CN109146811A - A kind of Adaptive contrast enhancement method of color image - Google Patents
A kind of Adaptive contrast enhancement method of color image Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration using histogram techniques
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
- G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
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- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
The present invention provides a kind of Adaptive contrast enhancement methods of color image, which is characterized in that the method includes the steps: S1: image bilateral filtering denoising；S2: image brightness histogram equalization；S3: picture contrast is enhanced based on improved gamma correction；S4: image saturation amendment.The invention proposes a kind of Adaptive contrast enhancement methods of color image, in conjunction with histogram equalization and Gamma alignment technique, contrast reinforcing effect is good, the stereovision and permeability of image can be effectively improved, further, the present invention is based on the enhanced color images of contrast to carry out saturation degree amendment, can significantly improve the color saturation of color image, significantly improve the visual effect of color image.
Description
Technical field
The present invention relates to field of image processing more particularly to a kind of Adaptive contrast enhancement methods of color image.
Background technique
Contrast enhancing plays very crucial effect on improving image/video quality, is widely used in computer view
Feel, pattern-recognition and digital image processing field.It is real due to being influenced by factors such as imaging device, imaging illumination conditions
Usually there is the problems such as contrast is low, target local detail information is unobvious in border image, this will affect human eye and finely distinguishes to target
Know or machine automatic identification ability generallys use picture superposition technology in practical applications to improve the vision of image
Effect.
Method for enhancing picture contrast is broadly divided into direct Enhancement Method and indirect Enhancement Method at present, in directly enhancing side
In method, picture contrast can be directly to be defined by certain contrast index, however, these most of indexs can not be measured simultaneously
Contrast at shadow and highlight details.On the contrary, Enhancement Method attempts to enhance image by redistributing probability density indirectly
Contrast.Image intensity is redistributed in dynamic range, does not define specific contrast index.For example, histogram is equal
Weighing apparatus method is a kind of indirect Enhancement Method of classics, and since it is calculated, simple, arithmetic speed is fast and is widely used, gamma
Gamma alignment technique achievees the purpose that histogram modification by using the auto-adaptive parameter γ of variation.
The present invention provides a kind of Adaptive contrast enhancement method, can significantly improve the contrast of image, promote image
Stereovision and permeability improve the visual effect of video image.
Summary of the invention
The present invention provides a kind of Adaptive contrast enhancement method of color image, the method includes the steps:
S1: image bilateral filtering denoising；
S2: image brightness histogram equalization；
S3: picture contrast is enhanced based on improved gamma correction；
S4: image saturation amendment.
Preferably, the histogram equalization method in the step S2 comprising steps of
S21: the probability density of each brightness degree of image is calculated；
S22: probability density is adjusted with weight distribution function；
S23: the cumulative distribution of brightness of image is calculated.
Preferably, the bilateral filtering calculation formula in the step S1 are as follows:
Wherein, g (u, v) indicates that the pixel value after pixel (u, v) bilateral filtering, (p, q) are that the K of pixel (u, v) is adjacent
Pixel in domain, w (u, v, p, q) indicate weight coefficient.
Preferably, the calculation formula of the step S22 are as follows:
Wherein, α is Dynamic gene, ρmaxIndicate the maximum value in statistic histogram, ρminIt indicates in statistic histogram most
Small value.
Preferably, improved Gamma correction function indicates in the step S3 are as follows:
Wherein, lmaxIndicate the maximum brightness value of input picture, l is the brightness value of current pixel point, Cw(l) brightness l is indicated
Corresponding accumulation histogram.
Preferably, the modified formula of saturation degree is carried out to the color image after Gamma correction in the step S4 are as follows:
Wherein, the brightness value after l ' expression Gamma correction, l indicate the brightness value before Gamma correction, and R, G, B are respectively indicated
The pixel value of red R, green G, blue channel B before saturation degree is corrected, R ', G ', B ' respectively indicate red R after saturation degree is corrected,
The pixel value of green G, blue channel B.
The invention proposes a kind of Adaptive contrast enhancement methods of color image, in conjunction with histogram equalization and Gamma
Alignment technique, contrast reinforcing effect is good, can effectively improve the stereovision and permeability of image, further, the present invention is based on
The enhanced color image of contrast carries out saturation degree amendment, can significantly improve the color saturation of color image, greatly change
It has been apt to the visual effect of color image.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention without any creative labor, may be used also for those of ordinary skill in the art
To obtain other drawings based on these drawings.
Fig. 1 is a kind of Adaptive contrast enhancement method flow diagram of the color image provided in the embodiment of the present invention；
Fig. 2 is the histogram equalization processing flow chart provided in the embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
For contrast of video images caused by the factors such as imaging device, imaging illumination condition is low, image permeability is insufficient
The problem of, the invention proposes a kind of Adaptive contrast enhancement methods, as shown in Figure 1, this method may include steps of:
S1: image bilateral filtering denoising；
To prevent picture noise from amplifying, need first to be smoothed image, the present invention carries out figure using bilateral filtering
As smooth, bilateral filtering (Bilateral filter) is a kind of nonlinear filtering method, is the spatial neighbor in conjunction with image
A kind of compromise of degree and pixel value similarity, while considering spatial information (si) and grey similarity, reach the mesh for protecting side denoising
's.The benefit of two-sided filter is can to do Edge preservation, all can be relatively significantly unlike Wiener filtering or gaussian filtering noise reduction
Fuzzy edge is not obvious the protecting effect of high frequency detail.
Two-sided filter, the value of output pixel depend on the worth weighted array of neighborhood territory pixel, and calculation formula is as follows:
Wherein, g (u, v) indicates that the pixel value after pixel (u, v) bilateral filtering, (p, q) are that the K of pixel (u, v) is adjacent
Pixel in domain, w (u, v, p, q) indicate weight coefficient.
S2: image brightness histogram equalization；
When directly modifying contrast by Gamma correction, such methods are integrally handled for image, therefore very
May occur the situation that local enhancement is insufficient or local enhancement is excessive, reinforcing effect when shadow and highlight details adjusts simultaneously
It is poor.To improve this disadvantage of gamma correction, the present invention is carried out pair by combining histogram equalization and Gamma bearing calibration
Enhance than degree, reaches Adaptive contrast enhancement effect.
As shown in Fig. 2, histogram equalization method includes the following steps:
S21: the probability density of each brightness degree of image is calculated；
Specifically, RGB color image is first switched into YCbCr image, statistics with histogram is carried out to Y luminance channel, it is different bright
The probability density calculation method of degree is as follows:
Wherein, ρ (l) indicates the probability density of brightness l, nlIndicate the number of pixels of brightness l in image, N indicates image
Total number of pixels；
S22: probability density is adjusted with weight distribution function；
Preferably, probability density adjustment is carried out with weight distribution function, calculation method is as follows:
Wherein, α is Dynamic gene, ρmaxIndicate the maximum value in statistic histogram, ρminIt indicates in statistic histogram most
Small value.
S23: the cumulative distribution of brightness of image is calculated；
Specifically, first to ρw(l) it is normalized, calculation formula is as follows:
Then, it is based on normalized weighted probability density ρw(l), the cumulative distribution of brightness l is calculated:
S3: based on improved Gamma correction enhancing picture contrast；
Present invention combination histogram modification method and the enhancing of Gamma bearing calibration degree of comparing, specifically, using image
The cumulative distribution function C of brightnessw(l) as the gamma variate-value in Gamma correction, the dynamic range of expanded images brightness.
Improved Gamma correction function indicates are as follows:
Wherein, lmaxIndicate the maximum brightness value of input picture, l is the brightness value of current pixel point, Cw(l) brightness l is indicated
Corresponding accumulation histogram.This method can gradually increase low-intensity and avoid high-intensitive substantially reduce.
S4: image saturation amendment.
Preferably, enhance influence to color saturation to reduce contrast, the present invention further to image saturation into
Row amendment carries out saturation degree amendment to R, G of color image, channel B using the brightness value of Gamma correction front and back respectively.
Firstly, going back to RGB color from YCbCr color space to the Y channel image after Gamma correction.
Then, saturation degree amendment is carried out to the color image after Gamma correction, correction formula is as follows:
Wherein the brightness value after l ' expression Gamma correction, l indicate the brightness value before Gamma correction, and R, G, B are respectively indicated
The pixel value of red R, green G, blue channel B before saturation degree is corrected, R ', G ', B ' respectively indicate red R after saturation degree is corrected,
The pixel value of green G, blue channel B.
The invention proposes a kind of Adaptive contrast enhancement methods of color image, in conjunction with histogram equalization and Gamma
Alignment technique, contrast reinforcing effect is good, can effectively improve the stereovision and permeability of image, further, the present invention is based on
The enhanced color image of contrast carries out saturation degree amendment, can significantly improve the color saturation of color image, greatly change
It has been apt to the visual effect of color image.
It should be understood that above-mentioned specific embodiment of the invention is used only for exemplary illustration or explains of the invention
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (6)
1. a kind of Adaptive contrast enhancement method of color image, which is characterized in that the method includes the steps:
S1: image bilateral filtering denoising；
S2: image brightness histogram equalization；
S3: picture contrast is enhanced based on improved gamma correction；
S4: image saturation amendment.
2. Adaptive contrast enhancement method according to claim 1, which is characterized in that the histogram in the step S2
Equalization method comprising steps of
S21: the probability density of each brightness degree of image is calculated；
S22: probability density is adjusted with weight distribution function；
S23: the cumulative distribution of brightness of image is calculated.
3. Adaptive contrast enhancement method according to claim 1, which is characterized in that the bilateral filter in the step S1
Wave calculation formula are as follows:
Wherein, g (u, v) indicates the pixel value after pixel (u, v) bilateral filtering, and (p, q) is in the K neighborhood of pixel (u, v)
Pixel, w (u, v, p, q) indicate weight coefficient.
4. Adaptive contrast enhancement method according to claim 2, which is characterized in that the calculating of the step S22 is public
Formula are as follows:
Wherein, α is Dynamic gene, ρmaxIndicate the maximum value in statistic histogram, ρminIndicate the minimum value in statistic histogram.
5. Adaptive contrast enhancement method according to claim 1, which is characterized in that improved in the step S3
Gamma correction function indicates are as follows:
Wherein, lmaxIndicate the maximum brightness value of input picture, l is the brightness value of current pixel point, Cw(l) indicate that brightness l is corresponding
Accumulation histogram.
6. Adaptive contrast enhancement method according to claim 1, which is characterized in that Gamma in the step S4
Color image after correction carries out the modified formula of saturation degree are as follows:
Wherein the brightness value after l ' expression Gamma correction, l indicate the brightness value before Gamma correction, and R, G, B respectively indicate saturation
The pixel value of red R, green G, blue channel B, R ', G ', B ' respectively indicate red R, green after saturation degree amendment before degree is corrected
G, the pixel value of blue channel B.
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| CN110519485A (en) * | 2019-09-09 | 2019-11-29 | Oppo广东移动通信有限公司 | Image processing method, image processing device, storage medium and electronic equipment |
| CN111161194A (en) * | 2019-12-31 | 2020-05-15 | Tcl华星光电技术有限公司 | Image processing method |
| CN112200848A (en) * | 2020-10-30 | 2021-01-08 | 中国科学院自动化研究所 | Depth camera vision enhancement method and system under low-illumination weak-contrast complex environment |
| CN112565915A (en) * | 2020-06-04 | 2021-03-26 | 海信视像科技股份有限公司 | Display apparatus and display method |
| CN112598607A (en) * | 2021-01-06 | 2021-04-02 | 安徽大学 | Endoscope image blood vessel enhancement algorithm based on improved weighted CLAHE |
| CN113256743A (en) * | 2021-06-16 | 2021-08-13 | 图兮数字科技(北京)有限公司 | Image processing method and device, electronic equipment and readable storage medium |
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| CN114612349A (en) * | 2022-01-27 | 2022-06-10 | 西安石油大学 | Low-illumination image enhancement method based on bilateral filtering and improved histogram equalization |
| CN114627009A (en) * | 2022-03-02 | 2022-06-14 | 安徽大学 | Image enhancement method and system based on brightness correction and fusion channel prior |
| CN115345788A (en) * | 2022-07-22 | 2022-11-15 | 内蒙古工业大学 | Method and device for improving image color contrast in vision of persons with abnormal color vision |
| CN116385359A (en) * | 2023-02-28 | 2023-07-04 | 陕西智引科技有限公司 | Image enhancement method for surface defects of low-contrast magnet devices based on machine vision |
| CN116721039A (en) * | 2023-08-08 | 2023-09-08 | 中科海拓(无锡)科技有限公司 | An image preprocessing method applied in automated optical defect detection |
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| CN117078561A (en) * | 2023-10-13 | 2023-11-17 | 深圳市东视电子有限公司 | RGB-based adaptive color correction and contrast enhancement method and device |
| CN117078561B (en) * | 2023-10-13 | 2024-01-19 | 深圳市东视电子有限公司 | RGB-based adaptive color correction and contrast enhancement method and device |
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