KR102207441B1 - The apparatus and method of HDR imaging generation - Google Patents

Abstract

The present invention relates to an apparatus and method for generating an HDR image, and more specifically, a first color space conversion unit for generating a first converted image converted from an input image to a YCbCr color space, and for adjusting the brightness of the first converted image. A brightness control unit, a second color space conversion unit for converting the first converted image and the input image to an HSV color space, a saturation compensation unit for comparing and compensating the saturation of the two images converted to the HSV color space, and the saturation degree It may be configured to include a third color space conversion unit for converting the compensated input image to the RGB color space.

Description

The apparatus and method of HDR imaging generation

The present invention relates to an apparatus and method for generating a high dynamic range (HDR) image, and more particularly, to an apparatus and method for generating an HDR image adaptively compensating for color saturation according to a change in brightness of an input image.

HDR (High Dynamic Range) refers to a technology that expands the dynamic range of a digital image by making bright places brighter and dark places darker, closer to what a person actually sees.

Currently, as cameras are used in various fields such as black boxes, CCTVs, autonomous vehicles, etc., when an HDR image with a wider dynamic range (HDR) is required to acquire more information from the captured image Is increasing.

Recently, an HDR image is generated by synthesizing a plurality of LDR (Low Dynamic Range) images taken at different exposure times while extending the dynamic range, or LDR images having different brightness values (exposure values) of a single frame LDR image Methods of generating an HDR image by synthesizing a plurality of LDR images, such as generating an HDR image by expanding the dynamic range while synthesizing again after decomposition into, are mainly studied.

However, in the method of generating an HDR image by synthesizing a plurality of LDR images captured at different exposure times and extending the dynamic range, a ghost phenomenon may occur due to the movement of the imaging device, and multiple LDR images may be generated in a single frame. In the method of generating an HDR image by generating an exposure image of, normalizing the brightness, and estimating detail and synthesizing the image, there was a problem that the image decomposition and synthesis method was complicated, and it was difficult to create a high-quality HDR image. .

In order to solve the above problem, as a basic image contrast enhancement technique, Garima et al. proposed the CLAHE method in "Contrast limited adaptive histogram equalization based enhancement for real time video system". This method is a multi-layer based local area brightness enhancement technique.

Meanwhile, Guarnieri proposed an HDR technique that removes common artifacts including halo around sharp edges by using an edgepreserving low-pass filter in “High dynamic range image display with halo and clipping prevention”. I did. Furthermore, in “Natural HDR image tone mapping based on retinex”, Kim presented the Retinex algorithm with tone mapping function to improve contrast in dark areas.

In addition, Hsia proposed an HDR technique using an inverted local pattern (ILP) in “High-performance high dynamic range image generation by inverted local patterns”. This method is a method of generating an HDR image in a method suitable for each image by separating it into an extreme image, a bright image, and a dark image within the same frame.

However, these methods are techniques applied only to brightness, and after generating an HDR image, there is a problem in that color saturation decreases in a specific area.

(Paper 1) G. Yadav, S. Maheshwari, and A. Agarwal, “Contrast Limited Adaptive Histogram Equalization Based Enhancement For Real Time Video System,” Proc. International Conference on Advances in Computing, Communications and Informatics, New Delhi, India, pp. 2392-2397. 2014. (Paper 2) G. Guarnieri, S. Marsi, and G. Ramponi, “High dynamic range image display with halo and clipping prevention,” IEEE Trans. Image Process., Vol. 20, No. 5, pp. 1351-1362, May 2011. (Paper 3) K. Kim, J. Bae, and J. Kim, “Natural HDR image tone mapping based on retinex,” IEEE Trans. Consum. Electron., Vol. 57, No. 4, pp. 1807-1814, Nov. 2011. (Paper 4) S. Hsia and T. Kuo, "High-performance high dynamic range image generation by inverted local patterns," IET Image Processing, Vol. 9, No. 12, pp. 1083-1091, Nov. 2015.

The present invention is to solve the problems of the above technical problem, and an object of the present invention is to provide a method for compensating for saturation according to a brightness component of an input image and an apparatus for implementing the same.

An HDR image generating apparatus according to an embodiment of the present invention for solving the above technical problem includes a first color space converter configured to generate a first converted image converted from an input image to a YCbCr color space, and the brightness of the first converted image. A brightness control unit for adjusting the first converted image and a second color space conversion unit for converting the input image into an HSV color space, a saturation compensation unit for comparing and compensating the saturation of the two images converted to the HSV color space, and And a third color space conversion unit converting the input image whose saturation is compensated into an RGB color space.

In addition, the brightness control unit is a histogram analysis unit that generates and analyzes a histogram of the first transformed image, a dark area enhancement unit that improves a dark area based on the histogram analysis result, and an inverse transform filter is applied to the first transformed image. An inverse transform filter applying unit to perform, an image fusion unit that fuses the brightness value obtained by improving the brightness by the dark area enhancement unit and the resulting image of the inverse transform filter application unit, and a brightness improving unit that adjusts the brightness of the image output from the image fusion unit. Can include.

In addition, the brightness improvement unit is a brightness gain that expands the luminance range for the entire region of the image for which the parameter is adjusted using a bright area enhancement unit that adjusts brightness contrast only in a bright area and an auto gain control method. It may further include an adjustment unit.

In addition, the inverse transform filter applying unit performs dark area enhancement and calculates an inversion coefficient for the input image through a block-processing-based inversion kernel in the Y channel, and the inversion kernel includes a maximum filter and a low-pass filter ( Low pass filter) can be performed and then reversed.

In addition, the saturation compensation unit includes a color saturation level storage unit for storing the color saturation level of the original image, a brightness enhancement analysis unit for comparing and analyzing the brightness region of the third converted image and the original image, and a comparative analysis result of the brightness enhancement analysis unit. A compensation coefficient derivation unit that derives a compensation coefficient by considering a value of a decrease in color saturation according to a change in brightness using a color saturation degree application unit that compensates and applies the color saturation of the original image using the derived compensation coefficient. Can include.

An HDR image generation method according to an embodiment of the present invention for solving the technical problem includes generating a first converted image obtained by converting an input image into a YCbCr color space, controlling the brightness of the first converted image, Generating a second transformed image and a third transformed image obtained by converting the first transformed image and the input image into an HVS color space, compensating the saturation degree by comparing the saturation degree of the second transformed image and the third transformed image, and The saturation-compensated image may be converted into an RGB color space.

In addition, controlling the brightness of the first transformed image includes generating and analyzing a histogram of the first transformed image, improving a dark area determined through analysis of the histogram, and performing an inverse transform filter on the first transformed image. The applying step may further include generating a fusion image of a brightness value obtained by improving the dark area and an image to which the inverse transform filter is applied, and adjusting the brightness of the fusion image.

In addition, the adjusting of the brightness may include adjusting brightness contrast for only a bright area and expanding a luminance range for the global area of the image for which the parameter is adjusted using an auto gain control method. It may further include.

In addition, the inverse transform filter performs dark region enhancement and calculates an inversion coefficient for the input image through a block-processing-based inversion kernel in the Y channel, and the inversion kernel includes a maximum filter and a low pass filter. pass filter).

In addition, the compensating for the saturation may include storing the color saturation of the original image, comparing and analyzing the brightness region of the third transformed image and the original image, and using the comparison analysis result to The method may further include deriving a compensation coefficient in consideration of a value corresponding to a decrease in saturation, and compensating and applying a color saturation degree of the original image using the derived compensation coefficient.

According to the apparatus and method for generating an HDR image using image processing according to the exemplary embodiment described above, a high-quality HDR image may be obtained by compensating for an appropriate color saturation according to the brightness of the image.

According to an apparatus and method for generating an HDR image using an embodiment of the present invention, since color saturation in a specific region decreases when generating an HDR image, color saturation is changed in consideration of a change in brightness in the HSV color space. Can compensate for the saturation of

According to an apparatus and method for generating an HDR image using an embodiment of the present invention, an image with sharper image quality may be provided by generating an HDR image in which brightness and saturation are considered together.

According to an apparatus and method for generating an HDR image using an embodiment of the present invention, it is possible to solve the problem that color saturation decreases in dark areas and bright areas by adaptively compensating color saturation according to brightness in consideration of brightness. I can.

1 is a block diagram of an HDR image generating apparatus according to an embodiment of the present invention.
2 is a flowchart illustrating a method of generating an HDR image according to an embodiment of the present invention.
3 is a flowchart illustrating a method of adjusting brightness of an image according to an embodiment of the present invention.
4 is a flowchart illustrating a method of compensating for saturation according to an embodiment of the present invention.
5 is a diagram for comparing an execution result according to an embodiment of the present invention and a result image of a conventional technique.
6 is a diagram illustrating a comparison between an implementation result according to an embodiment of the present invention and a color saturation compensation performance compared to the prior art.

In the present invention, various changes may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail.

However, this is not intended to limit the present invention to a specific embodiment, it is to be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention.

The terms used in the present application are used only to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in this application. Does not.

Hereinafter, exemplary embodiments of the present invention will be described in more detail with reference to the accompanying drawings. In describing the present invention, in order to facilitate an overall understanding, the same reference numerals are used for the same elements in the drawings, and duplicate descriptions for the same elements are omitted. Hereinafter,'image' may be generically referred to as a still image as well as a moving picture such as a video.

1 is a block diagram of an HDR image generating apparatus according to an embodiment of the present invention.

The HDR image generating apparatus according to the present invention includes an image input unit 100, a first color space conversion unit 200, a brightness adjustment unit 300, a second color space conversion unit 400, a saturation compensation unit 500, and a third A color space conversion unit 600 and an image output unit 700 may be included.

The image input unit 100 may be an input device for inputting an image for conversion into HDR to an HDR image generating device, and the input image may be configured with an RGB color space.

The first live space conversion unit 200 may convert an RGB color space of an input image into a YCbCr color space.

The brightness adjustment unit 300 includes a histogram analysis unit 310, a dark area enhancement unit 320, an inverse transform filter application unit 330, and an image fusion unit 340 to convert and output a brightness component value of an input image to increase or decrease. ), a bright area enhancement unit 350, and a brightness gain adjustment unit 360 may be further included.

The histogram analysis unit 310 generates and analyzes a histogram for the brightness of the entire image with respect to the image converted to the YCbCr color space. The histogram generated for the entire image is each pixel using Equation 1 below. Hi and Lo values, which are the number of histograms corresponding to the bright and dark areas, can be calculated.

In addition, the Hi and Lo values, which are the number of histograms, may be used later when applying other brightness adjustment methods and compensating for saturation according to the brightness values.

In Equation 1 above, h(i) represents the histogram of the i-th brightness, and Th ₁ to Th ₄ may be set as the j-th threshold Th _j ={15, 50, 205, 240} for an 8-bit image. Th _i is a brightness value in a pixel, and can be determined through repeated experiments, and Th _i may have a brightness value between 0 and 255.

The histogram analysis unit 310 may classify the Hi and Lo values calculated using Equation 1 into an excessive area, a bright area, and a dark area according to the conditions of Table 1 below.

Types Conditions gloominess Lo>2Hi Bright Hi>2Lo plethora

&

&

Standard otherwise

The dark area enhancement unit 320 may improve the dark area of the dark area and the excessive area by using Equation 2 below based on the brightness information of the image analyzed by the histogram analysis unit 310.

In Equation 2 above, Y _dark is the improvement result value for the dark area, (i, j) is the coordinate value of each pixel, Y _in is the signal value of the Y channel of the input image, and Th _dark is As a threshold for improving the dark area, it may be defined as follows.

The inverse transform filter application unit 330 may calculate an inversion coefficient for the Y channel of the input image through an inverse kernel based on block processing.

The inverse kernel is composed of a maximum filter of 2×2 size and a low pass filter of 3×3 size, and the result of filtering the inversion kernel is inverted. The inversion coefficient can be calculated through an inverse operation. The maximum filter may be composed of Equation 3 below, and the low-pass filter may be composed of Equation 4 below.

Here, max is a function for determining the maximum value, f _i,j is the pixel value of pixels located in the maximum filter, and Y _max may represent the maximum value of the 2x2 filter.

Here, Y _lpf is a function representing the result of the low-pass filter, and m and n are variables for the size of the filter, and are set to 3 in the embodiment of the present invention, but are not fixed thereto, and if necessary, in the range of natural numbers. You can change it.

The maximum filter is used to bring the effect of saving the detail of the input image, and the low pass filter can be used to remove jagging artifacts that occur while using the maximum filter.

In the inverse operation, in order to avoid positive saturation and negative saturation, a dark region may be brightened and a bright region may be darkened using an inversion function.

The image fusion unit 340 may generate a fused image by passing a brightness value that has been improved for a dark area for each pixel, and combining only a bright image portion with an inversion coefficient that has been passed through the inverse transform filter application unit 330. .

The bright area enhancement unit 350 may perform brightness enhancement only on the bright area through Equation 5 below in the image fused by the image fusion unit 340.

Here, Y _inv is an inversion function, Y _dark is an improved brightness value in a dark area, and k is a brightness adjustment variable, which may be a parameter that adjusts brightness.

Dark pixels are brightened by Y _inv , but bright pixels must be made darker to prevent over-exposed, so it is recommended to use a brightness adjustment factor k.

To determine the brightness control coefficient k, S. Hsia and T. Kuo's paper "High-performance high dynamic range image generation by inverted local patterns, IET Image Processing, Vol. 9, No. 12, pp. 1083-1091 , Nov. 2015.”, an experiment is performed for each type of image using three images, and a configuration for adjusting the brightness of bright pixels by setting an appropriate k is disclosed, and the present invention The brightness control variable k may be used in the same manner in the embodiment of, but is not limited thereto, and may be appropriately converted as necessary.

The brightness gain adjustment unit 360 may expand a luminance range for the entire range of the input image by using an auto gain control (AGC).

The second color space conversion unit 400 converts the YCbCr color space in which the brightness of the image is adjusted by the brightness adjustment unit 300 into a hue saturation value (HSV) color space, while converting the original image of the image input unit 100 into an RGB color space. It can convert from space to HSV color space.

The saturation compensation unit 500 includes a color saturation storage unit 510 and a brightness enhancement analysis unit to compensate for the color saturation in order to compensate for the lost color saturation in consideration of the saturation of the original image and the brightness change value of the image whose brightness is adjusted. 520, a compensation coefficient derivation unit 530, and a color saturation degree application unit 540.

The color saturation storage unit 510 may store a color saturation of an image whose brightness is adjusted by the brightness adjustment unit 300.

The brightness enhancement analysis unit 520 may compare and analyze the color saturation of the original image and the image whose brightness is adjusted by the brightness adjustment unit 300 and the color saturation of the original image.

In one embodiment, when the brightness increases, the perceived color saturation decreases compared to the brightness. Therefore, the brightness enhancement analysis unit 520 can maintain the image information by increasing the color saturation proportionally as the brightness increases. have.

The compensation coefficient derivation unit 530 may derive a compensation coefficient in consideration of a value with a reduced color saturation derived from the brightness enhancement analysis unit 520.

The compensation coefficient uses the luminance range enlarged by using the automatic gain adjustment, and can be generated by using Equation 6 below.

Here, S'is the saturation compensation coefficient, S is the S channel value (saturation) of the original image converted to the HSV color space, Th _dark is the threshold for improvement of the dark area used in Equation 2, and Y _in is the signal value of the Y channel of the input image, and Y _mean is the average brightness of the input image.

The color saturation application unit 540 may compensate and apply the reduced color saturation of the original image by using the saturation compensation coefficient derived from the compensation coefficient derivation unit 530.

The third color space conversion unit 600 may convert the original image converted into the HSV color space into an RGB color space.

The image output unit 700 receives the original image converted to the RGB color space by the third color space conversion unit 600 and finally outputs an HDR image that has solved the problem of decreasing color saturation to an image output device such as a display. have.

The image output device is a device that outputs an image such as a display or a beam projector to the outside and provides it to a user, as well as a device that records external images such as CCTV, black box, and camera and converts it to be stored in an internal storage device. It may include all of, and may include all methods of using images, such as transmitting the image to the outside and storing it inside.

2 is a flowchart illustrating a method of generating an HDR image according to an embodiment of the present invention.

An original image for performing HDR conversion may be input (S1100).

In order to adjust the brightness of the original image, an original image composed of an RGB color space may be converted into a YCbCr color space (S1200).

The brightness component value of the image converted to the YCbCr color space can be adjusted to increase or decrease (S1300), and a specific brightness control method will be described with reference to an embodiment of FIG. 3 below.

The brightness-controlled image composed of the YCbCr color space may be converted into an HSV color space image (S1400).

An original image composed of an RGB color space may be converted into an HSV color space (S1500).

The color saturation of the original image may be compensated by using a compensation variable derived from the image whose brightness is adjusted (S1600), and a specific color saturation compensation method will be described with reference to an embodiment of FIG. 4 below.

Since the original image for which color saturation is compensated is composed of an HSV color space, it may be converted into an RGB color space to output an image (S1700).

The HDR image converted to the RGB color space in which the problem of color saturation reduction is solved may be output to the outside through the image output device (S1800).

3 is a flowchart illustrating a method of adjusting brightness of an image according to an embodiment of the present invention. In particular, FIG. 3 is a diagram specifically illustrating the step of adjusting the brightness of an image in step S1300.

In step S1210, a histogram for a brightness component value (Y channel) may be generated for an input image subjected to color conversion with YCbCr in step S1200. By analyzing the generated histogram, the number of histograms corresponding to the bright area and the dark area may be calculated based on the brightness component value of the image.

The method of calculating the number of histograms of the bright area (Hi) and the dark area (Lo) is specifically disclosed in Equation 1, and using the number of histograms of the bright area and the dark area, the excess area is determined according to the conditions of Table 1. It can be classified into, light or dark areas.

In step S1230, the dark area and the dark area of the excessive area may be improved by using Equation 2 above based on information (excess area, bright area, dark area) classified through histogram analysis.

In step S1220, an inversion coefficient may be calculated for the Y channel of the input image through an inverse kernel based on block processing, and the inverse kernel is a 2×2 maximum filter. And a low pass filter having a size of 3×3, and an inversion coefficient may be calculated through an inverse operation on a result of filtering the inversion kernel.

The maximum filter is composed of Equation 3 and is used to bring the effect of saving the detail of the input image, and the low-pass filter is composed of Equation 4 and is jagging artifacts that occur while using the maximum filter. Can be used to remove

In the inverse operation, in order to avoid positive saturation and negative saturation, a dark region may be brightened and a bright region may be darkened using an inversion function.

In step S1240, an inverse transform filter image and an image with improved brightness in the dark area are combined. The brightness value after brightness enhancement for the dark area for each pixel passes, and the inverse transform filter application unit 330 for only the bright image portion. It is possible to generate a fused image by combining with the inversion coefficient through

In step S1250, brightness enhancement may be performed only on a bright area of the entire area of the input image, and brightness enhancement may be achieved through Equation 5 above.

In step S1260, the luminance range may be expanded for the entire range of the input image by using an auto gain control (AGC).

4 is a flowchart illustrating a method of compensating for saturation according to an embodiment of the present invention. Particularly, FIG. 4 is a diagram illustrating a step of compensating the color saturation of an image in step S1600 in detail.

In step S1610, the color saturation of the original image converted to the HSV color space in step S1400 and the color saturation of the brightness-adjusted image converted to the HSV color space image in step S1500 may be stored.

In step S1620, the color saturation of the original image and the color saturation of the brightness-adjusted image may be compared and analyzed.

In step S1630, a compensation coefficient may be derived in consideration of a value with reduced color saturation by receiving the data analyzed in step S1620, and the compensation coefficient may be derived using Equation 6 above.

In step S1640, the reduced color saturation of the original image may be compensated and applied using the derived compensation coefficient.

5 to 6 are diagrams for comparing the performance of the HDR image processing method of the present invention.

5 is a comparison diagram of an image subjected to HDR processing for three types of images in the prior art and an image subjected to HDR processing according to an embodiment of the present invention.

5A shows three types of original image images used as input images to compare image processing results.

FIG. 5B is a result image processed using the CLAHE method. Compared to (a), contrast is improved, but color saturation is reduced.

5C is a result image processed using the ILP method, and it can be seen that there is no change in overall color saturation in the same area as the original image.

5D is a result image processed using the present invention. According to the HDR image processing method processed according to an embodiment of the present invention, color in a dark area is adaptively compensated for color saturation according to a change in brightness. It can be seen that the saturation is improving.

6 is a diagram illustrating a comparison performed using a Visual Difference Predictor (VDP) index to confirm a result of improving color saturation in order to evaluate the performance of the present invention.

VDP is a paper by R. Mantiuk, K. Myszkowski, and H. Seidel (Visual difference predictor for HDR images, Proc. of IEEE International Conference on Systems, Man and Cybernetics, Hague, Netherlands, pp. 2763-2769, 2004.) It is a perceptual metric method that can predict whether the difference between two images can be visually distinguished or not.

6 shows an ILP method for an image of a girl and a VDP result for an image processing result according to an embodiment of the present invention. 6A is a VDP of an image processing result using an ILP method, and (b) shows a VDP of a result processed by an embodiment of the present invention.

Compared to (a) of FIG. 6, it can be seen that (b) contains a lot of red areas, which are areas in which the color saturation has changed a lot, and in particular, the difference in color saturation of the dark areas on the right is greatly improved compared to the bright areas on the left It can be confirmed that it is.

The present invention proposes an HDR imaging method in which color saturation is compensated. In addition to the HDR method based on the existing regional inversion pattern, color saturation is adaptively compensated according to brightness change, thereby reducing color saturation in dark and bright areas You can solve the problem.

Features, structures, effects, and the like described in the above-described embodiments are included in at least one embodiment of the present invention, and are not necessarily limited to only one embodiment. Further, the features, structures, effects, etc. illustrated in each embodiment may be combined or modified for other embodiments by a person having ordinary knowledge in the field to which the embodiments belong.

Accordingly, contents related to such combinations and modifications should be construed as being included in the scope of the present invention. In addition, although the embodiments have been described above, these are only examples and do not limit the present invention, and those of ordinary skill in the field to which the present invention belongs are illustrated above without departing from the essential characteristics of the present embodiment. It will be seen that various modifications and applications that are not available are possible. For example, each component specifically shown in the embodiments can be modified and implemented. And differences related to these modifications and applications should be construed as being included in the scope of the present invention defined in the appended claims.

100: video input unit
200: first color space conversion unit
300: brightness adjustment unit
400: second color space conversion unit
500: saturation compensation unit
600: third color space conversion unit
700: video output unit

Claims (10)

In the device for generating HDR (High Dynamic Range) images,
A first color space conversion unit for generating a first converted image converted from the input image into a YCbCr color space;
A brightness control unit for adjusting the brightness of the first converted image;
A first converted image whose brightness is adjusted and a second color space converter configured to convert the input image into an HSV color space;
The color saturation of the input image converted to the HSV color space is calculated by comparing the saturation of the first converted image converted to the HSV color space and the saturation of the input image converted to the HSV color space, and the calculated color saturation is calculated. A saturation compensation unit to compensate; And
A third color space conversion unit converting the input image whose saturation is compensated into an RGB color space;
HDR image generating apparatus comprising a. The method of claim 1,
The brightness control unit,
A histogram analysis unit for generating and analyzing a histogram of the first transformed image;
A dark area enhancement unit that improves a dark area based on a result of the histogram analysis;
An inverse transform filter application unit for applying an inverse transform filter to the first transformed image;
An image fusion unit for fusing a brightness value obtained by improving the brightness by the dark area enhancement unit and a result image of the inverse transform filter application unit; And
A brightness improving unit that adjusts the brightness of the image output from the image fusion unit;
HDR image generating apparatus comprising a. The method of claim 2,
The brightness improving unit,
A bright area enhancement unit that adjusts brightness contrast only in the bright area; And
A brightness gain adjustment unit that expands a luminance range for the entire area of the image for which the brightness parameter is adjusted using an auto gain control method;
HDR image generating apparatus comprising a. The method of claim 2,
The inverse transform filter application unit performs dark area enhancement and calculates an inversion coefficient for the input image through a block-processing-based inversion kernel in the Y channel, and the inversion kernel includes a maximum filter and a low pass filter. filter), and then inverting the HDR image generating apparatus. The method of claim 1,
The saturation compensation unit,
A color saturation level storage unit for storing a color saturation level of the input image;
A brightness enhancement analysis unit for comparing and analyzing a brightness region of the input image and a third converted image converted by the second color space conversion unit on the first converted image;
A compensation coefficient derivation unit for deriving a color saturation compensation coefficient of the input image according to a comparison analysis result of the brightness enhancement analysis unit; And
A color saturation degree applying unit that compensates and applies the color saturation degree of the input image using the derived compensation coefficient;
HDR image generating apparatus comprising a. In the method of generating a high dynamic range (HDR) image,
Generating a first transformed image obtained by converting the input image into a YCbCr color space;
Controlling the brightness of the first converted image;
Generating a second converted image obtained by converting the first converted image into an HSV color space and a third converted image obtained by converting the input image into an HSV color space;
Compensating the saturation of the third transformed image by comparing the saturation of the second transformed image and the third transformed image; And
Converting the third converted image for which saturation is compensated into an RGB color space;
HDR image generation method comprising a. The method of claim 6,
Controlling the brightness of the first converted image,
Generating and analyzing a histogram of the first transformed image;
Improving the dark area determined through the histogram analysis;
Applying an inverse transform filter to the first transformed image;
Generating a fusion image of a brightness value obtained by improving the dark area and an image to which the inverse transform filter is applied; And
Adjusting the brightness of the fusion image;
HDR image generation method comprising a. The method of claim 7,
The step of adjusting the brightness,
Adjusting brightness contrast only in a bright area; And
Expanding the luminance range for the entire area of the image for which the luminance parameter is adjusted using an auto gain control method;
HDR image generation method comprising a. The method of claim 7,
The inverse transform filter undergoes dark area enhancement and calculates an inversion coefficient for the input image through a block-processing-based inversion kernel in the Y channel,
Wherein the inversion kernel performs a maximum filter and a low pass filter and then inverts the HDR image. The method of claim 6,
Compensating for the saturation,
Storing a color saturation degree of the input image;
Comparing and analyzing a brightness region of the third transformed image and the input image;
Deriving a color saturation compensation coefficient according to a change in brightness of the input image using the comparison analysis result; And
Compensating and applying the color saturation of the input image using the derived compensation coefficient;
HDR image generation method comprising a.

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