KR19980014480A - Image quality improvement method using quantized mean-separated histogram equalization with gain control function and its circuit - Google Patents

Abstract

The image quality improvement method and circuit of the present invention quantizes the level of an input video signal, obtains an average of the input video signal on a screen basis, quantizes the obtained average to output a quantized average level, The quantized sub-images are divided into a predetermined number of quantized sub-images according to the quantized average level. Cumulative density function values are obtained for each quantized sub-image based on the gray-level distribution. The cumulative density function And outputs an improved signal by independently histogram equalizing each subimage on the basis of the cumulative density function value interpolated for each subimage, Based on the gray level change amount of the video signal and the improved signal and the level of the input video signal While improving the contrast hameuroseo regulate hwaryang kept constant on the average brightness of a given image, and also by preventing an artifact of the excessive improvement improve image quality.

Description

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

The present invention relates to an image quality improvement method using a quantized mean-separated histogram equalization having a gain control function and a circuit therefor. More particularly, the present invention relates to an image quality improvement method using a quantized mean- The present invention relates to a method and circuit for improving image quality by adjusting the gain of an improved signal to prevent artifacts due to excessive improvement while improving contrast by independently histogram equalizing the image.

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,

Also useful applications of the histogram equalization method including medical image processing and radar image processing are disclosed in the following documents [3], [4]: [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.

However, it can be said that the difference between input and output may be a problem that can occur when the contrast is improved based on the histogram equalization for a given image. 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 causes a problem of providing an undesired image.

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 were required to accumulate the number of occurrences of all levels.

An object of the present invention is to quantize an input image and divide the quantized input image into a predetermined number of sub-images, independently histogram equalize the sub-images to improve the contrast and maintain the average brightness constant, And to provide a method for improving image quality by adjusting a gain of an adaptively improved signal according to a level of a signal.

Another object of the present invention is to quantize an input image and divide the quantized input image into a predetermined number of sub-images and independently histogram equalize the divided sub-images so as to maintain the average brightness constant while improving contrast, There is provided a circuit for improving image quality by adjusting a gain of an adaptively improved signal according to a level of a video signal.

According to an aspect of the present invention, there is provided a method for enhancing image quality by histogram equalizing an image signal represented by a predetermined number of gray levels, the method comprising the steps of: (a) quantizing a level of an input image signal; step; (b) obtaining an average of input video signals on a screen basis, quantizing the obtained average, and outputting a quantized average level; (c) dividing the image signal quantized in step (a) into a predetermined number of quantized sub-images according to the quantized average level; (d) obtaining an accumulated density function value for each of the quantized sub-images based on a gray level distribution; (e) outputting a cumulative density function value interpolated for each sub-image by interpolation based on an input video signal and an accumulated density function value obtained for each quantized sub-image; (f) outputting an improved signal by independently histogram equalizing each subimage based on the cumulative density function value interpolated for each subimage; And (g) adjusting the amount of change according to a gray level change amount between the input video signal and the improved signal and 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: A first quantization means for outputting a 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 average level and outputting a quantized average level; Third calculation 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 and calculating an accumulated density function value for each quantized sub-image; An interpolation means for outputting a cumulative density function value interpolated for each sub-image by interpolation based on an input video signal and an accumulated density function value calculated for each of the quantized sub-images; An output unit for mapping the input video signal to a gray level according to an accumulated density function value calculated for each of the quantized sub images to output an improved signal; And a 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-separated histogram equalization with a gain adjustment function according to an embodiment of the present invention.

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

A description will be made of an image quality improvement method using a quantized mean-separated histogram equalization with a gain control function proposed in the present invention.

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

Given a picture {X} consists of L discrete gray levels {X0, X1, ..., XL-1}, where X0 = 0 is the black level and XL-1 = 1 is the white level .

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 1 L and {Z0, Z1, ..., ZQ-1} 1C {X0, X1, ..., XL-1}.

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

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

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

When {Z} = Q [{X}] and Zm = Q [Xm], Xm represents the average level of the original image, {Z} represents the quantized input image, and Zm represents the quantized average level, The quantized input image {Z} is divided into two sub-images {Z} L and {Z} U centered at Zm. Here, all samples in the quantized sub-picture {Z} L are below the quantized average level (Zm) and all samples in the quantized sub-picture {Z} U are larger than the quantized average level (Zm).

Each quantized probability density function (PDF) of the sub-image {Z} L, {Z} U can be expressed by the following equations (1) and (2).

[Equation 1]

&Quot; (2) "

P (Zq) is the probability of the q-th quantized gray level (Zq) in the quantized sub-picture {Z} U, and PL (Zq) And NqL and NqU represent the number of times the level Zq appears in the quantized sub-picture Z and the quantized sub-picture Z. NL and NU are the quantized sub-picture Z , And the total number of samples of each 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) "

Here, CL (Zm) = 1 and CU (ZQ-1) = 1.

The interpolated cumulative density function cL (Xk), cU (Xk) can be roughly calculated by linear interpolation from CL (Zq) and CU (Zq).

As shown in FIG. 2, assuming that Q [Xk] = Zq 1 Zm, Z-1 = 0 and cL (Xk) is interpolated as shown in the following equation (5).

&Quot; (5) "

Similarly, assuming that Q [Xk] = Zq Zm, cU (Xk) is interpolated as shown in Equation 6 below.

&Quot; (6) "

Here, CU (Zm) = 0.

Finally, based on the interpolated cumulative density function, the output (YH) of the proposed quantized mean-separated histogram equalization is given by Equation (7) for a given input image (Xk).

&Quot; (7) "

Here, Zm '= Zm + XL-1 / (L-1), which is the next gray level after Zm in {X0, X1, ..., XL-1}.

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

The basic concept of the gain control is to limit the change of the maximum gray level of the input video signal (Yi = Xk) according to the degree of contrast improvement when the contrast is improved by using the quantized average-separation histogram equalization.

First, the relationship between the input video signal (Yi = Xk) and the improved signal (YH) can be expressed by Equation (8) or (9) below.

&Quot; (8) "

or,

&Quot; (9) "

In this case,? Represents a level (YH) mapped to a new gray level by the amount of change (degree of improvement) produced by the quantized mean-separated histogram equalization, that is, the level of the input video signal Yi and the quantized average- .

In order to prevent excessive improvement due to histogram equalization, the present invention limits the amount of change DELTA as follows.

&Quot; (10) "

1 | Δ 1 | 1 g · f (Yi)

Where f (Yi) is a function of the input (Yi) and is always positive, i.e., f (Yi) 10, and g (g 1 0) is a gain control parameter.

Equation (10) can be expressed by Equation (11) as Equation (11).

&Quot; (11) "

- g? f (Yi) 1? 1 g? f (Yi)

The concept of limiting the amount of change (?) Shown in Equation (10) above is related to the Weber's ratio. In fact, if f (Yi) = Yi, the following Equation (12) can be obtained from Equation (10).

&Quot; (12) "

here, Is the amount corresponding to the ratio of Webber. The ratio of this webber is an experimental fact, which means that when Y1 changes by gY1 and Y2 changes by gY2, humans feel that the degree of change is the same.

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

DELTA 'is defined as a limited change amount, and can be expressed by the following Equation (13).

&Quot; (13) "

That is, if the absolute value of the change amount DELTA is less than gf (Yi), the change amount DELTA is used as the limited change amount DELTA ', and if the change amount DELTA is greater than gf (Yi) Is limited to -gf (Yi) when the change amount DELTA is less than -gf (Yi), thereby controlling the gain of the improved signal YH.

Therefore, the final output signal YOUT of the present invention can be expressed by the following Equation (14).

&Quot; (14) "

Next, an embodiment of an image quality improvement circuit using quantized mean-separated histogram equalization having a gain adjustment function in conjunction with FIG. 3 and FIG. 4 will be described.

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

In Fig. 3, the first quantizer 102 quantizes the input image signal Xk at the L discrete level to the Q discrete level, and outputs the quantized image Zq. The frame histogram calculator 104 calculates the gray level distribution of the quantized input image Zq 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 Xm of the input video signal in units of one frame. The second quantizer 108 quantizes the average level Xm of the input video signal Xk and outputs the quantized average level Zm.

The divider 110 divides the quantized gray level distribution calculated by the frame histogram calculator 104 into a predetermined number (here, two) of quantization levels based on the quantized average level Zm output from the second quantizer 108 And outputs the probability density functions PL (Zq) and PU (Zq) of the two quantized sub-images by dividing the sub-image ({Z} L, PL (Zq), PU (Zq)) can be calculated by the above Equations (1) and (2).

Here, all samples in the quantized sub-picture {Z} L are below the quantized average level (Zm) and all samples in the quantized sub-picture {Z} U are larger than the quantized average level (Zm).

The first CDF calculator 112 receives the quantized sub-picture {Z} by inputting the probability density function PL (Zq) of the quantized sub-picture {Z} L whose average level is below the quantized level of all the image samples from the divider 110, The cumulative density function value of L is calculated using the above equation (3).

The second CDF calculator 114 receives the probability density function PU (Zq) of the quantized sub-picture {Z} U where all the image samples output from the divider 110 are larger than the quantized average level Zm and quantizes The cumulative density function value of the sub-image {Z} U is calculated using Equation (4) above.

The CDF memory 116 stores cumulative density function values CL (Z (Zq), CU (Zq)) of the quantized sub-images ({Z} L, {Z} U) calculated by the first and second CDF calculators 112, And the cumulative density function values CL (Zq, CU (Zq)) of the previous screen stored during the update are supplied to the first and second interpolators 118 and 120 . 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 receives the cumulative density function of the quantized sub-image {Z} L and the input image signal XK and outputs the interpolated cumulative density function value cL (Xk) by linear interpolation according to Equation (5) ).

The first mapper 120 receives the input cumulative density function cL (Xk), the input video signal Xk and the quantized average level Zm to obtain a sub-image Z Z L, which is equal to or lower than the quantized average level Z m To the gray level from X0 to Zm according to the interpolated cumulative density function cL (Xk).

The second interpolator 122 receives the cumulative density function CU (Zq) of the quantized sub-image {Z} U and the input image signal Xk and outputs the cumulative density function interpolated by linear interpolation according to Equation (6) (cU (Xk)).

The second mapper 124 receives the interpolated cumulative density function cU (Xk), the input video signal Xk and the quantized average level Zm to obtain a sub-picture Z Z larger than the quantized average level Zm, U to the gray level from Zm 'to XL-1 according to the interpolated cumulative density function (cU (Xk)). Here, Zm '= Zm + XL-1 / (L-1).

That is, the video signal Xk input to the first and second interpolators 118 and 122 is the video signal of the next frame of the video signal Xk input to the first quantizer 102 and the frame averager 104 . 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 selector 126 compares the input video signal Xk with the quantized average level Zm output from the second quantizer 108 and outputs the first and second quantized average levels Zm, The mapper 120 is selected and if not the second mapper 124 is selected to output the improved signal YH which can be represented by the above equation (7).

Here, the first to the first quantizer 102 to the first selector 126 may be referred to as a quantized mean-separated histogram equalizer 100.

The gray level distribution of the divided image signals is calculated by the CDF calculators 112 and 114 without using the frame histogram calculator 104 and the CDF calculators 112 and 114 separately without using the frame histogram calculator 102, Can be calculated.

The subtractor 202 of the gain controller 200 subtracts the input image signal Yi = Xk from the improved signal YH output from the first selector 126 and outputs the quantized average-separated histogram equalizer 100 ) Is calculated by the following equation.

The gain characteristic determiner 204 limits the improvement of the input video signal Yi using the maximum limit function f (Yi), which is a function of the input video signal Yi. That is, the limit improvement amount of the input video signal Yi is calculated.

For example, when f (Yi) = K, and K is a constant, it equally limits input improvement regardless of the input gray value, and the maximum limit function is (Where a is a predetermined constant) or (Where a is a predetermined constant), which limits the amount of improvement of the input image differently depending on the input gray-level value.

The second selector 206 compares the input video signal Xk with the quantized average level Zm output from the second quantizer 108 and outputs the quantized average level Zm of the input video signal Xk, The first gain control parameter gL is selected, and if not, the second gain control parameter gU is selected. Here, the first gain control parameter gL is a parameter for a sub video signal whose amplitude is equal to or lower than the quantized average level Zm, and the second gain control parameter gU is a parameter for a sub video signal whose amplitude is greater than the quantized average level Zm Parameter.

The multiplier 208 multiplies the value of the maximum limit function f (Yi) output from the gain characteristic determiner 204 by the gain control parameter g selected by the second selector 206 to obtain a limit value gf (Yi) ). Here, the limit value g · f (Yi) is a characteristic of the gain controller 200 of the present invention.

The limiter 210 limits the amount of change DELTA by comparing the amount of change DELTA output from the subtractor 202 with the limit value gf (Yi) output from the multiplier 208 to obtain a limited amount of change (? ').

The adder 212 adds the input video signal Yi and the limited change amount DELTA 'output from the limiter 210 to output the output signal Yout of the gain controller 200 as shown in Equation (14) do.

4 is a block diagram according to another embodiment of the image quality improvement circuit using the quantized mean-separated histogram equalization with gain control function according to the present invention. And detailed description thereof will be omitted.

Therefore, the gain controller 200 ', which is different from the configuration shown in FIG. 3, will be described here.

4, the subtractor 222 of the gain controller 200 'subtracts the input image signal Yi = Xk from the improved signal YH output from the selector 126 and outputs the quantized average-separated histogram equalizer (?) Produced by the control unit (100). The gain characteristic determiner 224 limits the improvement of the input video signal Yi using the maximum limit function f (Yi), which is a function of the input video signal Yi.

The multiplier 226 multiplies the value of the maximum limit function f (Yi) output from the gain characteristic determiner 224 by the input gain control parameter g to output a limit value gf (Yi).

Here, the gain control parameter g is given the same value for the input image signal, unlike the gain control parameter given for each quantized sub-image in FIG.

The limiter 228 compares the amount of change DELTA output from the subtracter 222 with the limit value gf (Yi) output from the multiplier 226 to limit the amount of change DELTA, (? ').

The adder 230 adds the input image signal Yi and the limited variation amount DELTA 'output from the limiter 228 and outputs the output signal Yout of the gain controller 200' as shown in Equation (14) 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, home appliances, and the like.

As described above, according to the present invention, a sudden brightness change caused by a conventional histogram equalization and artifact is effectively reduced to improve the contrast, while maintaining the overall brightness of a given image and the gain of the improved signal based on the ratio of Weber And the image quality is improved by preventing artifacts due to an excessive improvement in contrast when adjusting the histogram.

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

Claims (30)

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 input video signal; (b) obtaining an average of input video signals on a screen basis, quantizing the obtained average, and outputting a quantized average level; (c) dividing the image signal quantized in step (a) into a predetermined number of quantized sub-images according to the quantized average level; (d) obtaining an accumulated density function value for each of the quantized sub-images based on a gray level distribution; (e) outputting a cumulative density function value interpolated for each sub-image by interpolation based on an input video signal and an accumulated density function value obtained for each quantized sub-image; (f) outputting an improved signal by independently histogram equalizing each subimage based on the cumulative density function value interpolated for each subimage; And (g) adjusting the amount of change according to a gray level change amount of the input video signal and the improved signal and a level of the input video signal. 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. 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. 2. The method of claim 1, wherein step (f) (f1) mapping samples of each quantized sub-image to a gray level according to an accumulated density function value interpolated for each sub-image; And (f2) selecting one of the signals mapped to the gray level for each of the quantized sub-images according to a result of comparing the input image signal and the quantized average level. 2. The method of claim 1, wherein the adjustment of the gain of the improved signal in step (g) is based on a ratio of Weber. The method of claim 1, wherein step (g) (g1) subtracting the input video signal from the improved signal to detect a change amount corresponding to the difference; (g2) calculating a limit improvement amount of the input video signal by a predetermined maximum limit function and a predetermined gain control parameter; (g3) comparing the limit improvement amount with the change amount, and outputting a limited change amount by limiting the change amount according to a comparison result; And (g4) adding the limited change amount to the input image signal. The method of claim 7, wherein, in step (g2), the enhancement of the input video signal is limited by a predetermined maximum limit function. 8. The method of claim 7, wherein step (g2) (g21) limiting the improvement of the input video signal by a predetermined maximum limit function to output a limited video signal; And (g22) multiplying the limited video signal by a predetermined gain control parameter to output a limit improvement amount. 10. The method of claim 9, wherein the predetermined gain control parameter comprises a plurality of gain control parameters for each quantized sub-image. 10. The image quality improvement method of claim 9, wherein the predetermined gain control parameter is one gain control parameter that is equally applied to an input video signal. 10. The method according to claim 9, wherein the maximum limit function f (Yi) , And a is a predetermined constant. 10. The method according to claim 9, wherein the maximum limit function f (Yi) , And a is a predetermined constant. The method according to claim 9, wherein, in the step (g3), the change amount is output as the limited change amount when the absolute value of the change amount is equal to or less than the limit function value, and the limit function value is output as the limited change amount . A circuit for enhancing image quality by histogram equalizing a video signal represented by a predetermined number of gray levels, the circuit comprising: A first quantization means for quantizing the level of 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 average level and outputting a quantized average level; Third calculation 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 and calculating an accumulated density function value for each quantized sub-image; An interpolation means for outputting a cumulative density function value interpolated for each sub-image by interpolation based on an input video signal and an accumulated density function value calculated for each of the quantized sub-images; An output unit for mapping the input video signal to a gray level according to an accumulated density function value calculated for each of the quantized sub images to output an improved signal; 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. The picture quality improving circuit according to claim 15, wherein the picture unit is a frame unit, and the predetermined number is 2. The image processing apparatus according to claim 15, further comprising a screen memory for delaying the input image signal in units of a screen so as to input the image signal of the same frame as the cumulative density function calculated by the third calculation means to the interpolation means A picture quality improving circuit. 16. The apparatus of claim 15, further comprising a buffer for updating the cumulative density function calculated for each sub-image quantized by the third calculation unit on a screen basis and for supplying the cumulative density function value stored during the update to the interpolation unit A picture quality improvement circuit characterized by. 16. The image quality improvement circuit according to claim 15, wherein the interpolation is linear interpolation. 16. The apparatus according to claim 15, wherein the output means A first mapper for mapping the input image signal to a gray level of a first range according to an accumulated density function value of a corresponding quantized sub-image if the input image signal is a first sub-image having an average level lower than a quantized average level; A second mapper for mapping the input image signal to a gray level of a second range according to an accumulated density function value of the corresponding quantized sub-image if the input sub-image is a second sub-image having an average level higher than the quantized average level; And And a selector for comparing the input video signal with the quantized average level to select a first mapper if it is a first sub-picture and selecting a second mapper if not. 18. The apparatus of claim 17, wherein the output means A first mapper for mapping the image signal output from the screen memory to a gray level of a first range according to an accumulated density function value of a corresponding quantized sub-image if the image signal outputted from the screen memory is a first sub- A second mapper for mapping the image signal output from the screen memory to a gray level of a second range according to an accumulated density function value of a corresponding quantized sub-image if the video signal is a second sub-image having an average level higher than the quantized average level; And And a selector for comparing the video signal output from the picture memory with the quantized average level to select a first mapper if it is a first sub-picture, and select a second mapper otherwise. 16. The image quality improvement circuit according to claim 15, wherein the gain control means controls the gain of the improved signal based on the Weber ratio. 16. The apparatus of claim 15, wherein the gain control means Detection means for subtracting the input video signal from the improved signal to detect a change amount corresponding to the difference; Gain characteristic determination means for calculating a maximum limit function value according to a level of the input video signal in order to limit the improvement of the input video signal by a predetermined maximum limit function; Selecting means for comparing the input video signal with a quantized average level to select a first gain control parameter if the input video signal is equal to or lower than a quantized average level and if not, selecting one of second gain control parameters; Multiplication means for multiplying the maximum limit function value by a gain control parameter selected by the selection means and outputting a limit function value; Limiting means 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 adding means for adding a limited amount of change to the input video signal and outputting a signal whose gain is adjusted for the improved signal. 24. The method of claim 23, wherein the maximum limit function f (Yi) , And a is a predetermined constant. 24. The method of claim 23, wherein the maximum limit function f (Yi) , And a is a predetermined constant. The limiter according to claim 23, wherein the limiting means 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 Image quality improvement circuit. 16. The apparatus of claim 15, wherein the gain control means Detection means for subtracting the input video signal from the improved signal to detect a change amount corresponding to the difference; Gain characteristic determining means for calculating a maximum limit function value according to a level of the input video signal in order to limit the improvement of the video signal input by the predetermined maximum limit function; Multiplying means for multiplying the maximum limit function value by a gain control parameter of a predetermined value to output a limit function value; Limiting means 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 adding means for adding a limited amount of change to the input video signal and outputting a signal whose gain is adjusted for the improved signal. 28. The method of claim 27, wherein the maximum limit function f (Yi) , And a is a predetermined constant. 28. The method of claim 27, wherein the maximum limit function f (Yi) , And a is a predetermined constant. 28. The apparatus according to claim 27, wherein the limiting means outputs the change amount as the limited change amount when the absolute value of the change amount is less than or equal to the limit function value, and outputs the limit function value as the limited change amount otherwise Image quality improvement circuit.