, carrying out the football match video image enhancement processing based on the orthogonal wavelet transformation; c, carrying out the pseudo-color football match video enhancement processing on the images. The match video image enhancement method based on wavelet analysis and pseudo-color processing of the present invention can overcome the defects in the prior art of complicated operation process, long time, low reliability, etc., and realizes the advantages of simple operation process, short time and high reliability.

Description

A Game Video Image Enhancement Method Based on Wavelet Analysis and Pseudo-color Processing

technical field

The invention relates to the technical field of video processing, in particular to a game video image enhancement method based on wavelet analysis and pseudo-color processing.

Background technique

Commonly used football game video image enhancement methods and their defects

Football game video image enhancement refers to the purposeful enhancement of the overall or local characteristics of the football game video image for a given image application, making the original unclear image clear or emphasizing some interesting features, expanding the football game The difference between different object features in the video image, suppressing uninteresting features, matching the image with the visual response characteristics, improving image quality, enriching the amount of information, enhancing image interpretation and recognition effects, and meeting the needs of some image analysis.

Commonly used football game video image enhancement methods can be divided into frequency domain methods and space domain methods. The algorithm based on the frequency domain is to modify the transformation coefficient value of the image in a certain transformation domain of the football game video image, and it is an indirect enhancement algorithm. The frequency domain method regards the football game video image as a two-dimensional signal, and performs a signal enhancement method based on two-dimensional Fourier transform on it. The processing process is shown in Figure 1. The frequency domain method first designs an appropriate correction function H(x, y) according to the specific enhancement requirements, and then uses Fourier transform to transform the football game video image into the frequency domain F(x, y), and then adjusts the football game video image Some kind of filter correction is performed on the spectrum, that is, F(x,y)·H(x,y) operation is performed to obtain G(x,y), and finally the corrected image is inversely Fourier transformed into the space domain to obtain Augment the image g(x,y). In this process, the low-pass filtering method is used to remove the noise in the picture; the high-pass filtering method is used to enhance high-frequency signals such as edges, so that the blurred image becomes clear. Figure 2 shows the results of video image enhancement of football games using the frequency domain method.

Algorithms based on airspace are divided into point operation algorithm and neighborhood enhancement algorithm. Point calculation algorithms are gray level correction, gray level transformation and histogram correction, etc. The purpose is to make the football game video image uniform, or expand the football game video image dynamic range and expand the contrast. Neighborhood enhancement algorithms are divided into image smoothing and sharpening. Smoothing is generally used to eliminate image noise, but it is also easy to cause blurring of edges. The purpose of sharpening is to highlight the edge contour of the object, which is beneficial to target recognition. Representative spatial domain algorithms include local averaging and median filtering, which can be used to remove or attenuate noise. Commonly used algorithms include gradient method, operator, high-pass filter, mask matching method, statistical difference method, etc. The spatial domain method is to perform convolution operations on the pixels in the image, and the formula is described as follows:

g(x,y)=f(x,y)*h(x,y)

Among them, f(x, y) represents the original football game video image function; h(x, y) represents the (low-pass or high-pass filtering) filter impulse response space conversion function; g(x, y) represents the processed football game Video image function. Figure 3 shows the result of football game video image enhancement using histogram correction, and Figure 4 shows the result of football game video image enhancement using grayscale transformation.

The traditional football game video image enhancement algorithm is based on the statistics of the entire image. Therefore, when calculating the transformation of the entire image, the low-frequency information, high-frequency information and noise information in the image are transformed at the same time, thus enhancing the image. At the same time, the noise in the image is enhanced, the signal-to-noise ratio of the image is reduced, and the information entropy of the image is reduced. It is not conducive to the subsequent analysis and processing of the target of interest, and the expected enhancement purpose has not been achieved.

In the process of realizing the present invention, the inventors found that the prior art at least has defects such as complicated operation process, long time-consuming and low reliability.

Contents of the invention

The object of the present invention is to address the above-mentioned problems and propose a game video image enhancement method based on wavelet analysis and pseudo-color processing, so as to realize the advantages of simple operation process, short time consumption and high reliability.

In order to achieve the above object, the technical solution adopted in the present invention is: a method for enhancing game video images based on wavelet analysis and pseudo-color processing, comprising:

a, using the orthogonal wavelet transform of the image to transform the football game video image;

b. Video image enhancement processing of football matches based on orthogonal wavelet transform;

c. Pseudo-color football game video enhancement processing of the image.

Further, said step a specifically includes:

suppose is a series of coefficients of any scale in the scale space, h ₀ and h ₁ are the low-pass filter and high-pass filter coefficients of the orthogonal wavelet function respectively, these two sets of coefficients are constant for any scale, and the coefficients of the orthogonal wavelet transform The relationship between them is represented by (1):

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

The edge profile of the original football game video image at one scale can be decomposed into four parts: low-frequency components, horizontal high-frequency components, vertical high-frequency components and diagonal components at smaller scales, which are obtained through four different filters respectively different information representing the original football game video image, where yes Obtained by the low-pass filter in the row and column directions, it corresponds to Edge profile information on the next scale; yes Obtained by a high-pass filter in the row direction and a low-pass filter in the column direction, it corresponds to The overview of the detailed information in the horizontal direction in the vertical direction; similarly, express The overview of the detail information in the vertical direction in the horizontal direction; express Details in the diagonal direction;

After the football game video image is decomposed by two-dimensional orthogonal wavelet transform, the low-frequency component, horizontal high-frequency component, vertical high-frequency component and diagonal component of the image are obtained respectively.

Further, the step b specifically includes:

Firstly, the wavelet fractal interpolation is used to denoise the video image signal of the football game, and a better effect of noise removal is obtained;

Then use the orthogonal wavelet transform to decompose a football game video image into components with different sizes, positions and directions. The component of interest and the attenuation of the component that has little effect on the image processing result;

Orthogonal wavelet analysis method is a kind of spatial window and frequency window can be used for adaptive change, space-frequency localized analysis method, two-dimensional multi-scale discrete orthogonal wavelet analysis is defined as:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Phi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\\ {\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Psi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\\ {\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Psi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\\ {\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 3</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Psi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Where f(x,y) is the image signal; S _j f(n,m) is the low frequency component of f(x,y); Represent the vertical, diagonal and horizontal high-frequency components of f(x,y), respectively;

When the formula (3) is established, that is, when the weight of the high-frequency component is large, the video image of the football game looks clearer:

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ {\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

in, is the high-frequency wavelet coefficient; is the low-frequency wavelet coefficient; k is the weight of the high-frequency component; j is the number of wavelet decomposition layers.

Further, the step c specifically includes:

Using frequency domain pseudo-color processing enhancement method to perform pseudo-color processing on football game video images;

Video Image Enhancement of Football Match Based on Wavelet Analysis and Pseudo-color Processing.

Further, the operation of performing pseudo-color processing on football game video images by using the frequency-domain pseudo-color processing enhancement method further includes:

First, the football game video image is transformed into the frequency domain by Fourier transform, and three filters with different transfer characteristics are separated into three independent components in the frequency domain;

Then perform an inverse Fourier transform on them to obtain three monochrome images representing different frequency components, and then further process these three images;

Finally, they are respectively added to the red, green, and blue display channels of the color display as three primary color components to realize the pseudo-color enhancement of frequency domain segmentation.

Further, the operation of the football game video image enhancement based on wavelet analysis and pseudo-color processing further includes:

Step 1: Use the orthogonal fractal wavelet transform to process the football game video image to obtain the image after denoising;

Step 2: Use orthogonal wavelet transform to decompose the football game video image into four parts: low-frequency component, horizontal high-frequency component, vertical high-frequency component and diagonal component;

Step 3: Enlarge the part of interest in the image, and at the same time weaken the unimportant information in the image;

Step 4: After using the orthogonal wavelet transform football game video image enhancement algorithm to obtain the result image, convert it into the frequency domain, and use the image enhancement method of pseudo-color processing to process different frequency parts to obtain better football game video image enhancement Effect.

The game video image enhancement method based on wavelet analysis and pseudo-color processing in each embodiment of the present invention, owing to comprise: a, utilize the orthogonal wavelet transform of image to carry out transform processing to football match video image; B, football game video image based on orthogonal wavelet transform Game video image enhancement processing; c, pseudo-color football game video enhancement processing of images; thereby can overcome the defects of complex operation process, long time-consuming and low reliability in the prior art, so as to realize simple operation process, short time-consuming and reliable operation Advantages of high sex.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention.

The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

Description of drawings

The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the description, and are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the attached picture:

Fig. 1 is frequency domain method football game video image enhancement schematic diagram in the present invention;

Fig. 2 is frequency domain method football game video image enhancement among the present invention, (a), (b), (c) are successively original image, FFT2 transformed image and enhanced image;

Fig. 3 is the histogram correction image enhancement in the present invention, (a) is the original image, (b) is the histogram of (a), (c) is the enhanced image, (d) is the histogram of (c);

Fig. 4 is gray scale linear transformation image enhancement among the present invention, (a) is original image, (b) is enhanced image;

Fig. 5 is a schematic diagram of basic wavelet decomposition (multilevel decomposition schematic diagram) in the present invention;

Fig. 6 is a schematic diagram of three-layer wavelet decomposition in the present invention;

Fig. 7 is orthogonal wavelet transform football game video image enhancement among the present invention, (a) is original image, (b) is enhanced image;

FIG. 8 is a schematic diagram of realizing false color processing by the mid-frequency domain filtering method of the present invention;

Fig. 9 is the image enhancement of the method proposed by the technical solution of the present invention, (a) is the low grayscale enhanced image of the original image, and (b) is the high grayscale enhanced image of the original image;

Fig. 10 is the fuzzy football game video image enhancement in the present invention, (a) is a fuzzy image, (b) is an enhanced image.

Detailed ways

The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

According to an embodiment of the present invention, as shown in FIGS. 1-10 , a game video image enhancement method based on wavelet analysis and pseudo-color processing is provided.

Video Image Enhancement of Football Match Based on Wavelet Analysis and Pseudo-color Processing

2.2.2.1 Orthogonal wavelet transform of football game video images

In order to realize the enhancement of the video image of the football match, the technical scheme of the present invention uses the orthogonal wavelet transform of the image to transform the video image of the football match.

suppose is a series of coefficients of any scale in the scale space, h ₀ and h ₁ are the coefficients of the low-pass filter and high-pass filter of the orthogonal wavelet function respectively, these two sets of coefficients are constant for any scale, thus, the orthogonal wavelet transform The quick decomposition of can be shown in Figure 5. The relationship between the coefficients of the orthogonal wavelet transform is represented by (1).

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; \&gamma;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; l</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

It can be seen from Figure 4 that the edge profile of the original football game video image at one scale can be decomposed into four parts at a smaller scale: low-frequency components, horizontal high-frequency components, vertical high-frequency components and diagonal components. Different information representing the original football game video image obtained by different filters, where yes Obtained by the low-pass filter in the row and column directions, it corresponds to Edge profile information on the next scale; yes Obtained by a high-pass filter in the row direction and a low-pass filter in the column direction, it corresponds to The overview of the detailed information in the horizontal direction in the vertical direction; similarly, express The overview of the detail information in the vertical direction in the horizontal direction; express Diagonally detailed information. After the football game video image is decomposed by two-dimensional orthogonal wavelet transform, the low-frequency component, horizontal high-frequency component, vertical high-frequency component and diagonal component of the image are obtained respectively. Figure 6 is a three-layer orthogonal wavelet decomposition diagram of a football game video image, where C ₃ is the low-frequency part of the image, and most of the energy of the image is concentrated in this area. They are the horizontal, vertical and diagonal components, which are the detailed information of the image.

2.2.2.2 Video Image Enhancement Processing of Football Match Based on Orthogonal Wavelet Transform

The wavelet coefficients of image signals in the corresponding positions of each layer often have a strong correlation, while the wavelet coefficients of noise have the characteristics of weak correlation or no correlation. Firstly, the wavelet fractal interpolation is used to denoise the football game video image signal, which can get a better effect of removing noise. Then use the orthogonal wavelet transform to decompose a football game video image into components with different sizes, positions and directions. Before the inverse transform, you can change the size of some coefficients in the wavelet transform domain, so that you can selectively enlarge the image. The components of interest in the football game video image are attenuated and the components that have little influence on the image processing result are attenuated. Orthogonal wavelet analysis method is a space-frequency localized analysis method that both the space window and the frequency window can be changed adaptively. Compared with the traditional Fourier analysis method, it has better space-frequency window characteristics.

Two-dimensional multiscale discrete orthogonal wavelet analysis is defined as:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Phi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\\ {\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Psi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\\ {\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Psi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\\ {\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 3</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; R</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{<span\; class="notranslate">\; \&Integral;</span><span\; class="notranslate">\; \&Integral;</span>}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}{\mathrm{<span\; class="notranslate">\; \&Psi;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; j</span>}}\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dxdy</span>}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Where f(x,y) is the image signal; S _j f(n,m) is the low frequency component of f(x,y); Represent the vertical, diagonal and horizontal high-frequency components of f(x,y), respectively.

It can be seen that after two-dimensional discrete orthogonal wavelet analysis, the video image of the football game is divided into low-frequency components and three high-frequency components: vertical, diagonal and horizontal. Since the low-contrast image mainly shows that the three high-frequency components are too small, resulting in blurred image details, so appropriately increasing the three high-frequency components can enhance image detail information. Therefore, when formula (3) holds true, that is, when the weight of the high-frequency component is relatively large, the video image of the football game looks clearer.

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ {\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}\end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

in, is the high-frequency wavelet coefficient; is the low-frequency wavelet coefficient; k is the weight of the high-frequency component; j is the number of wavelet decomposition layers. The experimental results obtained by using the orthogonal wavelet transform football game video image enhancement method are shown in Figure 7. However, after adopting this method, due to the enhanced high-frequency components, the resulting football game video image is often brighter and its contrast is poor, so it is necessary to use pseudo-color processing to further increase the resolution of the football game video image.

2.2.2.3 Pseudo-color football game video enhancement processing of images

The technical scheme of the present invention adopts the frequency domain pseudo-color processing enhancement method to perform pseudo-color processing on the football game video image, first transform the football game video image into the frequency domain through Fourier transform, and separate the three filters with different transfer characteristics into three in the frequency domain. Independent components, and then perform inverse Fourier transform on them to obtain three monochrome images representing different frequency components, then further process these three images (such as histogram equalization), and finally use them as three primary color components respectively Added to the red, green, and blue display channels of the color display, thereby realizing the false color enhancement of the frequency domain segmentation. Its block diagram is shown in Figure 8.

2.2.2.4 Football game video image enhancement based on wavelet analysis and pseudo-color processing

In order to overcome the defects of the soccer match video image enhancement algorithm based on orthogonal wavelet analysis and pseudo-color processing, the technical scheme of the present invention proposes a football match video image enhancement algorithm based on orthogonal wavelet analysis and pseudo-color processing. This algorithm can not only overcome the defects of brighter and poorer contrast of the image processed by the orthogonal wavelet analysis football match video image enhancement algorithm, but also overcome the inability of the pseudo-color processing football match video image enhancement algorithm to fully process some details in the image Information Defects. The specific implementation steps of the algorithm are as follows:

Step 1: Use the orthogonal fractal wavelet transform to process the football game video image to obtain the denoised image.

Step 2: Use the orthogonal wavelet transform to decompose the football game video image into four parts: low frequency component, horizontal high frequency component, vertical high frequency component and diagonal component at a smaller scale.

Step 3: In order to achieve the purpose of image enhancement of football game video, the part of interest in the image is selectively enlarged, and the unimportant information in the image is weakened.

Step 4: After using the orthogonal wavelet transform football game video image enhancement algorithm to obtain the result image, convert it into the frequency domain, and use the image enhancement method of pseudo-color processing to process different frequency parts to obtain better football game video image enhancement Effect.

Figure 9 shows the processing result of the football game video image enhancement method based on orthogonal wavelet analysis and pseudo-color processing proposed by the technical solution of the present invention. Since blurred images may be generated during the process of filming and playing video images, the method proposed by the technical solution of the present invention can be used to enhance the blurred images, as shown in FIG. 10 .

Experimental comparison

The technical scheme of the invention evaluates the enhancement effect of the football match video image quantitatively by calculating the average value, information entropy and definition of the enhanced football match video image. Use formula (5) to calculate the mean value of the image.

$\mathrm{<span\; class="notranslate">\; mean</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; X\; Y</span>}}\underset{\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; x</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\underset{\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; Y</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

Among them, I _e is the enhanced result image, and (X, Y) is the image size. For an image, the mean reflects the average brightness of the image. If the mean is moderate (with a grayscale value of 128 in the vicinity), then the visuals are good.

The calculation of information entropy is defined as follows:

$\mathrm{<span\; class="notranslate">\; Ent</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; L</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; In</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

Among them, p _i is the probability corresponding to the gray level GNL _i of the image; L is the total number of gray levels; i∈(0,1,...L-2,L-1). The larger the entropy value, the more information the image carries, so information entropy is an important indicator to measure the richness of image information.

The sharpness of football game video images can be calculated by formula (7):

Clarity can reflect the small detail contrast and texture transformation characteristics in football game video images. The larger the sharpness value, the clearer the corresponding football game video image. Table 1 shows the mean value, information entropy and clarity of football game video images enhanced by the three algorithms. Table 2 shows the mean value, information entropy and clarity of each RGB channel of the football game video image enhanced by the three algorithms.

$\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; Def</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; X\; Y</span>}}\underset{\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; x</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\underset{\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; Y</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\sqrt{{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}\\ \mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ \end{array}\right.<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

Table 1 Mean value, information entropy and sharpness of enhanced image

Table 2 Mean value, information entropy and sharpness of the enhanced image

This part introduces the football game video image preprocessing technology. Firstly, five commonly used image denoising methods, namely mean filter denoising, median filter denoising, PDE-based image denoising, full variation image denoising and fractal wavelet transform denoising, and their defects are introduced. A fractal wavelet adaptive image denoising algorithm based on multivariate statistical model is proposed. In the process of denoising, a multivariate statistical model is first established, which can estimate various relevant information more accurately, and the model parameters can be improved more flexibly. Then by combining with fractal wavelet denoising method can select high quality image space. Under moderate noise variance, the near-optimal parent-child tree can be found in the best subtree domain according to the tile distance. Finally, the noise-free image fractal wavelet code is predicted from the noisy image, so as to achieve the purpose of optimizing denoising. This method can effectively maintain the edge and texture features of the image while removing the noise, and preserve the fine structure of the image well, achieving a good denoising effect. Due to the use of predictive wavelet fractal coding, the algorithm structure is optimized, and the processing speed of the algorithm is relatively fast. Secondly, the commonly used frequency domain football match video image enhancement methods and space domain football match video image enhancement methods and their defects are introduced. A football game video image enhancement algorithm based on orthogonal wavelet analysis and pseudo-color processing is proposed. The football game video image enhancement algorithm with pseudo-color processing cannot fully deal with the defects of some detailed information in the image.

Finally, it should be noted that: the above is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, it still The technical solutions recorded in the foregoing embodiments may be modified, or some technical features thereof may be equivalently replaced. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (6)

1. A match video image enhancement method based on wavelet analysis and pseudo color processing is characterized by comprising the following steps:

a. transforming the football match video image by using orthogonal wavelet transform of the image;

b. enhancing the football match video image based on orthogonal wavelet transform;

c. and (3) enhancing the pseudo-color football game video of the image.

2. A match video image enhancement method based on wavelet analysis and pseudo-color processing according to claim 1, wherein said step a specifically comprises:

suppose thatIs an arbitrary scale coefficient series of a scale space, h₀And h₁Low-pass filter and high-pass filter coefficients, respectively, of an orthogonal wavelet function, both sets of coefficients being constant for any scale, the relationship between the coefficients of the orthogonal wavelet transform being represented by (1):

<math> <mrow> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <msubsup> <mi>s</mi> <mrow> <mi>i</mi> <mo>.</mo> <mi>l</mi> </mrow> <mi>j</mi> </msubsup> <mo>=</mo> <munder> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>n</mi> </mrow> </munder> <msub> <mi>h</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>2</mn> <mi>i</mi> <mo>)</mo> </mrow> <msub> <mi>h</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>2</mn> <mi>l</mi> <mo>)</mo> </mrow> <msubsup> <mi>s</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>m</mi> </mrow> <mrow> <mi>j</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>&alpha;</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>l</mi> </mrow> <mi>j</mi> </msubsup> <mo>=</mo> <munder> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>n</mi> </mrow> </munder> <msub> <mi>h</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>2</mn> <mi>i</mi> <mo>)</mo> </mrow> <msub> <mi>h</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>2</mn> <mi>l</mi> <mo>)</mo> </mrow> <msubsup> <mi>s</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>m</mi> </mrow> <mrow> <mi>j</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>&beta;</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>l</mi> </mrow> <mi>j</mi> </msubsup> <mo>=</mo> <munder> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>n</mi> </mrow> </munder> <msub> <mi>h</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>2</mn> <mi>i</mi> <mo>)</mo> </mrow> <msub> <mi>h</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>2</mn> <mi>l</mi> <mo>)</mo> </mrow> <msubsup> <mi>s</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>m</mi> </mrow> <mrow> <mi>j</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>&gamma;</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>l</mi> </mrow> <mi>j</mi> </msubsup> <mo>=</mo> <munder> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>n</mi> </mrow> </munder> <msub> <mi>h</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>2</mn> <mi>i</mi> <mo>)</mo> </mrow> <msub> <mi>h</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>m</mi> <mo>-</mo> <mn>2</mn> <mi>l</mi> <mo>)</mo> </mrow> <msubsup> <mi>s</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>m</mi> </mrow> <mrow> <mi>j</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </math>

the edge contour of the original football match video image in one scale can be decomposed into four parts of low-frequency component, horizontal high-frequency component, vertical high-frequency component and diagonal component in smaller scale, which are respectively passed through four different filters to obtain different information representing original football match video image, in whichIs thatObtained by low-pass filters in both the row and column directions, corresponding toEdge profile information on the next scale;is thatObtained by means of a high-pass filter in the row direction and a low-pass filter in the column direction, which corresponds toA profile of detail information in the horizontal direction in the vertical direction; in the same way, the method for preparing the composite material,to representIs perpendicular toA profile of the detail information in the direction in the horizontal direction;to representDetail information in the diagonal direction;

after the video image of the football match is decomposed by two-dimensional orthogonal wavelet transform, the low-frequency component, the horizontal high-frequency component, the vertical high-frequency component and the diagonal component of the image are respectively obtained.

3. A match video image enhancement method based on wavelet analysis and pseudo-color processing according to claim 1 or 2, wherein said step b specifically comprises:

firstly, denoising a football game video image signal by utilizing wavelet fractal interpolation to obtain a better denoising effect;

then, decomposing a football match video image into components with different sizes, positions and directions by using orthogonal wavelet transform, changing the sizes of certain coefficients in a wavelet transform domain before inverse transform, amplifying the components interested in the football match video image and attenuating the components with little influence on the image processing result;

the orthogonal wavelet analysis method is a space window and frequency window self-adaptive change and space frequency localization analysis method, and the two-dimensional multi-scale discrete orthogonal wavelet analysis is defined as follows:

<math> <mrow> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <msub> <mi>S</mi> <mi>j</mi> </msub> <mi>f</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mrow> <mo>&Integral;</mo> <mo>&Integral;</mo> </mrow> <msup> <mi>R</mi> <mn>2</mn> </msup> </munder> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <msup> <mn>2</mn> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msup> <msub> <mi>&Phi;</mi> <mi>j</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>n</mi> <mo>,</mo> <mi>y</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>m</mi> <mo>)</mo> </mrow> <mi>dxdy</mi> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>W</mi> <mi>j</mi> <mn>1</mn> </msubsup> <mi>f</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mrow> <mo>&Integral;</mo> <mo>&Integral;</mo> </mrow> <msup> <mi>R</mi> <mn>2</mn> </msup> </munder> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <msup> <mn>2</mn> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msup> <msubsup> <mi>&Psi;</mi> <mi>j</mi> <mn>1</mn> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>n</mi> <mo>,</mo> <mi>y</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>m</mi> <mo>)</mo> </mrow> <mi>dxdy</mi> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>W</mi> <mi>j</mi> <mn>2</mn> </msubsup> <mi>f</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mrow> <mo>&Integral;</mo> <mo>&Integral;</mo> </mrow> <msup> <mi>R</mi> <mn>2</mn> </msup> </munder> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <msup> <mn>2</mn> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msup> <msubsup> <mi>&Psi;</mi> <mi>j</mi> <mn>2</mn> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>n</mi> <mo>,</mo> <mi>y</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>m</mi> <mo>)</mo> </mrow> <mi>dxdy</mi> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>W</mi> <mi>j</mi> <mn>3</mn> </msubsup> <mi>f</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>,</mo> <mi>m</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mrow> <mo>&Integral;</mo> <mo>&Integral;</mo> </mrow> <msup> <mi>R</mi> <mn>2</mn> </msup> </munder> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <msup> <mn>2</mn> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msup> <msubsup> <mi>&Psi;</mi> <mi>j</mi> <mn>3</mn> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>n</mi> <mo>,</mo> <mi>y</mi> <mo>-</mo> <msup> <mn>2</mn> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>m</mi> <mo>)</mo> </mrow> <mi>dxdy</mi> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein f (x, y) is an image signal; s_jf (n, m) is the low frequency component of f (x, y); vertical, diagonal and horizontal high frequency components representing f (x, y), respectively;

when equation (3) is satisfied, i.e. the high frequency component weight is large, the video image of the soccer game looks sharper:

<math> <mrow> <msubsup> <mi>C</mi> <mi>j</mi> <mo>&prime;</mo> </msubsup> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <mi>k</mi> <mo>&times;</mo> <msubsup> <mi>C</mi> <mi>j</mi> <mi>H</mi> </msubsup> <mo>,</mo> <mi>k</mi> <mo>></mo> <mn>1</mn> </mtd> </mtr> <mtr> <mtd> <msubsup> <mi>C</mi> <mi>j</mi> <mi>L</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow> </math>

wherein,is a high-frequency wavelet coefficient;is a low-frequency wavelet coefficient; k is the high frequency component weight; j is the wavelet decomposition level number.

4. A match video image enhancement method based on wavelet analysis and pseudo-color processing according to claim 3, wherein said step c specifically comprises:

carrying out pseudo-color processing on the football match video image by adopting a frequency domain pseudo-color processing enhancement method;

and enhancing the video image of the football match based on wavelet analysis and pseudo-color processing.

5. A match video image enhancement method based on wavelet analysis and pseudo-color processing according to claim 4, wherein said operation of pseudo-color processing the football match video image using frequency domain pseudo-color processing enhancement method further comprises:

firstly, transforming a football game video image into a frequency domain through Fourier transform, and separating three filters with different transmission characteristics into three independent components in the frequency domain;

then, carrying out inverse Fourier transform on the three images to obtain three monochromatic images representing different frequency components, and then further processing the three images;

finally, the three primary color components are respectively added to red, green and blue display channels of a color display to realize the frequency domain segmented pseudo color enhancement.

6. A match video image enhancement method based on wavelet analysis and pseudo-color processing according to claim 4, wherein said operation of football match video image enhancement based on wavelet analysis and pseudo-color processing further comprises:

step 1, processing a football game video image by using orthogonal fractal wavelet transform to obtain a denoised image;

step 2, decomposing the football match video image into a low-frequency component, a horizontal high-frequency component, a vertical high-frequency component and a diagonal component under a smaller scale by utilizing orthogonal wavelet transform;

step 3, amplifying the interested part in the image and weakening unimportant information in the image;

and Step 4, converting the result image into a frequency domain after the result image is obtained by adopting an orthogonal wavelet transform football game video image enhancement algorithm, and processing different frequency parts by adopting a pseudo-color processing image enhancement method to obtain a better football game video image enhancement effect.