Image color correction method based on simulated annealing optimization algorithm

Abstract

The invention discloses an image color correction method based on a simulated annealing optimization algorithm, and belongs to the technical field of image processing and computer vision. The image color correction method includes the steps: 1) measuring RGB (red, green and blue) stimulus values of a color sample to obtain a standard value of the color sample under a standard illuminant; 2) building a color correction model and computing a sample color theoretical value; 3) adjusting the brightness of the sample color standard value; 4) computing a color difference average value serving as a target function between a converted sample color XYZ value and the sample color standard value; 5) solving a corresponding correction matrix M when the target function obtains a globally optimal solution; 6) judging whether the computed theoretical value and a sample color measuring value meet brightness constraint conditions or not, and adjusting brightness adjustment coefficient lambda according to a fixed step length and re-computing the matrix M until the brightness constraint conditions are met if the brightness constraint conditions are not met. The image color correction method has the advantages of high correction accuracy, high noise resistance and the like, and the method can adaptively adjust the brightness level before and after image correction.

Description

technical field [0001] The invention belongs to the technical field of image processing and computer vision, and more specifically relates to an image that best matches human visual experience obtained by combining theory with traditional color correction models and CIEDE2000 color difference calculation equations using simulated annealing search algorithms Color correction method. Background technique [0002] Color is one of the important parameters in the field of computer vision. With the development of computer science, the requirements for color quality are getting higher and higher in application fields such as printing, ceramic tiles, imaging, and image retrieval. However, with the current level of science and technology, the spectral sensitivity of the image sensor cannot best simulate the color perception of the human visual system, and is affected by factors such as the spectral distribution of the light source, resulting in the collected image and the real objec...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the problems of poor anti-noise performance of traditional color correction algorithms, inconsistent brightness levels before and after correction, and low correction accuracy, and provides an image color correction method based on simulated annealing optimization algorithm; the technical solution provided by the present invention, It can avoid the inconsistency between the color measurement value of some colors and the visual experience of the human eye, so that the corrected image is more in line with the visual experience of the human eye; and has the advantages of high correction accuracy and strong noise suppression performance, and can adaptively adjust the image before and after correction brightness level to keep it consistent

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