CN101340511A - Adaptive video image enhancing method based on lightness detection - Google Patents

Adaptive video image enhancing method based on lightness detection Download PDF

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CN101340511A
CN101340511A CNA2008101460562A CN200810146056A CN101340511A CN 101340511 A CN101340511 A CN 101340511A CN A2008101460562 A CNA2008101460562 A CN A2008101460562A CN 200810146056 A CN200810146056 A CN 200810146056A CN 101340511 A CN101340511 A CN 101340511A
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value
component
pixel
image
brightness
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CN101340511B (en
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黄晓红
张志辉
吴钊
王宁
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ZTE Corp
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ZTE Corp
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Abstract

The invention provides a self-adaptive video image enhancement method on the basis of brightness detection. The method of the invention detects the images under different illumination conditions and enhances the low-illumination images according to the detection result. When the images are detected, average values of brightness values of all sampling points of YUV-format images in a RGB colour space are taken as the brightness value of current frame of image. For each frame of image to be processed, if the brightness value of the frame of image is less than the prearranged brightness limit value of image under normal illumination, piecewise linearity is transformed for the value of Y-component of each pixel point in the area to be processed of the frame of image so as to improve the visible effect of the low-illumination image. In order to quicken the operation speed, the brightness values of all sampling points of the image in the RGB colour space are gained and the linear transform on the Y-component of the image under low illumination is operated in a form of table lookup. The method of the invention has small calculated quantities, meets the requirement of real-time performance and can be used for the processing of video images in video communication of mobile phones and televisions.

Description

A kind of adaptive video image enhancing method that detects based on brightness
Technical field
The invention belongs to the Image Information Processing field, be specifically related to the adaptive video image enhancing method that detects based on brightness.
Background technology
The figure image intensifying is a kind of basic means of image processing, the preprocessing process when its various often graphical analysis and processing, and its main purpose is: 1) improve the visual effect of image, improve the definition of iconic element; 2) image is become and more help Computer Processing.The method of figure image intensifying generally is divided into spatial domain and transform domain two big classes: the spatial domain method is directly handled the gray scale of image pixel, the transform domain method is handled conversion coefficient in certain transform domain of image, obtains to strengthen the result by inverse transformation then.
The details gray scale difference of low-light (level) image is only in tens grades, and the gradation of image value is lower.Therefore, wish to see the outstanding as far as possible again local detail of entire image by a kind of image enhancement processing.Traditional histogram equalization method is that a known gray scale probability density distribution image is become the new images that a width of cloth has even gray probability density distribution through certain conversion, consequently expand the dynamic range of pixel value, thereby reaching the effect that strengthens the integral image contrast, is a kind of gray scale enhancement algorithms commonly used.When using this method that some image is handled, its concrete reinforced effects is wayward, and result always obtains the histogram of overall equalization.The problem that may exist is as follows:
1) the actual grey excursion of output image is difficult to reach the maximum intensity change scope that picture format allows.
2) though the intensity profile histogram of output image distributes near even, still might there be bigger difference in its value and ideal value, are not to be optimum value.
3) gray scale of output image might be merged too much, therefore causes losing of image, information easily.
Summary of the invention
Technical problem to be solved by this invention provides a kind of adaptive video image enhancing method that detects based on brightness, improves the subjective vision effect of video image under the low light conditions, does not cause the display distortion of the sufficient picture of illumination simultaneously.
In order to solve the problems of the technologies described above, the invention provides a kind of adaptive video image enhancing method that detects based on brightness, comprising:
To each pending two field picture, as the brightness value of this two field picture luminance threshold value less than default normal illumination image, then the value of each the pixel Y component in the pending zone of this two field picture is carried out piecewise linear transform: be positioned at the default peaked high luminance values of the Y component interval that comprises as the value of this pixel Y component, then keep the value of this pixel Y component constant, otherwise, the linear transformation that makes this value increase to the value of this pixel Y component, and with the value of the value that obtains after the linear transformation as this pixel Y component after strengthening.
Further, said method also can have following characteristics: described linear transformation is carried out in the following manner:
The whole value scope of pixel Y component is divided into first interval, the second interval and described high luminance values interval from small to large, and first interval and second section boundaries are first threshold T 1, second interval is second threshold T with the high luminance values section boundaries 2
When the value of pixel Y component is positioned at first interval, Y '=Y (T 1+ α)/T 1(a);
When the value of pixel Y component is positioned at second interval:
Y′=T 1+α+(Y-T 1)(T 2-T 1-α)/(T 2-T 1) (b);
Wherein, Y is the original value of Y component, and Y ' is the value that the Y component obtains after linear conversion, and α is the value of Y component adjusting range parameter.
Further, said method also can have following characteristics: the value α of described Y component adjusting range parameter determines in the following manner:
α=min(Th 2,β(Th 1-Lum))
Wherein, Lum is the brightness value of current frame image, Th 1Be the luminance threshold value of default normal illumination image, Th 2Be the maximum of default Y component adjusting range, β is for default regulatory factor and satisfy 0<β<1,0<α<T 2-T 1
Further, said method also can have following characteristics: the brightness value of described current frame image equals the brightness value of this two field picture at rgb color space.
Further, said method also can have following characteristics:
The brightness value of described current frame image equals in the pending zone of this two field picture all or part of pixel in the average of the brightness value of rgb color space, and described pixel is meant maximum in the value of this pixel R component, G component and B component at the brightness value of rgb color space.
Further, said method also can have following characteristics:
The brightness value of described current frame image equals the average of the pixel of non-high brightness in the pending zone of this two field picture at the brightness value of rgb color space; The pixel of described non-high brightness is meant that minimum value in the value of this pixel R component, G component and B component is less than default high luminance threshold value.
Further, said method also can have following characteristics:
Described each pending two field picture is the image of yuv format, when calculating the brightness value of current frame image, to each pixel in the pending zone of this two field picture, earlier obtain maximum and minimum value in the value of this pixel R component, G component and B component according to the value of Y component, U component and the V component of this pixel.
Further, said method also can have following characteristics:
Y plane employing to described yuv format image makes Y plane and U, V plane have the down-sampling mode of identical size.
Further, said method also can have following characteristics:
Maximum and minimum value in the value of described pixel R component, G component and B component obtain in the following manner:
Before two field picture handled, the value of traversal U component and V component was calculated max (R ', G ' B ') and min (R ', G ' B ') earlier) value, with the first look-up table Table ' 1The corresponding relation of the value of the value of record U component, V component and max (R ', G ', B '), usefulness second look-up table Table ' 2The corresponding relation of the value of the value of record U component, V component and min (R ', G ', B '),
Wherein:
R′=1.402(V-128)
G′=-0.34414(U-128)-0.71414(V-128)
B′=1.772(U-128)
Then, the value of traversal Y component and max (R ', G ', B ') calculate max (R, G, value B), the value of traversal Y component and min (R ', G ', B ') is calculated min, and (value B) is with the 3rd look-up table Table for R, G 1(corresponding relation of value B) is with the 4th look-up table Table for R, G for the value of record Y component and max (R ', G ', B ') and max 2The value of record Y component and min (R ', G ', B ') and min (R, G, the corresponding relation of value B), wherein:
max(R,G,B)=min(255,Y+max(R′,G′,B′))
min(R,G,B)=max(0,Y+min(R′,G′,B′))
Max in the formula (R, G, B) and min (R, G B) are maximum and minimum value in the value of pixel R component, G component and B component;
When maximum in the value of calculating pixel point R component, G component and B component and minimum value, look into the first look-up table Table ' according to the value of this pixel U component and V component earlier 1With second look-up table Table ' 2Obtain the value of corresponding max (R ', G ', B ') and min (R ', G ', B '), and then look into the 3rd look-up table Table in conjunction with the value of this pixel Y component 1With the 4th look-up table Table 2Can obtain in the value of this pixel R component, G component and B component maximum max (R, G, B) and minimum value min (R, G, B).
Further, said method also can have following characteristics:
Before two field picture handled, first by formula (a) and the value Y ' that (b) obtains after the calculating linear transformation of the value α of the value Y of traversal pixel Y component and Y component adjusting range parameter, and with the corresponding relation of the 5th look-up table YMap record Y, α and Y ', 0<α<T 2-T 1And α is a positive integer;
In calculated value Y ' time, directly search the 5th look-up table YMap according to the value Y of the Y component that is positioned at first interval or second interval and the value α of Y component adjusting range parameter, obtain the respective value Y ' of Y through linear conversion.
Further, said method also can have following characteristics: the pending zone of described two field picture is the entire frame image, perhaps is meant the zone that is used to show in the entire frame image.
Further, said method also can have following characteristics: described T 1Span be 30~80, T 2Span be 200~250, Th 1Span be 110-135, Th 2≤ Th 1-T 1, the span of β is 0.6~1.
Adopt method of the present invention, detect and the low-light (level) image is strengthened by video image according to testing result to different illumination conditions, can in the dynamic range of suitably expanding pixel value, avoid gray scale to be merged too much as far as possible, solve the image fault problem that traditional histogram equalization method is brought, substantially do not changing under the prerequisite of normal illumination image, obviously improve the visual effect of dark scene image, obtain the output image of higher quality.Further make that by method such as table look-up the amount of calculation of the inventive method is little, can satisfy the demand of real-time, have stronger using value, can be used for the processing of mobile TV video communication video image.
Description of drawings
Fig. 1 is the flow chart of present embodiment based on the adaptive video image enhancing method of brightness detection;
Fig. 2 A is a Y plane sampling schematic diagram;
Fig. 2 B is a UV plane sampling schematic diagram.
Embodiment
Need in the present embodiment method to determine maximum and minimum value in the value of this pixel R, G, B component according to the value of pixel Y, U, V component, because the YUV color space relates to floating-point operation to the conversion of rgb color space, present embodiment writes maximum and the minimum value in the value of R, the G of the value correspondence of each Y, U, V component, B component in the look-up table, by the quick computing of look-up tables'implementation.If the value of traversal Y, U, V component is provided with look-up table, the table capacity respectively is 256 * 256 * 256 bytes.To realize needed internal memory in order reducing, to adopt the mode of Quadratic Map.Before video image is carried out enhancement process, carry out following look-up table initialization operation earlier.
YUV is as follows to the change type between the RGB:
R=Y+1.402(V-128)
G=Y-0.34414(U-128)-0.71414(V-128)
B=Y+1.772(U-128)
As not considering the influence of Y, following formula is write as:
R′=1.402(V-128)
G′=-0.34414(U-128)-0.71414(V-128) (1)
B′=1.772(U-128)
Obtain thus,
max(R,G,B)=min(255,Y+max(R′,G′,B′))
(2)
min(R,G,B)=max(0,Y+min(R′,G′,B′))
Above Y, U, V, R, G, B represent the value of YUV, rgb color space respective component respectively, and max (R ', G ', B '), min (R ', G ', B ') represents R ', G ' respectively, maximum among the B ' and minimum value, max (R, G, B), min (R, G B) represents maximum, minimum value among R, G, the B respectively.
During initialization, the first value of traversal U component and V component is calculated the value of max (R ', G ', B ') and min (R ', G ', B ') by formula (1), uses look-up table Table ' 1[256] corresponding relation of the value of the value of [256] record U component, V component and max (R ', G ', B '), usefulness look-up table Table ' 2[256] corresponding relation of the value of the value of [256] record U component, V component and min (R ', G ', B ').The interval of U, V component is [0,255], so Table ' 1[256] [256], Table ' 2[256] [256] needed internal memory only is 256 * 256 bytes.
Then, the value of traversal Y component and max (R ', G ', B '), by formula (2) calculate max (R, G, value B), the value of traversal Y component and min (R ', G ', B ') is calculated min, and (value B) is used look-up table Table for R, G 1[256] (corresponding relation of value B) is used look-up table Table for R, G for the value of [256] record Y component and max (R ', G ', B ') and max 2[256] value and min (R, G, the corresponding relation of value B) of [512] record Y component and max (R ', G ', B ').The interval of considering max (R ', G ', B '), min (R ', G ', B ') is no more than [0,255], [256,255], Table 1[256] [256], Table 2[256] [512] required memory is respectively: 256 * 256,256 * 512 bytes.
In addition, present embodiment has also been set up a table and has been preserved the value α of the value Y of pixel Y component, Y component adjusting range parameter and the corresponding relation of the value Y ' that Y is carried out obtaining after the linear transformation, for ease of understanding, is elaborated in the correlation step hereinafter again.
The flow process of the adaptive video image enhancing method that present embodiment detects based on brightness as shown in Figure 1, from the decoding output buffer, read in the image of a frame yuv format after, the processing of this two field picture be may further comprise the steps:
Step 110 is carried out down-sampling to the Y plane in this pending zone of two field picture, and the mode of used down-sampling makes the Y plane have identical size with U, V plane;
When two field picture is the YUV image of 4:2:0 pattern, need in level and vertical direction 1/2 down-sampling to be carried out on this two field picture Y plane respectively, make it have identical size with U, V plane.To reduce amount of calculation and to be beneficial to the calculating that color space is changed.But, be not limited thereto for the present invention, because no matter adopt which kind of down-sampling mode, all can calculate the value of R component, G component and B component (being abbreviated as R, G, B component) according to the value of Y component, U component and V component (being abbreviated as Y, U, V component), also just can finish in the subsequent treatment calculating equally, and then realize the figure image intensifying by linear transformation to pixel brightness value and image brightness value.
For pending image, might not handle Zone Full, for example final of some image needs demonstration subregion wherein, image enhancement processing is carried out as pending zone in this subregion that can show this moment, and other regional pixel does not need to carry out any processing.Supposing that image is upper and lower respectively has 1/8 interval not belong to pending zone, then can further reduce sampled point, promptly gets rid of the point in upper and lower each 1/8 interval.4:2:0 pattern YUV image with the 16*16 size is an example, and the Y plane sampled point that participates in the color space conversion is shown in Fig. 2 A, and U, V plane sampled point are shown in Fig. 2 B.Sampled point is wherein represented with small circle.
Step 120, obtain in Y, U, the V plane of sampling each pixel at the brightness value of rgb color space, this brightness value equals the maximum in the value of pixel R, G, B component, simultaneously wherein the average brightness value of the pixel of non-high brightness as the brightness value of current frame image;
In the present embodiment, the pixel of non-high brightness is meant that minimum value in the value of this pixel R, G, B component is less than default high luminance threshold value.The pixel of high brightness is often corresponding to light source point.
During concrete calculating, if satisfy min (R, G, B)<T 3Judge that then this sampled point is the pixel of non-high brightness, the number and the brightness value max (R thereof of the sampled point of this condition will be satisfied, G, B) add up respectively, obtain the total number Pixels of the pixel of non-high brightness in this two field picture of a width of cloth, and the brightness value sum Total_Lum of the sampled point of non-high brightness.T wherein 3May obtain by a large amount of experiments.
After the detection of each sampled point finished, calculate the average brightness value (also can be weighted on average) of the sampled point of non-high brightness to these sampled points, and with its brightness value as current frame image:
Lum = Total _ Lum Pixels ;
Come the brightness value of calculating pixel point and two field picture with the maximum of the R in the rgb color space, G, B component, than directly calculate the true brightness that will meet image more with the Y component in the YUV color space, help obtaining the output image of higher quality.But the present invention also can directly use the brightness value of the value of Y component as pixel, when calculating the brightness value of two field picture, can calculate the average brightness of brightness value less than the pixel of default high luminance threshold value.
In addition, the present invention also can not consider the influence of the pixel of high brightness, directly with the average brightness value of all pixels of the pending zone brightness value as current frame image.
For any sampled point (Y, U, V), when maximum in the value of determining its R, G, B component in rgb color space of tabling look-up and minimum value, earlier according to the value of this pixel U component and the V component Table ' that tables look-up 1[256] [256] and table Table ' 2[256] [256] obtain the value of corresponding max (R ', G ', B ') and min (R ', G ', B '), and then in conjunction with the value of this pixel Y component Table that tables look-up 1[256] [256] and table Table 2[256] [512] can obtain maximum and the minimum value in the value of this pixel R component, G component and B component.Be formulated as follows:
max(R,G,B)=Table 1[Y][Table 1′[U][V]];
min(R,G,B)=Table 2[Y][Table 2′[U][V]]。
Step 130 is with the luminance threshold value Th of the normal illumination image of the brightness value L um of current frame image and setting 1Compare, if the brightness value of current frame image is more than or equal to this luminance threshold value Th 1, then need not this two field picture is strengthened, keep the Y component of current frame image constant, finish enhancement process to this two field picture; If the brightness value L um of current frame image is less than this luminance threshold value Th 1, execution in step 140;
Step 140 is according to the brightness value L um and the luminance threshold value Th of current frame image 1Difference determine the value α of the Y component adjusting range of current frame image, then the value of each pixel Y component in the pending zone of current frame image is carried out piecewise linear transform, and with the value of the value that obtains after the linear transformation as this pixel Y component after strengthening;
The value α of Y component adjusting range determines according to following formula:
α=min(Th 2,β(Th 1-Lum))
Wherein, Lum represents the current frame image brightness value that calculated by previous step; β is default regulatory factor, and satisfies 0<β<1; Th 1The luminance threshold value of representing normal illumination image; Th 2The maximum of expression Y component adjusting range can be obtained by experiment.
Should be noted that α also can adopt the mode of tabling look-up according to Lum to obtain.
Present embodiment is that the whole span with the Y component is divided into 3 intervals, be respectively [0, T 1), [T 1, T 2], (T 2, 255] and interval, wherein (T 2, 255] and the interval also can be described as the high luminance values interval.T 1Be first interval and second section boundaries, also can be included in second interval.T 2Be the second interval and high luminance values section boundaries, also can be included in the high luminance values interval.Threshold T 1, T 2Can set according to experiment, and satisfy 0<T 1<T 2<255; α be interval (0, T 2-T 1) in arbitrary value.
When the value Y of Y component is carried out piecewise linear transform, carry out as follows:
As Y>T 2The time, think that this pixel is highlighted, do not revise the value of its Y component, that is:
Y′=Y;
Work as T 1≤ Y≤T 2The time, by linear relationship it is projected [T 1+ α, T 2] in the interval, that is:
Y′=T 1+α+(Y-T 1)(T 2-T 1-α)/(T 2-T 1); (3)
As Y<T 1The time, by linear relationship it is projected [0, T 1+ α) in the interval, that is:
Y′=Y(T 1+α)/T 1; (4)
Wherein, the value of Y ' for Y being carried out obtain after the linear transformation;
The method of above-mentioned linear transformation can avoid gray scale to be merged too much in the dynamic range of suitably expanding pixel value as far as possible, solve the image fault problem that traditional histogram equalization method is brought, not changing substantially under the prerequisite of normal illumination image, obviously improve the visual effect of dark scene image.But the division in above-mentioned interval and concrete linear transformation formula are not unique, as except that the high luminance values interval, can be divided into first interval, second interval and the 3rd interval again, perhaps only mark off first interval, or the like.The present invention does not do qualification to this.
In order to accelerate arithmetic speed, present embodiment remains the Y ' value that finds the Y correspondence by the mode of tabling look-up.Like this before step 110, need earlier traversal be positioned at [0, T 1), [T 1, T 2] the value Y of interval Y component and the value α of Y component adjusting range parameter (α ∈ (0, T 2-T 1) and α be positive integer), by formula (3) and (4) calculate the value Y ' to arriving after the Y linear transformation, and with table YMap[256] [256] write down the corresponding relation of Y ' and Y, α, this table required in save as 256 * 256 bytes.
After calculating α, for be positioned at [0, T 1), [T 1, T 2] the value Y of interval Y component, in conjunction with the value α of the Y component adjusting range parameter that the calculates YMap[256 that tables look-up] [256], can obtain the value Y ' that obtains after the Y linear transformation, i.e. Y '=YMap[α] [Y].
Step 150 will be sent into display buffer through the view data that strengthens.
Above-mentioned T 1, T 2, Th 1, T 3, β reference value be: T 1: 30~80; T 2: 200~250; T 3: 235-255; Th 1: 110-135; Th 2≤ Th 1-T 1β: 0.6~1.

Claims (12)

1, a kind of adaptive video image enhancing method that detects based on brightness comprises:
To each pending two field picture, as the brightness value of this two field picture luminance threshold value less than default normal illumination image, then the value of each the pixel Y component in the pending zone of this two field picture is carried out piecewise linear transform: be positioned at the default peaked high luminance values of the Y component interval that comprises as the value of this pixel Y component, then keep the value of this pixel Y component constant, otherwise, the linear transformation that makes this value increase to the value of this pixel Y component, and with the value of the value that obtains after the linear transformation as this pixel Y component after strengthening.
2, the method for claim 1 is characterized in that, described linear transformation is carried out in the following manner:
The whole value scope of pixel Y component is divided into first interval, the second interval and described high luminance values interval from small to large, and first interval and second section boundaries are first threshold T 1, second interval is second threshold T with the high luminance values section boundaries 2
When the value of pixel Y component is positioned at first interval, Y '=Y (T 1+ α)/T 1(a);
When the value of pixel Y component is positioned at second interval:
Y′=T 1+α+(Y-T 1)(T 2-T 1-α)/(T 2-T 1) (b);
Wherein, Y is the original value of Y component, and Y ' is the value that the Y component obtains after linear conversion, and α is the value of Y component adjusting range parameter.
3, method as claimed in claim 2 is characterized in that, the value α of described Y component adjusting range parameter determines in the following manner:
α=min(Th 2,β(Th 1-Lum))
Wherein, Lum is the brightness value of current frame image, Th 1Be the luminance threshold value of default normal illumination image, Th 2Be the maximum of default Y component adjusting range, β is for default regulatory factor and satisfy 0<β<1,0<α<T 2-T 1
As claim 1 or 2 or 3 described methods, it is characterized in that 4, the brightness value of described current frame image equals the brightness value of this two field picture at rgb color space.
5, method as claimed in claim 4 is characterized in that:
The brightness value of described current frame image equals in the pending zone of this two field picture all or part of pixel in the average of the brightness value of rgb color space, and described pixel is meant maximum in the value of this pixel R component, G component and B component at the brightness value of rgb color space.
6, method as claimed in claim 5 is characterized in that:
The brightness value of described current frame image equals the average of the pixel of non-high brightness in the pending zone of this two field picture at the brightness value of rgb color space; The pixel of described non-high brightness is meant that minimum value in the value of this pixel R component, G component and B component is less than default high luminance threshold value.
7, method as claimed in claim 5 is characterized in that:
Described each pending two field picture is the image of yuv format, when calculating the brightness value of current frame image, to each pixel in the pending zone of this two field picture, earlier obtain maximum and minimum value in the value of this pixel R component, G component and B component according to the value of Y component, U component and the V component of this pixel.
8, method as claimed in claim 7 is characterized in that:
Y plane employing to described yuv format image makes Y plane and U, V plane have the down-sampling mode of identical size.
9, method as claimed in claim 8 is characterized in that,
Maximum and minimum value in the value of described pixel R component, G component and B component obtain in the following manner:
Before two field picture handled, the value of traversal U component and V component was calculated max (R ', G ', B ') and min (R ', G ', B ') earlier) value, with the first look-up table Table 1The corresponding relation of the value of the value of ' record U component, V component and max (R ', G ', B ') is used second look-up table Table 2The corresponding relation of the value of the value of ' record U component, V component and min (R ', G ', B '), wherein:
R′=1.402(V-128)
G′=-0.34414(U-128)-0.71414(V-128)
B′=1.772(U-128)
Then, the value of traversal Y component and max (R ', G ', B ') calculate max (R, G, value B), the value of traversal Y component and min (R ', G ', B ') is calculated min, and (value B) is with the 3rd look-up table Table for R, G 1(corresponding relation of value B) is with the 4th look-up table Table for R, G for the value of record Y component and max (R ', G ', B ') and max 2The value of record Y component and min (R ', G ', B ') and min (R, G, the corresponding relation of value B), wherein:
max(R,G,B)=min(255,Y+max(R′,G′,B′))
min(R,G,B)=max(0,Y+min(R′,G′,B′))
Max in the formula (R, G, B) and min (R, G B) are maximum and minimum value in the value of pixel R component, G component and B component;
When maximum in the value of calculating pixel point R component, G component and B component and minimum value, look into the first look-up table Table according to the value of this pixel U component and V component earlier 1' and second look-up table Table 2' obtain the value of corresponding max (R ', G ', B ') and min (R ', G ', B '), and then look into the 3rd look-up table Table in conjunction with the value of this pixel Y component 1With the 4th look-up table Table 2Can obtain in the value of this pixel R component, G component and B component maximum max (R, G, B) and minimum value min (R, G, B).
10, method as claimed in claim 3 is characterized in that:
Before two field picture handled, first by formula (a) and the value Y ' that (b) obtains after the calculating linear transformation of the value α of the value Y of traversal pixel Y component and Y component adjusting range parameter, and with the corresponding relation of the 5th look-up table YMap record Y, α and Y ', 0<α<T 2-T 1And α is a positive integer;
In calculated value Y ' time, directly search the 5th look-up table YMap according to the value Y of the Y component that is positioned at first interval or second interval and the value α of Y component adjusting range parameter, obtain the respective value Y ' of Y through linear conversion.
11, as claim 3, the described method of arbitrary claim in 5 to 10 is characterized in that:
The pending zone of described two field picture is the entire frame image, perhaps is meant the zone that is used to show in the entire frame image.
12, method as claimed in claim 3 is characterized in that:
Described T 1Span be 30~80, T 2Span be 200~250, Th 1Span be 110-135, Th 2≤ Th 1-T 1, the span of β is 0.6~1.
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