CN101286231A

CN101286231A - Contrast enhancement method for uniformly distributing image brightness

Info

Publication number: CN101286231A
Application number: CNA2008100446303A
Authority: CN
Inventors: 刘强
Original assignee: Sichuan Hongwei Technology Co Ltd
Current assignee: Sichuan Hongwei Technology Co Ltd
Priority date: 2008-06-04
Filing date: 2008-06-04
Publication date: 2008-10-15
Anticipated expiration: 2028-06-04
Also published as: CN101286231B

Abstract

The invention relates to a contrast enhancing method of brightness of an evenly distributed image, which comprises the specific steps: a. the image is input, the display range from 0 to 255 of the whole gray is evenly divided into at least two continuous sub-regions as the target sub-regions for the mapping of the input image; b. the distribution of a histogram of the input image is calculated, thus counting the number of pixels which are corresponding to each gray level; c. the gray levels of the input image are divided into continuous sub-regions with the same number of the target sub-regions, and the number of the pixels corresponded by the gray level of each sub-region is roughly equal; d. and each continuous gray level sub-region of the input image is mapped to the target sub-regions divided from the gray range from 0 to 255. Compared with the histogram equalization processing method, the method can not only increase the visual distance between the pixels, but also better maintain the details of the image.

Description

A kind of contrast enhancement process of uniformly distributing image brightness

Technical field

The invention belongs to Digital Image Processing and video display technology field, be specifically related to a kind of picture contrast Enhancement Method of uniformly distributing image brightness.

Background technology

It is one of important technology in the digital image processing field that picture contrast strengthens, and by regulating the distribution of image gray levels, can increase the visible sensation distance between each pixel, makes fuzzy target easy identification, improves the viewing quality of image.Histogram equalization is modal picture contrast enhancement process method, this method is sought the gray level of the output image after the conversion according to the cumulative probability density of each gray level of input picture, according to the cumulative distribution function that calculates, set up the corresponding relation between input picture and the output image gray scale.It can play good effect to strengthening general pattern, but when the shared grey level number of image is considerably less, histogram equalization can be expanded several gray levels that contain a large amount of pixels to such an extent that hold very much, and have only the gray level of small number of pixels point seriously to be pushed, occur excessively strengthening, it is bright or dark excessively that enhancing back image is crossed, and is the histogram of an input picture as Fig. 3, and Fig. 4 is the histogram among Fig. 3 is handled the back output image through histogram equalization a histogram; By the contrast of two width of cloth drawings, can clearly reflect the limitation of prior art.

Summary of the invention

The technical problem to be solved in the present invention is the deficiency at existing picture contrast enhancement process method, proposes a kind of picture contrast Enhancement Method of uniformly distributing image brightness.

The present invention solves the problems of the technologies described above the technical scheme that is adopted, not the gray level of seeking the output image after the conversion according to the cumulative probability density of each gray level of input picture, but with the continuous gray-scales interval mapping that contains same pixel point of an input picture gray level interval with fixed grey level number to output image.Not only make the intensity profile of output image even like this after the conversion, and because the number of greyscale levels in the gray level interval of output image fix rather than determine by the cumulative probability density of gray level, so some gray level that can overcome input picture is by hyper expanded and the phenomenon that other gray levels are seriously pushed.

The present invention is that the concrete grammar that solves the problems of the technologies described above the technical scheme that is adopted is: a kind of contrast enhancement process of uniformly distributing image brightness, comprise following concrete steps: a. input picture, and whole gray scale indication range 0～255 is equally divided at least two continuous sub-ranges, as the target sub-range of input picture mapping; B. the histogram distribution of calculating input image is added up the pixel number of each gray level correspondence; C. the gray level with input picture is divided into the continuous sub-range identical with target sub-range quantity, and the number of pixels of gray level correspondence about equally in each sub-range; D. each the continuous gray level sub-range with input picture is mapped to by on the target sub-range that marks off between 0～255 gray area.

Further, the method for dividing the target sub-range is that whole gray scale indication range 0～255 is equally divided into 16 sub-ranges, is respectively L ₁[0,15], L ₂[16,31] ... L ₁₆[240,255].

Beneficial effect concrete manifestation of the present invention is in the following areas: the method expansion or the compression gray level that adopt histogram equalization, a lot of gray levels all are not used, and the present invention utilizes the gray level segmentation, with the continuous gray-scales interval mapping of the different length of input picture to the identical continuous target sub-range of gray scale indication range several length between 0～255, if number of greyscale levels is few in the input picture gray level sub-range, these gray levels are inserted in the target sub-range in inciting somebody to action so, increased the brightness distance between each gray level in so not only interval, and also increased with the distance in adjacent other interval, made full use of each gray level.Compare with the histogram equalization disposal route, the present invention can not only increase the visible sensation distance between the pixel, also can better keep image detail simultaneously.

Description of drawings

Fig. 1 is the process flow diagram of contrast enhancement process of the present invention.

Fig. 2 is the process flow diagram that each continuous sub-range of input picture of the present invention is mapped to the target sub-range.

Fig. 3 is the histogram of the input picture of one embodiment of the invention.

Fig. 4 is the histogram of Fig. 3 is handled the back output image through histogram equalization a histogram.

Fig. 5 is the histogram of Fig. 3 is handled the back output image through a method of the present invention histogram.

Embodiment

The invention will be further described below in conjunction with the drawings and specific embodiments.

Fig. 3 is the histogram of an input picture, in conjunction with the process flow diagram of Fig. 1 and Fig. 2 this input picture is handled.

(1) input picture, and whole gray scale indication range 0～255 is equally divided into 16 sub-ranges, be respectively L ₁[0,15], L ₂[16,31] ... L ₁₆[240,255] are as the target sub-range of input picture mapping.

(2) ask the input picture histogram distribution, add up the pixel number of each gray level correspondence.

(3) minimum gray level of calculating input image and high grade grey level Min, Max.

(4) if the input picture size is M * N, the grey level range Min～Max with whole input picture is divided into 16 continuous gray level sub-ranges equally

L ₁′[Min，x ₁]，L ₂′[x ₁+1，x ₂]...L ₁₆′[x ₁₅+1，Max]。

(4a) gray level with input picture is distributed into 16 gray level sub-ranges that length is identical, and

The pixel number of supposing each gray level sub-range correspondence is identical, and the interval corresponding pixel number of each gray level is so:

Mean = \frac{M \times N}{16} .

(4b) still the pixel number of different gray level correspondences has nothing in common with each other, so a deviate is set

Setover = \frac{M \times N}{256},

After making that like this input picture gray level is divided, each gray level

Interval corresponding pixel number all is in Mean ± Setover scope.

(5) the gray level sub-range L that input picture is divided _i' [x _I-1+ 1, x _i] in gray level be mapped to target

Sub-range L _iOn the gray level in [16 * (i-1), 16 * i-1].

As described in step (5), the specific practice that the continuous gray-scales sub-range of an input picture is transformed to the target sub-range is:

(5a) at first add up input picture sub-range L _i' [x _I-1+ 1, x _i] in number of greyscale levels n;

(5b) as if n＜8, with sub-range L _i' [x _I-1+ 1, x _i] in n continuous gray-scales be mapped to the sub-range

L _iIn [16 * (i-1), 16 * i-1], and the gray level after the feasible mapping is with the sub-range

L _i[16 * (i-1), 16 * i-1] are divided into the n+1 equal portions.

In the above-mentioned steps each continuous gray level sub-range of input picture is mapped to the concrete formula on the target sub-range:

L = 16 * (i - 1) + (L^{'} - x_{i - 1}) * \frac{16}{n + 1};

In this formula, L ' is the gray level of interval i in the input picture, L is the gray level of L ' mapping back target interval. formula has been realized and will be inserted in a few gray level in the sub-range of input picture on 16 gray levels of target interval, in the sub-range such as input picture 3 gray levels are arranged, so through being distributed in after the mapping on the 4th, the 8th on 16 grades of gray level intervals of target interval and the 12 gray level.

(5c) if n 〉=8, then these grey scale linear ground are stretched or be compressed to sub-range L _iOn [16 * (i-1), 16 * i-1] last 16 gray levels.

* (i - 1) + (L^{'} - x_{i - 1}) * \frac{16}{n};

The implication of symbol is identical in the symbol step (5b) in this formula.

Each gray level sub-range L of input picture _i' [x _I-1+ 1, x _i] all be mapped to new target sub-range after, finished the picture contrast enhancing, as Fig. 5 is the histogram of the histogram of Fig. 3 through method processing of the present invention back output image, compare with the histogram of output image after the histogram equalization method of prior art among Fig. 4 is handled, the present invention can not only increase the visible sensation distance between the pixel, also can better keep image detail simultaneously.

Those of ordinary skill in the art will appreciate that embodiment described here is in order to help reader understanding's principle of the present invention, should to be understood that the protection domain of inventing is not limited to such special statement and embodiment.Everyly make various possible being equal to according to foregoing description and replace or change, all be considered to belong to the protection domain of claim of the present invention.

Claims

1. the contrast enhancement process of a uniformly distributing image brightness is characterized in that, comprises following concrete steps:

A. input picture, and whole gray scale indication range 0～255 is equally divided at least two continuous sub-ranges, as the target sub-range of input picture mapping;

B. the histogram distribution of calculating input image is added up the pixel number of each gray level correspondence;

C. the gray level with input picture is divided into the continuous sub-range identical with target sub-range quantity, and the number of pixels of gray level correspondence about equally in each sub-range;

D. each the continuous gray level sub-range with input picture is mapped to by on the target sub-range that marks off between 0～255 gray area.

2. the contrast enhancement process of a kind of uniformly distributing image brightness according to claim 1 is characterized in that, the method for dividing the target sub-range among the step a is:

Whole gray scale indication range 0～255 is equally divided into 16 sub-ranges, is respectively L ₁[0,15], L ₂[16,31] ... L ₁₆[240,255].

3. the contrast enhancement process of a kind of uniformly distributing image brightness according to claim 2 is characterized in that, the concrete steps of dividing the continuous sub-range of input picture among the step c are:

C1. the minimum gray level Min of calculating input image and high grade grey level Max;

If c2. the input picture size is M * N, the grey level range Min～Max of whole input picture is divided into 16 continuous gray level sub-range L ₁' [Min, x ₁], L ₂' [x ₁+ 1, x ₂] ... L ₁₆' [x ₁₅+ 1, Max].

4. the contrast enhancement process of a kind of uniformly distributing image brightness according to claim 3 is characterized in that, the method for dividing the input picture grey level range among the step c2 is:

I. the gray level with input picture is distributed into 16 gray level sub-ranges that length is identical, and supposes that the pixel number of each gray level sub-range correspondence is identical, and the interval corresponding pixel number of each gray level is so:

Mean = \frac{M \times N}{16};

The pixel number of II. still different gray level correspondences has nothing in common with each other, so a deviate is set

Setover = \frac{M \times N}{256},

After making that like this gray level of input picture is divided, the interval corresponding pixel number of each gray level all is in Mean ± Setover scope.

5. the contrast enhancement process of a kind of uniformly distributing image brightness according to claim 4 is characterized in that, the method that in the steps d each continuous gray level sub-range of input picture is mapped on the target sub-range is:

D1. at first add up sub-range L _i' [x _I-1+ 1, x _i] in number of greyscale levels n;

D2. as if n＜8, with sub-range L _i' [x _I-1+ 1, x _i] in n gray level be mapped to sub-range L _iIn [16 * (i-1), 16 * i-1], and the gray level after the feasible mapping is with sub-range L _i[16 * (i-1), 16 * i-1] are divided into the n+1 equal portions;

D3. if n 〉=8, then these grey scale linear ground are stretched or be compressed to sub-range L _iOn [16 * (i-1), 16 * i-1] last 16 gray levels.

6. the contrast enhancement process of a kind of uniformly distributing image brightness according to claim 5 is characterized in that, in the steps d 2 each continuous gray level sub-range of input picture is mapped to the concrete formula on the target sub-range:

L = 16 * (i - 1) + (L^{'} - x_{i - 1}) * \frac{16}{n + 1};

(L ' is the gray level of interval i in the input picture in this formula, L is the gray level of L ' mapping back target interval. formula has been realized and will be inserted in a few gray level in the sub-range of input picture on 16 gray levels of target interval, in the sub-range such as input picture 3 gray levels are arranged, so through being distributed in after the mapping on the 4th, the 8th on 16 grades of gray level intervals of target interval and the 12 gray level).

7. the contrast enhancement process of a kind of uniformly distributing image brightness according to claim 5 is characterized in that, in the steps d 3 each continuous gray level sub-range of input picture is mapped to the concrete formula on the target sub-range:

L = 16 * (i - 1) + (L^{'} - x_{i - 1}) * \frac{16}{n};

(symbol in this formula is identical with the implication of symbol in the claim 6).