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Method for correcting image colors through gray points

A point correction, image technology, applied in the field of computer vision and image processing, can solve the problems of not suitable for real-time color correction, poor flexibility, complex calculation, etc., to achieve the effect of fast speed, few parameters, and simple calculation

Active Publication Date: 2015-04-08
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in actual natural conditions, many images do not satisfy the basic assumption that the sum of the edge response intensities under the three color channels is equal, so the main disadvantage of this method is that the effect is poor
Another type of image color correction algorithm based on statistical learning can achieve better results, but the main disadvantages of this type of method are complex calculations, poor flexibility, and are not suitable for real-time color correction.

Method used

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  • Method for correcting image colors through gray points
  • Method for correcting image colors through gray points
  • Method for correcting image colors through gray points

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Effect test

Embodiment 1

[0018] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0019] Download the plastic-1_solux-3500+3202 image and its corresponding standard light source and standard colorless image from the currently internationally recognized image library website for verifying image color correction. The image size is 468×637×3, 48 bits The image in tif format, the standard colorless image is obtained from the image provided by the image library and corrected by the real light source. The specific calculation process is as follows figure 1 As shown, the specific process is as follows:

[0020] Step 1. Decompose the input color image into three color channel images of red, green and blue, and perform logarithmic transformation on each channel image to obtain three logarithmic color channel images; The gray values ​​of the green and blue channels are 3502, 4592, and 10672 respectively. After logarithmic transform...

Embodiment 2

[0027] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0028] Download the plastic-1_solux-3500+3202 image and its corresponding standard light source and standard colorless image from the currently internationally recognized image library website for verifying image color correction. The image size is 468×637×3, 48 bits The image in tif format, the standard colorless image is obtained from the image provided by the image library and corrected by the real light source. The specific calculation process is as follows figure 1 As shown, the specific process is as follows:

[0029] Step 1. Decompose the input color image into three color channel images of red, green and blue, and perform logarithmic transformation on each channel image to obtain three logarithmic color channel images; The gray values ​​of the green and blue channels are: 4962, 10600, and 29240, respectively. After logarithmic transf...

Embodiment 3

[0036] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0037] Download the plastic-1_solux-3500+3202 image and its corresponding standard light source and standard colorless image from the currently internationally recognized image library website for verifying image color correction. The image size is 468×637×3, 48 bits The image in tif format, the standard colorless image is obtained from the image provided by the image library and corrected by the real light source. The specific calculation process is as follows figure 1 As shown, the specific process is as follows:

[0038] Step 1. Decompose the input color image into three color channel images of red, green and blue, and perform logarithmic transformation on each channel image to obtain three logarithmic color channel images; The gray values ​​of the green and blue channels are: 7032, 5022, and 3674, respectively. After logarithmic transfor...

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Abstract

The invention belongs to the technical field of computer vision and image processing and particularly relates to a method for correcting image colors through gray points. The method comprises dividing an image into three components of red, green and blue and performing logarithm transformation on each channel; calculating the local contrast of each logarithm channel and calculating the average gray value obtained by dividing the contrast ratio relative standard deviation of all pixel points in the three channels by the pixel points in the positions to obtain a gray measurement coefficient distribution diagram; sorting all pixels of the gray measurement coefficient distribution diagram from the small gray measurement coefficient to the large gray measurement coefficient, extracting the top 50% of the pixel points of the total pixel points to serve as gray points to estimate the image light source, and performing color correction on the image by using the light source. The method has the advantages of being few in parameter, simple in calculation, rapid in speed, good in effect, capable of performing real-time processing and the like and particularly applicable to color correction of images through front ends arranged in camera preprocessing units.

Description

technical field [0001] The invention belongs to the technical field of computer vision and image processing, in particular to a color correction method for color images. Background technique [0002] In natural images, color images provide richer information than grayscale images. However, due to the limitation of imaging technology, the color of images captured by mechanical devices (such as cameras, etc.) often deviates from the real environment colors. For example, the same white object will appear reddish in red light and bluish in blue light. The color deviation of the acquired image often interferes with various image processing tasks based on color information. Therefore, in computer vision applications, it is of great significance to perform color correction on the collected images for subsequent scene processing (such as target detection, recognition, etc.). [0003] Well-known color correction algorithms include the grayscale world algorithm and the whiteboard a...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/00
CPCG06T7/90
Inventor 杨开富李永杰高绍兵李朝义
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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