KR101761947B1 - Device and method for reducing blooming of camera image - Google Patents

Abstract

A method and apparatus for reducing blooming of a camera image are disclosed. A blooming reduction apparatus of a camera image includes a first histogram detection unit for calculating a frequency of pixels in accordance with a gray level classification predetermined for each pixel included in a ROI set for an input image; Calculating a ratio of pixels included in a predetermined high brightness level range by referring to the frequency of pixels in accordance with the gray level classification, and determining whether a ratio of pixels included in the calculated high brightness level range exceeds a predetermined set value, A first histogram analyzing unit for determining whether or not the image is generated; And an automatic exposure adjusting unit for adjusting the target value of automatic exposure (AE) of the image sensor unit to provide an input image step by step when it is determined that blooming has occurred. A second histogram analyzer for calculating an average brightness of a gamma-corrected image of an input image provided from the image sensor; A second histogram analyzer configured to adjust a gamma curvature parameter such that an average brightness of the gamma corrected image coincides with an average brightness of an input image before occurrence of blooming within a predetermined range; And a gamma curve converting unit for calculating the new gamma curve for gamma correction of an input image provided from the image sensor unit using the knee point determined by the first histogram analyzing unit and the adjusted gamma curvature parameter.

Description

[0001] The present invention relates to a method and apparatus for reducing blooming of a camera image,

The present invention relates to a method and apparatus for reducing blooming of a camera image.

In order to improve driver comfort and safety during the recent driving of a vehicle, a camera is installed on the front and rear of the vehicle. A driver displays a captured image through a display provided on the driver's instrument panel, recognizes objects and lanes around the vehicle, And a variety of systems are being researched and developed.

In general, a camera has a backlight function. When a high luminance area and a low luminance area coexist in a photographed image, a backlight function is applied to a low luminance area with a weighted value, and iris opening (IRIS open) and gain up Up) or the like is performed.

Accordingly, when the backlight compensation operation is performed, the brightness level of the low brightness area is increased, and the user can normally recognize the dark subject. At this time, the brightness level of the high brightness area increases as if the bright subject is saturated A visible blooming phenomenon occurs.

As described above, in the case of a camera image photographed using an image pickup device, a strong blooming phenomenon occurs in a high luminance region such as a headlight of an opposite vehicle in a nighttime low illuminance environment, and due to saturation of the input image, Or difficulty in recognizing lanes or objects in the image.

Accordingly, there is a need for a method for appropriately reducing the blooming phenomenon for a camera image or the like photographed in a low-illuminance environment.

An object of the present invention is to provide a method and apparatus for reducing blooming of a camera image, which can reduce blooming of a camera output image used for recognition of objects or pedestrians in a nighttime environment.

The present invention relates to a camera image captured in a low-illuminance environment and a night vision camera image captured in a low-illuminated environment, in which a blooming caused by a headlight of a vehicle is appropriately reduced, And to provide a reduction method and apparatus.

In order to efficiently reduce blooming, which is a supersaturation region existing in an image, and to allow a subject existing in a dark region of the image to be recognized normally, the present invention provides a blooming And to provide a reduction method and apparatus.

Other objects of the present invention will become readily apparent from the following description.

According to an aspect of the present invention, there is provided a blooming reduction apparatus for a camera image, the apparatus comprising: a first histogram calculating unit for calculating a frequency of pixels in accordance with a gray level classification previously designated for each pixel included in a ROI set for an input image; A detection unit; Calculating a ratio of pixels included in a predetermined high brightness level range by referring to the frequency of pixels in accordance with the gray level classification, and determining whether a ratio of pixels included in the calculated high brightness level range exceeds a predetermined set value, A first histogram analyzing unit for determining whether or not the image is generated; An automatic exposure adjusting unit for adjusting the target value of the automatic exposure (AE) of the image sensor unit to provide an input image step by step when it is determined that blooming has occurred; A second histogram analyzer for calculating an average brightness of a gamma-corrected image of an input image provided from the image sensor; A second histogram analyzer configured to adjust a gamma curvature parameter such that an average brightness of the gamma corrected image coincides with an average brightness of an input image before occurrence of blooming within a predetermined range; And a gamma curve converting unit for calculating the new gamma curve for gamma correction of an input image provided from the image sensor unit using the knee point determined by the first histogram analyzing unit and the adjusted gamma curvature parameter A blooming reduction device for a camera image is provided.

The first histogram analyzing unit may calculate a minimum gray level value of a gray level having a highest pixel frequency in a predetermined gray level range among the histograms detected in the input image adjusted by the target value adjusting unit by the automatic exposure adjusting unit, It can be determined as a Knee-point.

The second histogram analyzing unit may calculate an average of the remaining gray levels excluding the gray level predetermined to mean saturated pixels of the image to calculate the average brightness of the gamma corrected image.

The second histogram analyzing unit may calculate an average brightness of the gamma corrected image using the following equation.

Here, AVG _B is the average brightness of the gamma corrected image, n is the number of remaining gray levels excluding the gray level predetermined to mean saturated pixels of the image, M_GrayLevel (i) is the brightness level of each gray level And PB (i) may be the frequency of pixels for the gray level.

According to another aspect of the present invention, there is provided a blooming reduction method performed by a blooming reduction apparatus of a camera image, the method comprising: calculating a frequency of a pixel according to a gray level classification predetermined for each pixel included in a ROI ; Calculating a ratio of pixels included in a predetermined high brightness level range by referring to the frequency of pixels in accordance with the gray level classification, and determining whether a ratio of pixels included in the calculated high brightness level range exceeds a predetermined set value, Judging whether or not it has occurred; And adjusting the target value of the automatic exposure (AE) of the image sensor unit providing the input image in a stepwise manner if it is determined that blooming has occurred.

A minimum gray level value of a gray level having a highest pixel frequency in a predetermined gray level range is determined as a knee point for calculating a new gamma curve from the histogram detected in the input image after the adjustment of the target value Steps may be further included.

Calculating an average brightness of a gamma-corrected image of an input image provided from the image sensor unit; Adjusting a gamma curvature parameter such that an average brightness of the gamma corrected image coincides with an average brightness of an input image before occurrence of blooming within a predetermined range; And calculating the new gamma curve for gamma correction of the input image provided from the image sensor unit using the determined knee point and the adjusted gamma curvature parameter.

The average brightness of the gamma corrected image may be calculated as an average of the gray levels other than the predetermined gray level to mean saturated pixels of the image.

The average brightness of the gamma corrected image can be calculated using the following equation.

Here, AVG _B is the average brightness of the gamma corrected image, n is the number of remaining gray levels excluding the gray level predetermined to mean saturated pixels of the image, M_GrayLevel (i) is the brightness level of each gray level And PB (i) may be the frequency of pixels for the gray level.

According to still another aspect of the present invention, there is provided a recording medium on which a program that can be read by a digital processing apparatus is recorded for performing a blooming reduction method of a camera image.

Other aspects, features, and advantages will become apparent from the following drawings, claims, and detailed description of the invention.

According to the embodiment of the present invention, it is possible to reduce the blooming of the camera output image used for recognizing objects or pedestrians in the nighttime environment.

In addition, there is also an effect of appropriately reducing the blooming caused by the headlight of the vehicle in a state where the brightness loss of the entire image is reduced with respect to the camera image and the night vision camera image captured in the low-illuminance environment.

In addition, there is also an effect that the image brightness of an area other than the blooming area can be improved in order to efficiently reduce blooming, which is a supersaturation area existing in the image, and to normally recognize a subject in a dark area of the image.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic view showing a configuration of a blooming mitigation apparatus according to an embodiment of the present invention. FIG.
Figure 2 illustrates a ROI setting method in accordance with an embodiment of the present invention.
FIG. 3 illustrates a histogram detection state according to an embodiment of the present invention. FIG.
4 is a graph showing a result of blooming reduction according to a target value adjustment of automatic exposure (AE) according to an embodiment of the present invention.
5 is a diagram showing a result of blooming reduction by exposure value correction according to an embodiment of the present invention.
6 illustrates average brightness reduction of a full image according to a target value variation of automatic exposure in accordance with an embodiment of the present invention.
FIG. 7 illustrates various gamma curves that may be generated according to variations in the calculated knee point and gamma curvature according to an embodiment of the present invention. FIG.
8 is a view comparing a final image corrected by the Blooming reduction process according to an embodiment of the present invention with an original image before correction.
9 illustrates a blooming mitigation method in accordance with an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, the terms "comprises" or "having" and the like refer to the presence of stated features, integers, steps, operations, elements, components, or combinations thereof, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

Also, the terms " part, "" unit," " module, "and the like, which are described in the specification, refer to a unit for processing at least one function or operation and may be implemented by hardware or software or a combination of hardware and software .

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail.

2 is a diagram illustrating a ROI setting method according to an embodiment of the present invention. FIG. 3 is a diagram illustrating a ROI setting method according to an embodiment of the present invention. FIG. 7 is a diagram illustrating a histogram detection state according to an embodiment of the present invention. FIG. FIG. 4 is a graph showing a result of blooming reduction according to a target value adjustment of automatic exposure (AE) according to an embodiment of the present invention. FIG. 6 is a diagram illustrating an average brightness reduction of a whole image according to a target value variation of automatic exposure according to an exemplary embodiment of the present invention. Referring to FIG. FIG. 7 illustrates various gamma curves that can be generated according to the calculated knee point and gamma curvature changes according to an exemplary embodiment of the present invention. FIG. 8 is a flowchart illustrating a blooming reduction process according to an exemplary embodiment of the present invention. And comparing the corrected final image with the original image before correction.

As will be described later, the blooming mitigation apparatus according to the present embodiment includes two histogram detection units (see the first histogram detection unit 120 and the second histogram detection unit 140 in FIG. 1) The brightness distribution of the photographed image is discriminated, and the automatic exposure value of the image sensing device and the gradient of the gamma curve applied to the image are simultaneously converted according to the result, thereby suppressing the blooming phenomenon occurring in the photographed image, It has an advantage that it can be corrected.

Hereinafter, a blooming mitigation apparatus according to an embodiment of the present invention will be described in detail with reference to the related drawings.

2, the blooming mitigation apparatus includes an image sensor unit 110, an ROI setting unit 115, a first histogram detecting unit 120, a first histogram analyzing unit 125, an automatic exposure (AE) adjusting unit 130, A gamma curve correction unit 135, a second histogram detection unit 140, a second histogram analysis unit 145, and a gamma curve conversion unit 150.

The ROI setting unit 115 sets a region of interest (ROI) to accurately determine whether there is a blooming in an image input from the image sensor unit 110.

For example, in the case of a full-length camera, the blooming phenomenon occurs mainly in the headlight portion of the opposite vehicle, which is a vehicle coming from the front. Therefore, the ROI setting unit 115 can be configured to set the ROI around the traveling path of the opposite vehicle as illustrated in FIG.

The region of interest can be set to a rectangular shape, for example, by determining the starting pixel coordinates (x, y) and the horizontal and vertical lengths of the ROIs in the entire image. The region of interest may be set to any value depending on the camera mount position, but may generally be set to a slightly offset from the entire image to the lower left as shown in FIG.

The first histogram detecting unit 120 calculates the frequency with respect to the gray level of the image for each pixel included in the ROI set by the ROI setting unit 115 with respect to the input image.

In order to reduce the complexity in the frequency calculation process, the frequency can be calculated in a state where the interval of the gray level of the image having the range of 0-255 is divided by 8 and set to the 32 level as illustrated in FIG.

The first histogram analyzer 125 determines whether or not blooming has occurred based on the detected histogram distribution, and sets a knee-point value of the gamma curve applied to the subsequent stage.

FIG. 3 illustrates histogram detection results. The first histogram analyzing unit 125 can determine whether or not blooming of an image occurs by using the distribution of the detected histogram.

The first histogram analyzing unit 125 calculates the frequency of each gray level calculated by the first histogram detecting unit 120 as a ratio with respect to the frequency count of the entire level, It is possible to determine whether or not blooming has occurred in the corresponding image.

For example, when the ratio of the pixels corresponding to the four highest levels of high brightness (i.e., the range of gray levels 224 to 255) is 1% or more, the first histogram analyzing unit 125 generates excessive blooming . Of course, it is a matter of course that the high luminance level set in accordance with the condition of the sensed image and the pixel ratio thereof can be variously changed.

Generally, when a saturated region such as a blooming occurs in an image, the level value of the saturation region can be lowered by correcting the brightness at the subsequent stage, but it is impossible to restore the already oversaturated and lost image data.

Accordingly, when it is determined that the first histogram analyzing unit 125 generates blooming, the automatic exposure adjusting unit 130 gradually reduces the target value of the automatic exposure (AE) of the image sensor unit 110 to 1 Thereby performing a function of reducing the size of blooming.

Generally, as the set target value of automatic exposure (AE) is higher, the shutter speed and aperture are adjusted so that the brightness of the image is increased. In the case of the low-illuminance environment, the gain value is adjusted to amplify the input image data . Therefore, in a low-illuminance environment such as a nighttime, due to a target value of a predetermined automatic exposure, an excessive blooming phenomenon may be caused when a subject of high luminance approaches.

Therefore, when the first histogram analyzing unit 125 determines that blooming has occurred (for example, the pixel ratio distributed in four levels of high brightness of the histogram is 1% or more), the blooming reduction apparatus according to the present embodiment performs the automatic exposure The adjustment unit 130 gradually adjusts the target value of the automatic exposure so that the blooming phenomenon is reduced (that is, the pixel ratio distributed over the four levels of high brightness of the histogram is less than 1%).

FIG. 4 shows a result of blooming reduction according to the target value adjustment of the automatic exposure (AE).

Referring to FIG. 4, it can be confirmed that the blooming phenomenon is reduced by adjusting the target value of the automatic exposure. However, in addition to the pure function of reducing the blooming phenomenon, the brightness of the entire image may gradually become dark.

To improve this phenomenon, the blooming reduction apparatus according to the present embodiment can automatically correct the lost brightness by newly calculating and applying a gamma curve to the gamma curve correction unit 135 as described later. The target value of the automatic exposure (AE) applied to the automatic exposure adjusting unit 130 may be, for example, a ratio of pixels corresponding to two highest levels of high brightness (levels corresponding to 240 to 255 gray levels) It is considered that a high-luminance subject disappears from the image, thereby restoring the target value of the previously set automatic exposure, and thus the gamma curve can be automatically corrected to the original value.

The first histogram analyzing unit 125 analyzes not only the presence of a blooming phenomenon in the image but also the histogram distribution at the time of occurrence of blooming as described above to determine a knee point of a gamma curve to be applied to the subsequent stage Further functions can be performed. Here, the knee point means an inflection point at which the variation width of the output signal with respect to the input signal sharply decreases in an arbitrary specific curve.

Generally, in the case of a camera image in a nighttime or low-illuminance environment, an image of a dark subject is input and the brightness is corrected by changing the output level of the input image using the gamma curve of the gamma curve converting unit 150 at the subsequent stage.

As shown in FIG. 5, the first original image generated by blooming is reduced and inputted through the exposure value correction process of the automatic exposure adjustment unit 130, and the first histogram analysis unit 125 calculates the exposure value correction (For example, gray levels 144 to 144) corresponding to the remaining high luminance areas excluding the predetermined levels (for example, the highest four levels) of the histogram detected in the input second original image, 223), and determines the minimum gray level value as the knee-point of the gamma curve to be applied.

Referring to the example of FIG. 5, a value of 176, which is the minimum image gray level of the level 22, can be determined as a knee point. Therefore, even after the gamma curve correction unit 135 performs the brightness correction using the gamma curve, the photographed image provided by the image sensor unit 110 does not greatly increase the saturation of the blooming size or the high brightness level, There is an advantage that the brightness of the subject can be increased.

The gamma curve correction unit 135 performs a function of changing the brightness of the input image to be dark or bright using a gamma curve indicating the relationship of the output level to the input level.

When blooming occurs in the original image, a knee point calculated by the first histogram analyzer 125 and a Gamma Curve Ratio (Gamma Curve Ratio) calculated by a second histogram analyzer 145, which will be described later, By applying the newly calculated gamma curve, the brightness of the darkened image can be improved by adjusting the exposure value while suppressing the increase in blooming of the image.

The second histogram detecting unit 140 and the second histogram analyzing unit 145 are located at the rear end of the gamma curve correcting unit 135 and use the gamma curve corrected by the gamma curve correcting unit 135, It receives input and performs specified processing.

Unlike the first histogram detector 120, the second histogram detector 140 detects the frequency of the input pixel with respect to the gray level of the entire image.

6, if the first histogram analyzing unit 125 determines that blooming has occurred, the automatic exposure adjusting unit 130 may reduce the target value of the automatic exposure to reduce the blooming, so that even if the image is gamma corrected with the same curvature, The histogram for the image moves to the darker side than the pre-correction image and the average brightness is lowered.

The second histogram analyzing unit 145 converts the distribution of the detected histogram into the ratio of the total number of pixels, and calculates the average brightness of the entire image using the ratio. At this time, an average of remaining levels (for example, 30 levels) excluding a predetermined level (for example, two highest brightness levels corresponding to gray levels 240 to 255) designated to mean saturated pixels of an image is calculated.

The average brightness (AVG _B ) of the whole image is calculated by multiplying the middle value (M_GrayLevel (i)) of the histogram brightness levels by the ratio of the frequency (for example, PB (i)) and then calculating the average.

The second histogram analyzing unit 145 obtains the average brightness of the entire image changed by the automatic exposure value adjustment after the occurrence of the blooming as described above and then compares the average brightness of the entire image with the brightness of the stored before blooming, To adjust the gamma curvature (?) Parameter.

The gamma curve converting unit 150 calculates a new gamma curve to be applied to the gamma curve adjusting unit using the knee point calculated by the first histogram analyzing unit 125 and the gamma curvature calculated by the second histogram analyzing unit 145 And stores it in an LUT (LookUpTable) format.

FIG. 7 shows examples of various gamma curves that can be generated according to the calculated knee point and the change in gamma curvature. As shown in the figure, the generated curve can suppress the blooming and saturation of the image as the output ratio is lowered from the high luminance input level located at the knee point. As the average brightness of the image is lowered, So that the brightness of the subject in the dark region of the image can be improved.

As described above with reference to the related drawings, the blooming reduction apparatus according to the present embodiment is capable of reducing the blurring phenomenon occurring in a high luminance subject existing in the photographed image while preserving the brightness of the dark region in the output image of the camera used in the nighttime environment Can be reduced.

That is, the histogram distribution for each of the image input from the image sensor unit 110 and the gamma correction image by the gamma curve correction unit 135 is analyzed to determine whether or not blooming occurs. If blooming occurs, the image sensor unit 110 to adjust the knee point and the curvature of the gamma curve according to the distribution of the histogram and to correct the brightness of the darkened image according to the blooming reduction without increasing the blooming phenomenon.

FIG. 8 shows a comparison between a final image corrected by the blooming reduction apparatus according to the present embodiment and a final image before correction.

8 (a), 8 (c), and 8 (e) are diagrams for explaining an example in which the original image input from the image sensor unit 110, the gamma- 8 (b), 8 (d), and 8 (f) show the images to which the exposure correction for reducing blooming and the modified gamma conversion curve are applied.

As shown in the figure, when the blooming reduction apparatus according to the present embodiment is used, strong blooming occurs in the headlight of the opposite vehicle in the output image of the camera and the night vision camera used in the nighttime low illumination environment, It is possible to prevent the object from being recognized and at the same time, the brightness of the object in the dark region can be increased without increasing the blooming phenomenon, so that accurate image information can be provided to the driver.

9 is a diagram illustrating a blooming mitigation method according to an embodiment of the present invention.

Referring to FIG. 9, in step 910, the blooming reduction apparatus sets a region of interest (ROI) to accurately determine whether blooming exists in the image input from the image sensor unit 110. The region of interest may be set to a rectangular shape, for example, by determining the starting pixel coordinates (x, y) and the horizontal and vertical lengths of the ROIs in the entire image.

In step 920, the blooming reduction device calculates the frequency of the gray level of the image for each pixel included in the region of interest set for the input image.

In step 930, the blooming mitigation device determines whether a blooming phenomenon has occurred. For example, the blooming mitigation apparatus calculates the frequency of each calculated gray level as a ratio to the frequency of the whole level, refers to the ratio of the pixels included in the predetermined highest brightness level using the ratio, It is possible to judge whether or not it has occurred.

As a result of the determination in step 930, if the blooming phenomenon does not occur, the corrected image will be output according to the currently applied gamma curve. Since this is a general process and is somewhat distant from the gist of the present invention, the description thereof will be omitted.

However, if the blooming phenomenon occurs, the blooming reduction apparatus operates to reduce the blooming size by gradually lowering the target value of the automatic exposure (AE) of the image sensor unit 110 in step 940, Determines a knee-point for newly calculating a new gamma curve so that the brightness can be automatically corrected.

For example, the knee point may be adjusted to a predetermined level (for example, the highest brightness level) excluding the predetermined levels (for example, the uppermost four levels) of the histogram detected in the input image by reducing the blooming through the exposure value correction process (For example, levels from 19 to 28 as 10 levels corresponding to gray levels 144 to 223), and the minimum gray level value among the histograms of the histograms is calculated as a knee point of the gamma curve to be applied. .

In step 950, the blooming mitigation apparatus detects the gray-level pixel frequency for the gamma-corrected whole image using the gamma curve currently applied.

The blooming mitigation apparatus then calculates the average brightness for the gamma corrected full image in step 960 and adjusts the gamma curvature parameter for the new gamma curve calculation.

The average brightness of the entire image may be, for example, the remaining levels except for a predetermined level (for example, two highest brightness levels corresponding to the gray level 240 to 255) designated as a saturated pixel of the image (for example, 30 levels ). ≪ / RTI >

Also, the gamma curvature parameter may be adjusted so as to obtain an average brightness of the entire image changed by automatic exposure value adjustment after occurrence of blooming, and then compare the average brightness with the brightness of the stored blooming before the stored blooming.

In step 970, the blooming mitigation device calculates a new gamma curve using the knee point determined in step 940 and the gamma curvature parameter adjusted in step 960.

The image input from the image sensor unit 110 is gamma corrected by the new gamma curve calculated by the above-described process and output (step 980).

It is a matter of course that the above-described blooming mitigation method may be performed by an automated procedure in a time-series sequence by a built-in program or the like installed in the digital processing apparatus. The codes and code segments that make up the program can be easily deduced by a computer programmer in the field. In addition, the program is stored in a computer readable medium readable by the digital processing apparatus, and is read and executed by the digital processing apparatus to implement the method. The information storage medium includes a magnetic recording medium and an optical recording medium.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention as defined in the following claims And changes may be made without departing from the spirit and scope of the invention.

110: Image sensor unit
115: ROI setting section
120: first histogram detector
125: first histogram analyzing unit
130: automatic exposure (AE) adjustment unit
135: Gamma curve correction unit
140: second histogram detector
145: second histogram analyzing unit
150: gamma curve conversion section

Claims (9)

A blooming mitigation apparatus for a camera image,
A first histogram detecting unit for calculating a frequency of pixels in accordance with a gray level classification previously designated for each pixel included in a ROI set for an input image;
Calculating a ratio of pixels included in a predetermined high brightness level range by referring to the frequency of pixels in accordance with the gray level classification, and determining whether a ratio of pixels included in the calculated high brightness level range exceeds a predetermined set value, A first histogram analyzing unit for determining whether or not the image is generated;
An automatic exposure adjusting unit for adjusting the target value of the automatic exposure (AE) of the image sensor unit to provide an input image step by step when it is determined that blooming has occurred;
A gamma correction unit configured to calculate an average brightness of an image obtained by gamma correction of an input image provided from the image sensor unit and to calculate a gamma curvature parameter such that an average brightness of the gamma corrected image coincides with an average brightness of an input image before blooming, A second histogram analyzing unit for adjusting the second histogram analyzing unit; And
And a gamma curve converting unit for calculating a new gamma curve for gamma correction of an input image provided from the image sensor unit using the knee point determined by the first histogram analyzing unit and the adjusted gamma curvature parameter,
Wherein the second histogram analyzing unit calculates an average of remaining gray levels excluding a gray level predetermined to mean saturated pixels of an image to calculate an average brightness of the gamma corrected image. The method according to claim 1,
The first histogram analyzing unit may calculate a minimum gray level value of a gray level having a highest pixel frequency in a predetermined gray level range among the histograms detected in the input image adjusted by the target value adjusting unit by the automatic exposure adjusting unit, And determines the knee point as the knee-point. delete The method according to claim 1,
Wherein the second histogram analyzing unit calculates an average brightness of the gamma corrected image using the following equation.

Here, AVGB is the average brightness of the gamma corrected image, n is the number of remaining gray levels excluding the gray level predetermined to mean saturated pixels of the image, and M_GrayLevel (i) is the middle of the brightness level for each gray level And PB (i) is the frequency of the pixel with respect to the gray level. A blooming mitigation method performed in a blooming mitigation apparatus of a camera image,
Calculating a frequency of pixels according to a gray level classification predetermined for each pixel included in a ROI set for an input image;
Calculating a ratio of pixels included in a predetermined high brightness level range by referring to the frequency of pixels in accordance with the gray level classification, and determining whether a ratio of pixels included in the calculated high brightness level range exceeds a predetermined set value, Judging whether or not it has occurred;
If it is determined that blooming has occurred, stepwise adjusting a target value of automatic exposure (AE) of an image sensor unit for providing an input image;
Calculating an average brightness of a gamma-corrected image of an input image provided from the image sensor unit;
Adjusting a gamma curvature parameter such that an average brightness of the gamma corrected image coincides with an average brightness of an input image before occurrence of blooming within a predetermined range; And
Calculating a new gamma curve for gamma correction of an input image provided from the image sensor unit using the knee point and the adjusted gamma curvature parameter,
Wherein the average brightness of the gamma corrected image is calculated as an average of gray levels other than a predetermined gray level to mean saturated pixels of the image. 6. The method of claim 5,
A minimum gray level value of a gray level having a highest pixel frequency in a predetermined gray level range among the histograms detected in the input image after the adjustment of the target value is determined as the knee point for calculating a new gamma curve Further comprising the steps of: delete 6. The method of claim 5,
Wherein the average brightness of the gamma corrected image is calculated using the following equation.

Here, AVGB is the average brightness of the gamma corrected image, n is the number of remaining gray levels excluding the gray level predetermined to mean saturated pixels of the image, and M_GrayLevel (i) is the middle of the brightness level for each gray level And PB (i) is the frequency of the pixel with respect to the gray level. A recording medium on which a program that can be read by a digital processing apparatus is recorded to perform a blooming reduction method of a camera image according to any one of claims 5, 6, and 8.

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