KR19980015067A - Image quality improvement method using quantized mean-separated histogram equalization with brightness compensation function and its circuit - Google Patents

Abstract

The image quality improvement method and circuit of the present invention quantizes input video signals, obtains an average of the input video signals on a screen basis and quantizes them, and outputs the quantized video signals to a predetermined number of quantized sub- Extracts a cumulative density function of each of a predetermined number of quantized subimages, outputs an accumulated cumulative density function value interpolated for each subimage by interpolation based on the cumulative density function obtained for each quantized subimage, And outputs a corrected average level by adding a correction value according to a predetermined correction function based on the average brightness of the video signal to the average level to output the compensated average level and quantizes the corrected average value based on the accumulated density function value interpolated for each sub- By independently histogram equalizing each sub-image, it is possible to effectively reduce sudden brightness changes and artifacts, While improving agent maintains the overall brightness of the given image, and, in particular, excessively dark or light to improve the contrast of an input video signal.

Description

Image quality improvement method using quantized mean-separated histogram equalization with brightness compensation function and its circuit

The present invention relates to an image quality improvement method using quantized mean-separated histogram equalization having a brightness compensating function and a circuit therefor. More particularly, the present invention relates to an image quality improvement method using a quantized average- And separately performing histogram equalization while compensating brightness of divided sub-images.

The basic operation of histogram equalization is to transform a given input image based on the histogram of the input image, where the histogram represents the gray level distribution in a given input image.

This histogram of gray levels provides an overall depiction of the appearance of the image. The appropriately adjusted gray level according to the sample distribution of the image improves the appearance or the contrast of the image.

Among many methods for improving the contrast, histogram equalization, which is a method for improving the contrast of a given image according to a sample distribution of an image, is most widely known and is disclosed in the following documents [1] and [2]: [1] JSLim , Two-Dimensional Signal and Image Processing, Prentice Hall, Englewood Cliffs, New Jersey, 1990, [2] RC Gonzalez and P. Wints, Digital Image Processing, Addison-Wesley, Reading, Massachusetts,

In addition, useful applications of histogram equalization methods including medical image processing and radar image processing are disclosed in [3] and [4] below: [3] J. Zimmerman, S. Pizer, E. Staab, E. Perry, W. McCartney, and B. Brenton, Evaluation of the Effectiveness of Adaptive Histogram Equalization for Contrast Enhancement, IEEE Tr. On Medical Imaging, pp. 304-412, Dec. 1988, [4] Y. Li, W. Wang , and DYYu, Application of adaptive histogram equalization to x-ray chest image, Proc. of the SPIE, pp. 513-514, vol.2321, 1994.

Therefore, the technique using the histogram of a given image has been applied to various fields such as medical image processing, infrared image processing, and radar image processing.

In general, histogram equalization has the effect of stretching the dynamic range so that the histogram equalization flattenes the distribution density of the resulting image and consequently improves the contrast of the image.

This characteristic of the widely known histogram equalization is a drawback in practical cases. That is, since the output density of the histogram equalization is constant, the average brightness of the output image is close to the middle gray level. In practice, for histogram equalization of analog images, the average brightness of the output image in the histogram equalization is exactly the middle gray level regardless of the average brightness of the input image. Obviously, this characteristic is not desirable in practical applications. For example, a scene taken at night may look like a scene taken during the day after histogram equalization.

In addition, the conventional histogram equalization circuit is required to have a configuration capable of storing all the occurrences of all the gray levels, thus causing a problem of high hardware cost. For example, assuming that the gray level (L) is L = 256, 256 memory elements are required to store the number of occurrences of all levels, and 256 accumulators are required to accumulate the number of occurrences of all levels Respectively.

An object of the present invention is to divide an input image quantized by level of an input image into a predetermined number of quantized sub images based on the average and to add a corrected average value obtained by adding a correction value to an average level according to an average brightness of an input image, Level of the quantized sub-images independently of the quantized sub-images to improve the image quality.

Another object of the present invention is to provide a method and an apparatus for quantizing an input image by dividing a quantized input image into a predetermined number of quantized sub images based on the quantized input image, The present invention provides a circuit for improving image quality by independently histogram equalizing each quantized sub-image using an average level.

According to an aspect of the present invention, there is provided a method for improving image quality by histogram equalizing an image signal represented by a predetermined number (L) of gray levels, the method comprising the steps of: (a) And outputting a quantized video signal; (b) obtaining an average of the inputted video signals on a screen basis and quantizing them to output a quantized average level; (c) dividing the quantized image signal into a predetermined number of quantized sub-images according to the quantized average level; (d) obtaining cumulative density functions of the predetermined number of quantized sub-images; (e) outputting a cumulative density function value interpolated for each sub-image by interpolation based on a cumulative density function obtained for each quantized sub-image; (f) outputting a compensated average level by adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level; And (g) independently histogram equalizing each of the quantized sub-images based on the accumulated density function value interpolated for each sub-image and the compensated average level.

According to another aspect of the present invention, there is provided an image quality improvement circuit for enhancing image quality by histogram equalizing an image signal represented by a predetermined number (L) of gray levels, the circuit comprising: A first quantization means for outputting a video signal that is generated by the first quantization means; First calculation means for calculating a gray level distribution of the quantized video signal on a screen basis; Second calculation means for calculating an average level of an input video signal on a screen basis; Second quantization means for quantizing the calculated average level and outputting a quantized average level; A brightness compensation means for adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level to output a compensated average level; Division means for dividing the gray level distribution calculated by the first calculation means into a predetermined number of quantized sub-images according to the quantized average level; Third calculation means for obtaining an accumulated density function for each quantized sub-image; Interpolating means for outputting a cumulative density function value interpolated for each sub-image by interpolation based on the cumulative density function calculated for each of the quantized sub-images; A brightness compensation means for adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level to output a compensated average level; And output means for outputting an improved signal by mapping the quantized sub-image to a new gray level according to the interpolated cumulative density function value and the compensated average level corresponding to the quantized sub-image.

1 is a diagram showing an example of quantizing an L level discrete signal into a Q level discrete signal in order to explain the quantization concept of the present invention.

2 is a diagram for explaining an interpolation concept applied to the present invention.

FIG. 3 is a block diagram of an image quality improvement circuit using quantized mean-separated histogram equalization having a brightness compensation function according to an embodiment of the present invention.

4A and 4B are diagrams illustrating an example of a brightness correction function applied to the present invention.

FIGS. 5A and 5B are diagrams showing examples of the relationship between the average level compensated by the brightness correction function shown in FIGS. 4A and 4B and the average level of the input image.

6 is a block diagram according to another embodiment of an image quality improvement circuit using quantized mean-separated histogram equalization having a brightness compensation function according to the present invention.

A description will be made of a picture quality improvement method using a quantized mean-separated histogram equalization with the brightness compensation function proposed in the present invention.

A given image X consists of L discrete gray levels {X ₀ , X ₁ , ..., X _L-1 }, where X ₀ = 0 represents the black level and X _{L -1} = 1 indicates a white level. Also, X _m ∈ {X ₀ , X ₁ , ..., X _L-1 }.

Quantizing the original discrete input levels {X ₀ , X ₁ , ..., X _L-1 } to a Q discrete level defined by {Z ₀ , Z ₁ , ..., Z _Q-1 } Z _Q-1 = X _L-1 referred to, and also _{Q 1 L, {Z 0,} Z 1, ..., Z Q-1} 1C {X 0, X 1, ..., X L-1 }.

An example of quantizing the discrete signal of the L level in the Q level discrete signal is shown in Fig.

Then, Q [X _k ] is called a quantization operation and is defined as follows.

Q [X _k ] = Z _q , if Z _q-1 X _K 1Z _q

{Z} = Q [{X }] and when both said _{Z m = Q [X m]} , X m is an average level of the original image, {Z} the quantized input image, Z _m is the average level quantization And divides the quantized input image {Z} into two sub-images {Z} _L and {Z} _U centered at Z _m . Here, all samples in the quantized sub-picture {Z} _L are less than the quantized average level (Z _m ) and all samples in the quantized sub-picture {Z} _U are larger than the quantized average level (Z _m ).

The quantized probability density function (PDF) of each of the sub-images {Z} _L and {Z} _U can be expressed by the following equations (1) and (2).

[Equation 1]

&Quot; (2) "

Here, P _L (Z _q) is the quantized sub-image {Z} and _L probability of the q th quantized gray level (Z _q) In, P _U (Z _q) is the q th quantized by the quantization sub-image {Z} _U the gray level and the (Z _q) probability, N _q ^L, N _q ^U represent the number of times the level (Z _q) is represented in the sub-image {Z} _L, the quantized sub-image {Z} _U, respectively quantized, N _L , N _U represents the total number of samples of each of the quantized sub-picture {Z} _L and the quantized sub-picture {Z} _U.

Then, the cumulative density function (CDF) of each of the quantized sub-image {Z} _L and the quantized sub-image {Z} _U is defined by the following equations (3) and (4).

&Quot; (3) "

&Quot; (4) "

Where C _L (Z _m ) = 1 and C _U (Z _Q-1 ) = 1.

The interpolated cumulative density function c _L (X _k ), c _U (X _k ) is calculated approximately from the quantized cumulative density function C _L (Z _q ), C _U (Z _q ) .

Assuming that Q [X _k ] = Z _q 1 Z _m , Z _-1 = 0 and c _L (X _k ) is linearly interpolated as shown in Equation (5).

&Quot; (5) "

Similarly, assuming that Q [X _k ] = Z _q Z _m , c _U (X _k ) is linearly interpolated as shown in Equation 6 below.

&Quot; (6) "

On the other hand, the biggest problem of the histogram equalization is that the average brightness between the input and output signals can be remarkably changed depending on the accumulated density function value used as the conversion function.

Further, in the present invention, the following mapping operation combining brightness compensation is proposed when the average brightness of a given image is excessively dark or bright.

Based on the interpolated cumulative density function, the improved output (Y _H ) is given by Equation (7) for the input image (X _k ).

&Quot; (7) "

here,

&Quot; (8) "

That is, let B _m be a compensated average level, and? Be a correction value obtained by a predetermined correction function according to the average brightness, the compensated average level B _m is a correction value obtained by multiplying the average level (X _m ) (?). At this time, it is assumed that B _m ⊂ {X ₀ , X ₁ , ..., X _L-1 }.

And,

&Quot; (9) "

to be. B _m 'represents the first gray level mapped in the level region above the compensated average level (B _m ).

In conclusion, than Equation (7) is if the samples are equal to or less than the quantized mean level (Z _m) of the input image is (0, B _m) in which the results, and the samples are the mean-level quantization of the input image (Z _m) are mapped to (B _m ', X _L-1 ), respectively.

Thus, the correction value is an average brightness of greater than 0 (△ 0), improved output (Y _H) will become bright, the correction value with an average brightness is less than 0 (△ 0), improved output (Y _H) is dark, It will lose. As Δ increases, the dynamic range of the lower level region will be improved, and as Δ decreases, the dynamic range of the upper level region will be improved. A quantized mean-separated histogram equalization using an average level (B _m ) appropriately compensated according to an average level (X _m ) of a given image, i.e., bright and dark, can greatly improve the quality of the input image.

Here, the present invention refers to a quantized mean-separated histogram equalization in which histogram equalization is performed independently for each sub-image obtained by dividing a predetermined number of quantized sub-images according to an average level of an input image and quantized.

Next, an embodiment of an image quality improvement circuit using quantized mean-separated histogram equalization having a brightness compensation function according to the present invention will be described with reference to FIGS. 3 to 6. FIG.

FIG. 3 is a block diagram of an image quality improvement circuit using quantized mean-separated histogram equalization having a brightness compensation function according to an embodiment of the present invention.

In Fig. 3, the first quantizer 102 quantizes the input video signal X _k at the L discrete level to the Q discrete level and outputs the quantized video signal Z _q . The frame histogram calculator 104 calculates a gray level distribution of the quantized image signal (Z _q ) in units of one screen. Here, the screen unit may be a field, but it is a frame.

The frame average calculator 106 calculates the average level (X _m ) of the input image on a frame-by-frame basis. The second quantizer 108 quantizes the average level X _m of the input video signal X _k and outputs the quantized average level Z _m .

The dividing unit 110 divides the quantized gray level distribution calculated by the frame histogram calculator 104 into a predetermined number (here, two) of gray level distributions based on the quantized average level Z _m output from the second quantizer 108 each of the probability density function of the segmented by quantization by the quantization sub video _{({Z} L, {Z} } U) sub video _{({Z} L, {Z} } U) (P L (Z q), P U ( Z _q)) having, a quantized probability density function (P _L (Z _q for outputting _{a), P U (Z q)} ) can be calculated by equation 1 and equation 2 above.

Here, all samples in the quantized sub-picture {Z} _L are less than the quantized average level (Z _m ) and all samples in the quantized sub-picture {Z} _U are larger than the quantized average level (Z _m ).

The first CDF calculator 112 calculates a CDF based on the quantized sub-image {Z} _{L based on} the probability density function P _L (Z _q ) of the quantized sub-image {Z} _{L that} is equal to or lower than the quantized average level Z _m from the divider 110 The cumulative density function value C _L (Z _q ) of {Z} _L is calculated using Equation (3) above.

The second CDF calculator 114 quantizes the quantized sub-image {Z} _{U based on} the probability density function P _U (Z _q ) of the quantized sub-image {Z} _U larger than the quantized average level Z _m output from the divider 110 The cumulative density function value C _U (Z _q ) of the sub-image {Z} _U is calculated using Equation (4) above.

The CDF memory 116 stores the cumulative density function values C _L (Z _q ) and C _U (Z) of the quantized sub-images ({Z} _L , {Z} _U ) calculated by the first and second CDF calculators 112 and 114 Z _q ) are updated in units of a picture according to the synchronization signal SYNC and the quantized cumulative density function values C _L (Z _q ) and C _U (Z _q ) stored during the update are stored in the first and second interpolation Are supplied to the units 118 and 120, respectively. Here, the sync signal SYNC becomes a field sync signal if the picture unit is a field, the frame sync signal becomes a frame sync signal, and the CDF memory 116 is used as a buffer.

The first interpolator 118 is the on the basis of the cumulative density function value of the quantized sub-image {Z} _L (C _L (Z _q)) interpolated by linear interpolation by the above equation (5) the cumulative density function values (c _L (X _k ). Here, k = 0, 1, ..., m.

The second interpolator 120 is the on the basis of the cumulative density function value of the quantized sub-image {Z} _U (C _U (Z _q)) interpolated by linear interpolation by the above equation (6) the cumulative density function values (c _U (X _k ). Here, k = m + 1, m + 2, ..., L-1.

The video signal X _k input to the first and second interpolators 118 and 120 is a video signal of the next frame of the video signal X _k input to the first quantizer 102 and the frame averager 106 . However, it is possible to reduce the hardware by omitting the frame memory by using the property of having high correlation between adjacent frames.

The brightness compensator 122 receives the average level X _m output from the frame average calculator 106 and calculates a correction value Δ according to the average brightness of the input image as an average level X _m ) and outputs the compensated average level (B _m ).

This correction value DELTA is determined by the correction function as shown in Figs. 4A and 4B. The present invention is not limited to the example of the correction function shown in Figs. 4A and 4B, and there may be other applications.

The brightness of the improved signal Y _H is adjusted by the correction value according to the correction function as shown in FIGS. 4A and 4B. In other words. If the average level X _m of the input image is very small, that is, if it is a very dark image, a correction value DELTA greater than 0 is added to the average level X _m , The resulting average-separated histogram equalization brightens the average brightness of the improved signal (Y _H ).

If the average level X _m of the input image is very large, that is, if it is a very bright image, a correction value? Smaller than 0 is added to the average level X _m , The quantized mean-divergent histogram equalization darkens the average brightness of the improved signal (Y _H ). Accordingly, the quantization of the average-separated histogram using the average level (B _m ) compensated by the predetermined appropriate correction value (?) According to the average level (X _m ) can greatly improve the quality of the input image.

5A and 5B are diagrams showing the relationship between the compensated average level B _{m obtained} by adding the correction value Δ according to the brightness correction function shown in FIGS. 4A and 4B and the average level X _m of the input image .

The first mapper 124 receives the quantized average level Z _m (X _k ) by inputting the interpolated cumulative density function value c _L (X _k ), the input video signal X _k and the compensated average level B _m , ) it is mapped in accordance with the quantized sub-image {Z} _L interpolating the cumulative density function of the sample values (c _L (X _k)) from X ₀ to a gray level of less than or equal to B _m.

The second mapper 126 receives the interpolated cumulative density function value c _U (X _k ), the input image signal X _k and the compensated average level B _m to obtain a quantized average level Z _m Maps samples of the large quantized sub-image {Z} _U to gray levels from B _m 'to X _L-1 according to the interpolated cumulative density function value c _U (X _k ).

The output mapped by the first and second mapper 124 and 126 is expressed by Equation (7), and B _m 'is represented by Equation (9).

The comparator 128 compares the input video signal X _k with the quantized average level Z _m to determine whether the input video signal X _k is less than or equal to the quantized average level Z _m , And generates a selection control signal for selecting the second mapper 126 if not.

The selector 130 selects the first mapper 124 according to the selection control signal, that is, when the input image signal X _k is equal to or lower than the quantized average level Z _m , And outputs an improved signal (Y _H ) that can be expressed by Equation (7).

In the present invention, the frame histogram calculator 104 and the first and second CDF calculators 112 and 114 are not used separately, but the sub-image quantized by the first and second CDF calculators 112 and 114 without the frame histogram calculator 104. [ And the CDF can be calculated based on the gray level distribution.

6 is a block diagram according to another embodiment of an image quality improvement circuit using quantized mean-separated histogram equalization having a brightness compensation function according to the present invention.

In Fig. 6, the first quantizer 202 quantizes the input video signal X _k at the L discrete level to the Q discrete level and outputs the quantized video signal Z _q . The frame histogram calculator 204 calculates a gray level distribution on a frame-by-frame basis of the quantized video signal Z _q .

Frame mean calculator 206 calculates the mean level (X _m) of an input video on a frame-by-frame basis. The second quantizer 208 quantizes the average level X _m of the input video signal X _k and outputs the quantized average level Z _m .

Splitter 210 includes a frame histogram calculator 204, a quantized gray level distribution of the second mean level quantized output from the quantizer (208) (Z _m) to the the basis of the two quantized sub-images calculated in the ({ (each of the probability density function (P _L (Z _q of the _{{Z} L, {Z}} U)), P U (Z q)) output _{Z} L, {Z} U} ) divided by the quantized sub-image by And the quantized probability density functions P _L (Z _q ) and P _U (Z _q ) can be calculated by the above equations (1) and (2).

Claim 1 CDF calculator 212 is the probability density function (P _L (Z _q)) of the quantized sub on the basis of the image {Z} cumulative density function value of _L of the sub-image {Z} _L quantization from the divider 210, (C _L (Z _q )) is calculated using the above equation (3).

Claim 2 CDF calculator 214 is the probability density function of the quantized sub-image {Z} _U (P _U (Z _q)) of the sub-image {Z} _U quantized as a basis the cumulative density function value (C _U (Z _q )) is calculated using Equation (4) above.

The CDF memory 216 stores the cumulative density function values C _L (Z _q ), C _U (Z) of the quantized sub-images ({Z} _L , {Z} _U ) calculated by the first and second CDF calculators 212, Z _q ) are updated frame by frame according to the frame synchronization signal SYNC and the quantized cumulative density function values C _L (Z _q ) and C _U (Z _q ) And is supplied to the interpolators 218 and 220.

The frame memory 200 delays the input video signal X _k by one frame.

Here, since the quantized cumulative density function values C _L (Z _q ) and C _U (Z _q ) are cumulative density function values of a video signal delayed by one frame compared with the currently input video signal X _k , The input video signal X _k to input the video signal of the same frame as the cumulative density function values C _L (Z _q ) and C _U (Z _q ) to the first and second interpolators 218 and 220, The memory 200 delays one frame.

The first interpolator 218 is the basis of the cumulative density function value of the quantized sub-image {Z} _L (C _U (Z _q)) interpolated by linear interpolation by the above formula (5), the cumulative density function values (c _L (X _k ). Here, k = 0, 1, ..., m.

The second interpolator 220 of the linear interpolation by the following formula 6 for interpolation on the basis of the cumulative density function value of the quantized sub-image {Z} _U (C _U (Z _q)), the cumulative density function value (c _U (X _k ). Here, k = m + 1, m + 2, ..., L-1.

The brightness compensator 222 receives the average level X _m output from the frame average calculator 206 and adds the correction value according to the average brightness of the input image to the average level X _m as shown in Equation 8 And outputs the compensated average level (B _m ).

The first mapper 224 receives the interpolated cumulative density function value c _L (X _k ) output from the first interpolator 218 and the image signal X _k output from the frame memory 200 and the brightness compensator 222) according to the mean level (B _m) of the average level quantization type (Z _m) or less sub-image {Z} the cumulative density function value interpolation of samples _L (c _L (X _k)) compensation from X ₀ It is mapped in a gray level of from B _m.

The second mapper 226 compares the interpolated cumulative density function value c _U (X _k ) output from the second interpolator 220 with the image signal X _k output from the frame memory 200 and the brightness compensator compensated mean level (B _m), the input to the quantized mean level (Z _m) than interpolating the large sub video samples of the {Z} _U cumulative density function value (c _U (X _k)) to the output from 222.) And maps to the gray level from B _m 'to X _L-1 .

The output mapped by the first and second mapper 224 and 226 is expressed by Equation (7), and B _m 'is expressed by Equation (9).

The comparator 228 compares the delayed video signal X _k output from the frame memory 200 with the quantized average level Z _m and outputs the quantized average of the video signal X _k output from the frame memory 200 And generates a selection control signal for selecting the first mapper 224 if it is less than or equal to the level Z _m and selecting the second mapper 226 otherwise.

The selector 230 selects the first mapper 224 according to the selection control signal, that is, when the video signal X _k output from the frame memory 200 is equal to or lower than the quantized average level Z _m , 2 mapper 226 and outputs an improved signal Y _H that can be represented by Equation 7 above.

INDUSTRIAL APPLICABILITY The present invention can be applied to a wide variety of fields related to image quality improvement of a video signal. That is, it can be applied to broadcasting equipment, radar signal processing system, medical engineering, and household appliances.

The method of the present invention using the quantized average-separated histogram equalization in consideration of the correction value according to the average brightness of the input image effectively reduces the sudden brightness change and the artifact generated in the conventional histogram equalization to improve the contrast, There is an effect to maintain. In addition, the method of the present invention improves the image quality by improving the contrast of an overly dark or bright input video signal.

In addition, the circuit of the present invention quantizes the input image signal and independently histograms the sub-images divided by a predetermined number to store and accumulate only the number of times the quantized levels are generated for CDF calculation, thereby simplifying the hardware and reducing the cost It is effective.

Claims (21)

A method for improving image quality by histogram equalizing a video signal represented by a predetermined number (L) of gray levels, comprising: (a) quantizing an input video signal and outputting a quantized video signal; (b) obtaining an average of the inputted video signals on a screen basis and quantizing them to output a quantized average level; (c) dividing the quantized image signal into a predetermined number of quantized sub-images according to the quantized average level; (d) obtaining cumulative density functions of the predetermined number of quantized sub-images; (e) outputting a cumulative density function value interpolated for each sub-image by interpolation based on a cumulative density function obtained for each quantized sub-image; (f) outputting a compensated average level by adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level; And (g) independently histogram equalizing each quantized sub-image based on the cumulative density function value interpolated for each sub-image and the compensated average level. The method of claim 1, wherein the quantizing step divides the quantized image signal into two sub-images according to the quantized average level. The method of claim 1, wherein the interpolation in step (e) is linear interpolation. The method of claim 1, wherein in step (f), if the average level is very small, that is, in case of a very dark image, a correction value greater than zero is added to the average level to output a compensated average level, That is, in the case of a very bright image, a correction value smaller than zero is added to the average level to output a compensated average level. The method of claim 1, wherein step (g) (g1) to the mean level (B _m) compensating for at least the gray level (X ₀₎ in accordance with the cumulative density function value interpolation corresponding to the video signal is an image signal to be input is the quantized mean level below input thereto gray Level; And (g2) mapping from B _m 'in accordance with the cumulative density function value interpolation corresponding to the video signal that is larger input than the input video signal the quantized mean level thereto as a gray-level to the maximum gray level (X _L-1) But here Wherein the step (c) comprises the step of (d). 6. The method of claim 5, further comprising: (g3) inputting the delayed video signal by delaying the input video signal by a unit of the screen in steps (g1) and (g2). A method for improving image quality by histogram equalizing a video signal represented by a predetermined number (L) of gray levels, comprising: (a) quantizing an input video signal and outputting a quantized video signal; (b) obtaining a gray level distribution of the quantized video signal on a screen basis; (c) outputting a quantized average level by quantizing the input video signal by averaging the input video signal in units of a screen; (d) dividing the gray level distribution obtained in the step (b) into a predetermined number of quantized sub-images according to the quantized average level; (e) obtaining a quantized cumulative density function based on the gray level distribution of the predetermined number of quantized subimages; (f) outputting a cumulative density function value interpolated for each sub-image by interpolation based on a cumulative density function obtained for each quantized sub-image; (g) outputting a compensated average level by adding a correction value according to a predetermined correction function based on an average brightness of an inputted video signal to the average level; And (h) outputting an improved signal by mapping the subpixel to a new gray level independently for each subimage based on the accumulated density function value interpolated for each subpixel and the compensated average level, Way. The method of claim 7, wherein in step (d), the gray level distribution obtained in step (b) is divided into two quantized sub-images according to the quantized average level. 8. The method of claim 7, wherein the interpolation in step (f) is linear interpolation. The method of claim 7, wherein, in step (g), if the average level is very small, i.e., in case of a very dark image, a correction value greater than zero is added to the average level to output a compensated average level, That is, in case of a very bright image, a correction value smaller than zero is added to the average level to output a compensated average level, And the brightness of the improved signal is adjusted according to the compensated average level. 8. The method of claim 7, wherein step (h) (h1) of up to a mean level (B _m) compensating for at least the gray level (X ₀₎ in accordance with the cumulative density function value interpolation corresponding to the video signal is an image signal to be input is the quantized mean level below input thereto gray Level; And (h2) mapping from B _m 'in accordance with the cumulative density function value interpolation corresponding to the video signal that is larger input than the input video signal the quantized mean level thereto as a gray-level to the maximum gray level (X _L-1) But here The image quality improvement method comprising: 12. The method of claim 11, further comprising: (h3) inputting a delayed video signal by delaying the input video signal by a unit of a picture in steps of (h1) and (h2). A circuit for enhancing image quality by histogram equalizing a video signal represented by a predetermined number (L) of gray levels, comprising: A first quantization means for quantizing an input video signal and outputting a quantized video signal; First calculation means for calculating a gray level distribution of the quantized video signal on a screen basis; Second calculation means for calculating an average level of an input video signal on a screen basis; Second quantization means for quantizing the calculated average level and outputting a quantized average level; A brightness compensation means for adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level to output a compensated average level; Division means for dividing the gray level distribution calculated by the first calculation means into a predetermined number of quantized sub-images according to the quantized average level; Third calculation means for obtaining an accumulated density function for each quantized sub-image; Interpolating means for outputting a cumulative density function value interpolated for each sub-image by interpolation based on the cumulative density function calculated for each of the quantized sub-images; A brightness compensation means for adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level to output a compensated average level; And And an output unit for outputting an improved signal by mapping the quantized sub-image to a new gray level according to the interpolated cumulative density function value and the compensated average level corresponding to the quantized sub-image. The image processing apparatus according to claim 13, further comprising: a screen memory for delaying the input video signal in units of a screen in order to input a video signal having the same screen as the quantized cumulative density function value calculated for each sub- Further comprising an image quality enhancement circuit. The image processing apparatus according to claim 13, further comprising: a buffer for updating the quantized cumulative density function value calculated for each sub-image in the third calculation unit on a screen by picture basis and supplying the quantized cumulative density function value stored in advance to the interpolation means, Wherein the picture quality improvement circuit comprises: 14. The picture quality improvement circuit according to claim 13, wherein the picture unit is a frame and the predetermined number is 2. 14. The picture quality improvement circuit according to claim 13, wherein the interpolation is linear interpolation. 14. The apparatus of claim 13, wherein the brightness compensating means outputs a compensated average level by adding a correction value larger than zero to the average level when the average level is very small, that is, when the average level is very dark, And outputs a compensated average level by adding a correction value smaller than zero to the average level in the case of a very bright image. 14. The apparatus of claim 13, wherein the output means If the input video signal is below the quantized average level, the input video signal is mapped to the gray level from the minimum gray level (X ₀ ) to the compensated average level (B _m ) according to the interpolated cumulative density function value corresponding thereto A first mapper; If the input video signal is greater than the quantized average level, the input video signal is mapped to the gray level from B _m 'to the maximum gray level (X _L-1 ) according to the interpolated cumulative density function value corresponding thereto A second mapper; A comparator for comparing the input video signal with the quantized average level to output a selection control signal; And And a selector for selecting the first mapper if the input video signal is equal to or lower than the quantized average level according to the selection control signal, and selecting the second mapper if not. 15. The apparatus of claim 14, wherein the output means If the delayed video signal output from the screen memory is below the quantized average level, the delayed video signal is shifted from the minimum gray level (X ₀ ) to the compensated average level (B _m ) according to the interpolated cumulative density function value corresponding thereto To a gray level of the first mapper; If the delayed video signal is greater than the quantized average level, the delayed video signal is mapped to a gray level from B _m 'to the maximum gray level (X _L-1 ) according to the interpolated cumulative density function value corresponding thereto A second mapper; A comparator for comparing the delayed video signal with the quantized average level to output a selection control signal; And And a selector for selecting the first mapper if the delayed video signal is equal to or lower than the quantized average level according to the selection control signal, and selecting the second mapper otherwise. A circuit for enhancing image quality by histogram equalizing a video signal represented by a predetermined number (L) of gray levels, comprising: A first quantization means for quantizing an input video signal and outputting a quantized video signal; First calculation means for calculating an average level of an input video signal on a screen basis; Second quantization means for quantizing the calculated average level and outputting a quantized average level; A brightness compensation means for adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level to output a compensated average level; Dividing means for dividing the quantized image signal into a predetermined number of quantized sub-images according to the quantized average level; Second calculation means for calculating an accumulated density function for each quantized sub-image based on a gray-level distribution calculated by calculating a gray-level distribution for each quantized sub-image; Interpolating means for outputting a cumulative density function value interpolated for each sub-image by interpolation based on the cumulative density function calculated for each of the quantized sub-images; A brightness compensation means for adding a correction value according to a predetermined correction function based on an average brightness of an input video signal to the average level to output a compensated average level; And And an output unit for outputting an improved signal by mapping the quantized sub-image to a new gray level according to the interpolated cumulative density function value and the compensated average level corresponding to the quantized sub-image.