3D stereo image color correction method based on matching and optimization

Abstract

The invention relates to a 3D stereo image color correction method based on matching and optimization. The method comprises the following steps: 1, registering a reference image and a target image byusing a scene mapping algorithm to obtain a matching image of the reference image and the target image; 2, generating a confidence coefficient diagram of the matching image and the target image by using a structural similarity algorithm; 3, correcting the target image by using a global color correction algorithm; 4, performing image initialization on pixels with relatively low confidence coefficients in the matching image by using a correction result of the global color correction algorithm according to the confidence coefficient diagram to generate an initial color correction result image; and 5, improving the color consistency of the initial color correction result image by using an optimization algorithm to obtain a finally optimized color correction result image. By adoption of the method, a good correction effect of stereo image color difference can be achieved, and the corrected target image and the reference image maintain the color consistency.

Description

technical field [0001] The invention relates to the fields of image and video processing and computer vision, in particular a method for color correction of 3D stereoscopic images based on matching and optimization. Background technique [0002] The color correction algorithm uses the reference image to correct the color of the target image with color differences, so that the color characteristics of the target image are as consistent as possible with the reference image. Image color and brightness differences are usually caused by various factors, such as intensity variation, light source location, aperture size difference, shooting angle, shooting time, etc. The color difference between left and right views in stereoscopic display will increase the burden of stereoscopic image fusion, thus causing human visual fatigue. Some color correction algorithms have been proposed to reduce color differences and improve the quality of stereoscopic images or videos and multi-view vid...

AI Technical Summary

Problems solved by technology

However, the color correction algorithm based on sparse feature matching has few feature points, so the color correction result is very dependent on the accuracy of feature point matching. Once there is a wrong match or an area without feature point matching, the wrong color correction result will appear.

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