KR100224885B1 - Image quality enhancement method and circuit thereof based on the quantized mean-maching histogram equalization having gain control function - Google Patents

Abstract

The image quality improvement method and circuit according to the present invention quantizes the level of an input video signal and obtains a cumulative density function based on a gray level distribution of a screen unit for a quantized video signal and obtains a quantized cumulative density function value A cumulative density function value interpolated by interpolation is calculated, an average level of the input video signal is calculated on a screen basis, an input cumulative density function is used as a transform function to map the input video signal to a gray level Adjusting the conversion function so that the average level is mapped to itself, outputting the improved signal, and adjusting the gray level change amount of the input video signal and the improved signal according to the level of the input video signal, It is possible to maintain the average brightness of the input image constant while improving the contrast by being mapped to the user, By preventing artifacts in accordance with the improved to improve the image quality.

Description

[0001] The present invention relates to an image quality enhancement method and a circuit thereof, and more particularly, to an image quality enhancement method and a circuit thereof using a quantized mean-matching histogram equalization with a gain control function,

The present invention relates to a method and a circuit for improving image quality using quantized mean-matching histogram equalization with a gain control function, and more particularly to a method and apparatus for improving artifacts by improving the contrast while maintaining the average brightness of a given image constant And an image quality improving method and circuit therefor.

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 appear to be too bright after histogram equalization.

In addition, the problem that can be caused by improving the contrast based on the histogram equalization for a given image is that the difference between input and output can be large. In other words, the contrast may be excessively improved by the histogram equalization based on an algorithm that depends on the histogram of the input image, which has a problem in that an undesired image is provided.

In addition, the conventional histogram equalization circuit has a problem that hardware cost is increased because it requires a configuration capable of storing all occurrences of all gray levels. 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.

It is an object of the present invention to adjust the conversion function so that the average level of the input image is mapped to itself when the histogram equalization is performed by using the cumulative density function interpolated by the interpolation as the quantized cumulative density function of the input image as the transform function, And improving the image quality by adjusting the amount of improvement adaptively according to the level of the input video signal.

It is another object of the present invention to provide a method and apparatus for converting a quantized cumulative density function of an input image into a cumulative density function interpolated by interpolation as a transform function so that an average level of the input image is mapped to itself when the histogram is equalized And to improve the picture quality by adjusting the amount of improvement adaptively according to the level of the input video signal while improving the contrast by adjusting the function.

According to an aspect of the present invention, there is provided a method for improving image quality by histogram equalizing an image signal expressed by a predetermined number of gray levels, the method comprising the steps of: (a) Outputting a quantized video signal; (b) obtaining a cumulative density function based on a gray-level distribution diagram of each picture unit for the quantized video signal and outputting a quantized cumulative density function value; (c) outputting the cumulative density function value interpolated by the interpolation based on the quantized cumulative density function value; (d) calculating an average level of an input video signal on a screen basis; (e) mapping the input video signal to a gray level using the interpolated cumulative density function as a transform function, and adjusting the transform function so that the average level obtained in step (d) is mapped to itself, Outputting; And (f) adjusting a gray level change amount of the input video signal and the improved signal according to a level of the input video signal.

According to another aspect of the present invention, there is provided an image quality improvement circuit for enhancing an image quality by histogram equalizing an image signal represented by a predetermined number of gray levels, the circuit comprising: Quantization means for outputting a video signal; First calculation means for calculating a cumulative density function based on a gray level distribution of a screen unit for the quantized video signal and outputting a quantized cumulative density function value; Second calculation means for calculating an average level of an input video signal on a screen basis; Interpolating means for interpolating the quantized cumulative density function value and outputting an interpolated cumulative density function value; Using the interpolated cumulative density function as a transform function to map an input video signal to a gray level and adjusting the transform function such that the average level obtained by the second calculation means is mapped to itself, Output means; And gain control means for controlling a gain of the improved signal according to a change amount of a gray level between the input video signal and the improved signal and a level of the input video signal.

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 enhancement circuit using quantized mean-matched histogram equalization with a gain control function according to an embodiment of the present invention.

4 is a block diagram of an image quality improvement method using quantized mean-matching histogram equalization with a gain adjustment function according to the present invention.

First, an image quality improvement method using a quantized mean-matching histogram equalization with a gain control function proposed by the present invention will be described.

First, a quantized mean-matching histogram equalization algorithm will be described.

{X} denotes a given image, and Xm denotes an average level of a given image {X}.

The given image X consists of L discrete gray levels {X0, X1, ..., XL-1}, where X0 = 0 represents the black level and XL-1 = 1 represents the white level . Also, Xm ∈ {X0, X1, ..., XL-1}.

Quantizing the original discrete input levels {X0, X1, ..., XL-1} to a Q discrete level defined by {Z0, Z1, ..., ZQ-1}, where ZQ- 1, and Q ?? L, and {Z0, Z1, ..., ZQ-1}. {X0, X1, ..., XL-1}.

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

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

Q [Xk] = Zq, if Zq-1XK Zq

When {Z} = Q [{X}], {Z} represents a quantized input image.

The probability density function (PDF) of the quantized input image {Z} can be expressed by Equation (1) below.

Here, P (Zq) is the probability of the q-th quantized gray level (Zq) in the quantized image {Z}, Nq is the number of times the level (Zq) appears in the quantized image {Z}, N is the quantized Represents the total number of samples of the image {Z}.

Then, the cumulative density function (CDF) of the quantized image {Z} is defined by the following equation (2).

Here, C (ZQ-1) = 1.

The cumulative density function c (Xk) of the samples before being quantized can be approximately calculated through linear interpolation from the cumulative density function C (Zq) of the quantized samples as shown in Fig.

When Q [Xk] = Zq, assuming that Z-1 = 0, c (Xk) is linearly interpolated as shown in Equation 3 below.

From the above equation (3), c (Xm) can also be approximated.

The major problem with histogram equalization is that the average brightness between input and output signals can vary significantly depending on the cumulative density function used as the transform function.

In order to solve such a problem, the present invention proposes a next mapping operation based on the average of the input image combined with the cumulative density function obtained through the linear interpolation.

This is because the input sample with an average level (Xm) To an Xm to Xm gray level, and an input sample larger than the average level (Xm) Lt; / RTI > to < RTI ID = 0.0 > XL-1 < / RTI > Xm is again mapped to Xm in Equation (4).

Therefore, when a given image is histogram equalized according to the interpolated cumulative density function computed from the quantized cumulative density function, the average level of a given image is transformed to a transform function based on the interpolated cumulative density function Is adjusted as shown in Equation (4) so that the average brightness of a given image is not changed by the histogram equalization in the present invention is referred to as quantized mean-matching histogram equalization.

The following describes an algorithm for adjusting the gain of an improved signal by quantized mean-matching histogram equalization.

The basic concept of the gain control is to appropriately limit the change of the maximum gray level of the input video signal Xk according to the level of the input video signal when the contrast is improved by using the quantized average-matching histogram equalization.

First, the relationship between the input video signal Xk and the improved signal Y can be expressed by Equation (5) or (6) below.

or,

Here,? K is the level of the input image signal Xk, which is the amount of change (improvement amount) produced by the quantized mean-matched histogram equalization, ie, the level mapped to the new gray level by the quantized mean- ).

In order to prevent excessive improvement due to histogram equalization, the amount of change? K is limited as follows in the present invention.

Here, g (Xk) is defined as a maximum bounding function, and g (Xk) is a function of the input video signal Xk and is always positive, that is, g (Xk) 0, ( 0) is a gain control parameter.

Equation (7) can be expressed as Equation (8) as Equation (8).

The concept of limiting the amount of change (? K) shown in Equation (7) above is related to the Weber's ratio. In fact, if g (Xk) = Xk, the following Equation 9 can be obtained from Equation (7).

here, Is the amount corresponding to the ratio of Webber. The ratio of this webber is such that X1 X1, and X2 is changed by It is an experimental fact that means that when human is changed by X2, the degree of change is the same.

Therefore, the gain control concept applied to the present invention is to control the gain of the improved signal, i.e., the amount of improvement, using the quantized average-matching histogram based on the ratio of the Weber.

? K 'is defined as a limited change amount, and can be expressed by the following Equation (10).

That is, when the absolute value of the change amount? If g (Xk) or less, the amount of change? K is used as the limited amount of change? K ', and the amount of change? If g (Xk) is greater than · G (Xk), and the amount of change (k) If g (Xk) is less than - - g (Xk) to control the gain of the improved signal (Y).

Therefore, the final output signal YOUT of the present invention can be expressed by the following Equation (11).

Next, an embodiment of an image quality improvement circuit using quantized mean-matching histogram equalization with a gain control function according to the present invention will be described with reference to FIGS. 3 and 4. FIG.

FIG. 3 is a block diagram of an image quality enhancement circuit using quantized mean-matched histogram equalization with a gain control function according to an embodiment of the present invention.

3, the quantizer 102 quantizes the input image (Xk's) at the L level to the Q level and outputs the quantized image (Zq's). The frame histogram calculator 104 calculates a gray-level distribution diagram for each quantized image (Zq's) in units of one screen, and calculates a probability density function (P (Zq) 's) using Equation (1). Here, the screen unit may be a field, but here it is a frame.

The CDF calculator 106 calculates the cumulative density function (() () using the equation 2 based on the probability density function P (Zq) 's of the quantized image Zq's calculated in the frame histogram calculator 104 The CDF interpolator 108 linearly interpolates by the equation (3) based on the cumulative density function value C (Zq) 's of the quantized image (Zq's) (X (k)) 's, where k = 0, 1, ..., L-1.

On the other hand, the frame average calculator 110 calculates the average level Xm of the input image Xk's in units of frames and calculates the average level Xm calculated in accordance with the synchronizing signal (here, the frame synchronizing signal SYNC) 112), and outputs it to the first and second mapper (114, 116).

The CDF memory 112 updates the cumulative density function c (Xk) 's interpolated by the CDF interpolator 108 on a frame-by-frame basis in accordance with the synchronization signal SYNC and stores the interpolated cumulative density function value (c (Xm)) for the average level (Xm) output from the frame average calculator 110 and the average level (Xm) output from the frame average calculator 110. [ Here, the CDF memory 112 is used as a buffer, and k = 0, 1, ..., L-1.

The first mapper 114 receives the interpolated cumulative density function value c (Xk) output from the CDF memory 112 and the cumulative density function value c (Xm) for the mean level from the frame average calculator 110 The input video signal Xk which is the average level Xm and the input video signal Xk and outputs the input video signal Xk and the input video signal Xk to the gray level of X0 to Xm do.

The second mapper 116 stores the interpolated cumulative density function value c (Xk) output from the CDF memory 112 and the cumulative density function value c (Xm) for the average level from the frame averager 110 The input video signal Xk that is larger than the average level Xm by inputting the average level Xm and the input video signal Xk is converted into one of the gray levels Xm + 1 to XL-1 using Equation (4) ≪ / RTI >

The video signal Xk input to the first and second mapper 114 and 116 is the video signal of the next frame in comparison with the interpolated cumulative density function value c (Xk) output from the CDF memory 112. (Xk) input to input the video signal of the same frame as the interpolated cumulative density function value c (Xk) to the first and second mappers 114 and 116 can be delayed by one frame by the frame memory have.

However, in FIG. 1, the hardware is reduced by omitting the frame memory using the property of having high correlation between adjacent frames.

The first selector 118 compares the input video signal Xk with the average level Xm output from the frame averager 110 and outputs the result of comparison to the first mapper 114 , Otherwise selects the second mapper 116 and outputs an improved signal YH as shown in equation (4).

Here, the gray histogram calculator 104 and the CDF calculator 106 are not used separately, and the gray level distribution diagram for the quantized image (Zq's) is calculated in units of one screen, and the CDF As shown in FIG.

The frame histogram calculator 102 to the first selector 118 are referred to as a quantized mean-matching histogram equalizer 100.

The subtractor 202 of the gain controller 200 subtracts the input image signal Xk from the improved signal Y output from the first selector 118 and outputs the subtracted input image signal Xk to the quantized average matching histogram equalizer 100 (? K) is calculated by the following equation.

The gain characteristic determiner 204 limits the improvement of the input image signal Xk by using the maximum limit function g (Xk), which is a function of the input image signal Xk.

For example, when g (Xk) = K, and K is a constant, it limits the input improvement by the same amount regardless of the input gray value, and the maximum limit function is g (X_k) = aX_k Constant) or g (X_k) = a root {X_k}, where a is a constant, which limits the amount of enhancement of the input image differently depending on the input gray-level value.

The second selector 206 compares the input video signal Xk with the average level Xm output from the frame average calculator 106 and inputs the video signal Xk input from the outside if the input video signal Xk is below the average level Xm. The first gain control parameter ( L) is selected, and if not, the second gain control parameter ( U). In FIG. 1, a gain control parameter for a video signal of an average level or lower L) and gain control parameters for image signals larger than the average level ( u) are set separately.

The multiplier 208 multiplies the maximum limit function g (Xk) value output from the gain characteristic determiner 204 and the gain control parameter selected by the second selector 206 ) To multiply the threshold value ( G (Xk)). Here, G (Xk) is a characteristic of the gain controller 200 of the present invention.

The limiter 210 outputs the variation amount? K output from the subtracter 202 to a limit value (? K) output from the multiplier 208 (Gk (Xk)) to limit the amount of change? K and output the limited amount of change? K 'as in Equation 10 above.

The adder 212 adds the input video signal Xk and the limited variation amount Δk 'output from the limiter 210 to the output signal Yout of the gain controller 200 as shown in Equation (11) Output.

4 is a block diagram of another embodiment of an image quality enhancement circuit using quantized mean-matched histogram equalization with a gain control function according to the present invention.

4, the quantizer 302 of the quantized mean-matching histogram equalizer 300 quantizes the input image (Xk's) at the L level to the Q level and outputs a quantized image (Zq's).

The frame histogram calculator 304 calculates a gray-level distribution diagram for each quantized image (Zq's) on a frame-by-frame basis and calculates a probability density function P (Zq) 's of the quantized image (Zq's) do.

The CDF calculator 306 calculates the cumulative density function (() of the quantized image (Zq's) quantized using Equation 2 based on the probability density function P (Zq) 's of the quantized image (Zq's) calculated by the frame histogram calculator 304 C (Zq) 's).

The CDF interpolator 308 calculates the cumulative density function value c (Xk) 's (x) by linearly interpolating according to Equation (3) based on the cumulative density function C (Zq)' s of the quantized image ). Here, k = 0, 1, ..., L-1.

On the other hand, the frame average calculator 310 calculates the average level Xm of the input image Xk's in units of frames and outputs the average level Xm calculated in accordance with the frame synchronizing signal SYNC to the CDF memory 314, 1 and the second mapper 316, 318, respectively.

The frame memory 312 stores the input image Xk's in units of one frame. The CDF memory 314 updates the cumulative density function value c (Xk) 's interpolated by the CDF interpolator 308 on a frame-by-frame basis in accordance with the frame sync signal SYNC, and stores the interpolated cumulative density And outputs the cumulative density function value c (Xm) for the average level Xm output from the frame average calculator 310. [ Here, k = 0, 1, ..., L-1.

The first mapper 316 receives the interpolated cumulative density function value c (Xk) output from the CDF memory 314 and the cumulative density function value c (Xm) for the average level from the frame average calculator 310 A delayed input video signal Xk which is equal to or lower than the average level Xm by using Equation 4 is inputted from X0 to Xm (Xm) by inputting the average level Xm outputted from the frame memory 312 and the video signal Xk delayed by one frame outputted from the frame memory 312, Lt; / RTI > to one of the gray levels up to < RTI ID = 0.0 >

The second mapper 318 receives the cumulative density function value c (Xk) output from the CDF memory 314 and the cumulative density function value c (Xm) for the average level from the frame average calculator 310 A delayed input image signal Xk which is larger than the average level Xm is input to the input image signal Xk delayed by one frame outputted from the average level Xm outputted from the frame memory 312 and Xm Maps to one of the gray levels from +1 to XL-1.

The selector 320 compares the image signal Xk output from the frame memory 312 with the average level Xm output from the frame average calculator 310 and outputs the image signal Xk output from the frame memory 312 If it is equal to or lower than the average level Xm, the first mapper 316 is selected. Otherwise, the second mapper 318 is selected and the improved video signal Y is output.

The subtractor 402 of the gain controller 400 subtracts the input image signal Xk from the improved signal Y output from the selector 320 and outputs the variation amount ? K).

The gain characteristic determiner 404 limits the improvement of the input video signal Xk by using the maximum limit function g (Xk), which is a function of the input video signal Xk.

The multiplier 406 multiplies the maximum limit function g (Xk) value output from the gain characteristic determiner 404 and the gain control parameter ) To multiply the threshold value ( G (Xk)).

Gain control parameter ( ) May be different gain control parameters depending on when each input sample is greater than and smaller than the average level, as shown in FIG. 1, but here the same value is given for the input video signal.

The limiter 408 outputs the variation amount? K output from the subtracter 402 to a limit value (? K) output from the multiplier 406 (Gk (Xk)) to limit the amount of change? K and output the limited amount of change? K 'as in Equation 10 above.

The adder 410 adds the input video signal Xk and the limited variation amount Δk 'output from the limiter 408 to the output signal Yout of the gain controller 400 as shown in Equation (11) Output.

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, household appliances, and the like.

As described above, the present invention is used as a transform function so that the average gray level of a given image is mapped to itself when the histogram equalization is performed according to the cumulative density function approximated through linear interpolation from the quantized cumulative density function of a given image signal By adjusting the interpolated cumulative density function to improve the contrast, the effect of maintaining the average brightness of a given image constant and adjusting the amount of improvement based on the ratio of Webber to prevent artifacts due to excessive improvement, have.

In addition, the circuit of the present invention has the effect of simplifying the hardware and reducing the cost by storing and accumulating the number of occurrences of the quantized levels for quantizing the input image signal and performing histogram equalization.

Claims (37)

A method for enhancing image quality by histogram equalizing a video signal represented by a predetermined number of gray levels, comprising: (a) quantizing a level of an inputted video signal and outputting a quantized video signal; (b) obtaining a cumulative density function based on a gray-level distribution diagram of each picture unit for the quantized video signal and outputting a quantized cumulative density function value; (c) outputting the cumulative density function value interpolated by the interpolation based on the quantized cumulative density function value; (d) calculating an average level of an input video signal on a screen basis; (e) mapping the input video signal to a gray level using the interpolated cumulative density function as a transform function, and adjusting the transform function so that the average level obtained in step (d) is mapped to itself, Outputting; And (f) adjusting an amount of gray level change between the input image signal and the improved signal according to a level of the input image signal. 2. The method of claim 1, further comprising: (e1) outputting the delayed video signal to the step (e) by delaying the inputted video signal by a screen unit. The method of claim 1, wherein the interpolation in step (c) is linear interpolation. 2. The method of claim 1, wherein the adjustment of the gain of the improved signal in step (f) is based on a ratio of Weber. 2. The method of claim 1, wherein step (f) (f1) subtracting an input image signal from the improved signal to detect a change amount corresponding to the difference; (f2) calculating a limit improvement amount of the input image signal by a predetermined maximum limit function and a predetermined gain control parameter; (f3) comparing the limit improvement amount and the variation amount, limiting the variation amount according to a comparison result, and outputting a limited variation amount; And (f4) adding the limited change amount to the input image signal. The image quality improving method according to claim 5, wherein the predetermined gain control parameter is a gain control parameter set according to a level of an input video signal. The image processing apparatus according to claim 5, wherein the predetermined gain control parameter is a first gain control parameter for an input image signal of an average level or lower and a second gain control parameter for an input image signal larger than an average level, How to improve. 6. The method of claim 5, wherein the predetermined gain control parameter is one gain control parameter applied to the input image signal in the same manner. 6. The image quality improvement method according to claim 5, wherein the maximum limit function g (Xk) is g (X_k) = aX_k, and a is a constant. 6. The image quality improvement method according to claim 5, wherein the maximum limit function g (Xk) is g (X_k) = a root {X_k}, and a is a constant. A method for enhancing image quality by histogram equalizing a video signal represented by a predetermined number of gray levels, comprising: (a) quantizing a level of an inputted video signal and outputting a quantized video signal; (b) obtaining a gray level distribution diagram of the quantized video signal on a screen basis; (c) obtaining a cumulative density function based on the obtained gray level distribution of the quantized image signal; (d) outputting a cumulative density function value interpolated by interpolation based on the quantized cumulative density function and an accumulated density function value for the average level; (e) calculating an average level of an input video signal on a screen basis; (f) mapping an input video signal to a gray level according to an accumulated cumulative density function value corresponding to the input cumulative density function value and an average level, and mapping the average level obtained in the step (e) Outputting a signal; (g) subtracting the input image signal from the improved signal to obtain a change amount corresponding to the difference; (h) calculating a limit improvement amount of the input image signal by adding a predetermined gain to the input image signal; (i) comparing the limit improvement amount and the variation amount, and outputting a limited variation according to a comparison result; And (j) adjusting the gain of the improved signal by adding the limited change amount to the input video signal. 12. The method of claim 11, further comprising: (f1) outputting the delayed video signal to the step (f) by delaying the input video signal by the unit of the screen. The method of claim 11, wherein the interpolation in step (c) is linear interpolation. 12. The method of claim 11, wherein in step (h), improvement of the input image signal is limited by a predetermined maximum limit function. 12. The method of claim 11, wherein step (h) (h1) limiting the improvement of the input video signal by a predetermined maximum limit function to output a limited video signal; And (h2) multiplying the limited video signal by a predetermined gain control parameter to output a limit improvement amount. 16. The method of claim 15, wherein the predetermined gain control parameter is a gain control parameter set according to a level of an input video signal. The image display apparatus according to claim 15, wherein the predetermined gain control parameter is a first gain control parameter for an input image signal of an average level or lower and a second gain control parameter for an input image signal larger than an average level, How to improve. 16. The method of claim 15, wherein the predetermined gain control parameter is one gain control parameter applied to the input image signal in the same manner. 16. The image quality improvement method according to claim 15, wherein the maximum limit function g (Xk) is g (X_k) = aX_k, and a is a constant. 16. The method of claim 15, wherein the maximum limit function g (Xk) is g (X_k) = a root {X_k}, and a is a constant. 12. The method according to claim 11, wherein, in the step (i), when the absolute value of the change amount is equal to or smaller than the limit improvement amount, the variation amount is output as the limited variation amount, . A circuit for enhancing image quality by histogram equalizing a video signal represented by a predetermined number of gray levels, the circuit comprising: Quantization means for quantizing the level of an input video signal and outputting a quantized video signal; First calculation means for calculating a cumulative density function based on a gray level distribution of a screen unit for the quantized video signal and outputting a quantized cumulative density function value; Second calculation means for calculating an average level of an input video signal on a screen basis; Interpolating means for interpolating the quantized cumulative density function value and outputting an interpolated cumulative density function value; Using the interpolated cumulative density function as a transform function to map an input video signal to a gray level and adjusting the transform function such that the average level obtained by the second calculation means is mapped to itself, Output means; And And gain control means for controlling a gain of the improved signal according to a change amount of a gray level between the input video signal and the improved signal and a level of the input video signal. 23. The apparatus of claim 22, wherein the first calculation means A frame histogram calculator for obtaining a gray level distribution diagram of the quantized video signal on a screen basis; And And a CDF calculator for calculating a cumulative density function based on the obtained gray level distribution of the quantized image signal and outputting a quantized cumulative density function value. 23. The picture quality improvement circuit according to claim 22, wherein the interpolation is linear interpolation. 23. The apparatus of claim 22, further comprising a buffer for updating the interpolated cumulative density function value on a screen basis and outputting an interpolated cumulative density function value stored during the update and an accumulated cumulative density function value for the mean level, A picture quality improving circuit. The image processing apparatus according to claim 25, further comprising a screen memory for delaying the input video signal in units of a screen so as to input the video signal of the same frame as the interpolated cumulative density function value to the output means Circuit. 26. The apparatus of claim 25, wherein the output means Wherein the average level calculated by the second calculation means is mapped to itself and an input image signal having an average level or lower is compared with an interpolated cumulative density function value corresponding to the average level and a cumulative density function value corresponding to the average level, A first mapper for mapping to a gray level; A second mapper for mapping an input image signal having an average level higher than the average level to a second range of gray levels according to a corresponding cumulative density function value and an accumulated density function value for the average level; And And a selector that selects a first mapper if the input image signal is less than or equal to the average level by comparing the input image signal with the average level, and selects a second mapper if the input image signal is below the average level. 27. The apparatus of claim 26, wherein the output means The average level calculated by the second calculation means is mapped to itself and a video signal of an average level or lower output from the picture memory is multiplied by a cumulative density function value corresponding to the interpolated cumulative density function value, A first mapper for mapping the first range to a gray level; A second mapper for mapping a video signal larger than the average level output from the screen memory to a gray level of a second range according to a corresponding cumulative density function value and an accumulated density function value for the average level; And And a selector for comparing the video signal output from the picture memory with the average level and selecting a first mapper if the video signal output from the picture memory is below the average level, A picture quality improving circuit. 23. The picture quality improvement circuit according to claim 22, wherein the gain control means controls the gain of the improved signal based on the Weber ratio. 23. The apparatus of claim 22, wherein the gain control means A subtractor for subtracting the input image signal from the improved signal to detect a variation corresponding to the difference; A gain characteristic determiner for calculating a maximum limit function value according to a level of the input video signal in order to limit improvement of the input video signal by a predetermined maximum limit function; A selector that compares an input video signal with an average level to select a first gain control parameter if the input video signal is below an average level and otherwise select one of the second gain control parameters; A multiplier for multiplying the maximum limit function value by a gain control parameter selected by the selector and outputting a limit function value; A limiter for limiting the amount of change according to a result of comparison between the limit function value and the change amount and outputting a limited change amount; And And an adder for adding a limited amount of change to the input video signal and outputting a signal whose gain is adjusted by the improved signal. 31. The picture quality improvement circuit according to claim 30, wherein the maximum limit function g (Xk) is g (X_k) = aX_k, and a is a constant. The image quality improvement circuit according to claim 30, wherein the maximum limit function g (Xk) is g (X_k) = a root {X_k}, and a is a constant. The image processing apparatus according to claim 30, wherein the limiter outputs the change amount as the limited change amount when the absolute value of the change amount is equal to or smaller than the limit function value, and outputs the limit function value as the limited change amount otherwise Improvement circuit. 23. The apparatus of claim 22, wherein the gain control means A subtractor for subtracting the input image signal from the improved signal to detect a variation corresponding to the difference; A gain characteristic determiner for calculating a maximum limit function value according to a level of the input video signal in order to limit improvement of the input video signal by a predetermined maximum limit function; A multiplier for multiplying the maximum limit function value by a gain control parameter of a predetermined value to output a limit function value; A limiter for limiting the amount of change according to a result of comparison between the limit function value and the change amount and outputting a limited change amount; And And an adder for adding a limited amount of change to the input video signal and outputting a signal whose gain is adjusted by the improved signal. 35. The picture quality improvement circuit according to claim 34, wherein the maximum limit function g (Xk) is g (X_k) = aX_k, and a is a constant. The image quality improvement circuit according to claim 34, wherein the maximum limit function g (Xk) is g (X_k) = a root {X_k}, and a is a constant. The image processing apparatus according to claim 34, wherein the limiter outputs the change amount as the limited change amount when the absolute value of the change amount is equal to or less than the limit function value, and outputs the limit function value as the limited change amount otherwise Improvement circuit.