Stereo matching method based on disparity map pixel classification correction optimization

Abstract

The invention relates to the technical field of stereo vision, in particular to a stereo matching method. The method solves the problem that the accuracy of disparity correction optimization of the existing stereo matching method is insufficient. The stereo matching method based on disparity map pixel classification correction optimization comprises the following steps that (I) cost aggregation is conducted by taking a left view and a right view as references and based on a method combining a gray scale difference with a gradient, and a left disparity map and a right disparity map are obtained and subjected to left and right consistency detection to generate an initial reliable disparity map; (II) correlation credibility detection and weak texture area detection are conducted, and a pixel is classified into stable matching pixel points, unstable matching pixel points, occlusion area pixel points and weak texture area pixel points; (III) the unstable matching points are corrected by an adaptive weight algorithm based on improvement, and the occlusion area points and the weak texture area points are corrected by a mismatching pixel correction method; and (IV) the corrected disparity maps are optimized by an algorithm based on division, and dense disparity maps are obtained.

Description

technical field [0001] The invention relates to the technical field of stereo vision, in particular to a stereo matching method based on disparity map pixel classification, correction and optimization. Background technique [0002] Stereo matching is a hot and difficult point in the field of machine vision research, and has a wide range of applications and prospects in the field of stereo vision. Stereo matching is a process of obtaining the parallax map of the scene by establishing a one-to-one correspondence between the stereo images of the same scene in three-dimensional space under different viewpoints. [0003] The difficulty of stereo matching is mainly to eliminate the ambiguity and ambiguity of the matched images. Ambiguity and fuzziness are caused by noise in the acquisition of the image as well as dramatic changes in the scene itself, weak textures, and regions of repeated textures. In order to deal with these morbid problems, stereo matching algorithms adopt dif...

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Problems solved by technology

[0005] In order to solve the problem of inaccurate parallax correction optimization existing in the existing stereo matching method, the present invention provides a stereo matching method based on disparity map pixel classification correction optimization

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