Matching search method for stereo image

Abstract

The invention discloses a matching search method for a stereo image, which comprises the process of performing dynamic adjustment on the search length of matching points, wherein the process judges the trend of matching error of the matching points, and finishes the matching process of current reference points if the increase trend is showed. The method determines whether the matching process continues to be executed or not by judging the variation trend of the matching error, thereby realizing the dynamic adjustment of the search length. By narrowing the search range, the unnecessary matching operation is reduced as much as possible, which not only improves matching accuracy and matching efficiency, but also ensures accurate matching of shadowed parts.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for searching matching points in a stereo image pair. Background technique [0002] When a stereo camera is used to shoot a stereo image, due to sensor defects or changes in the environment, the captured stereo image pair (that is, the left-eye image and the right-eye image) often has serious grayscale distortion and geometric distortion, thereby greatly increasing the stereoscopic image quality. The difficulty of image matching. [0003] In order to ensure the correctness of the results in any case, the conventional matching algorithm always takes a maximum disparity value d as the search length. For each point of the reference image, a search of length d is required on the image to be matched. In this way, a lot of time will be wasted on non-matching points, resulting in a waste of system resources and a reduction in matching efficiency. Content...

AI Technical Summary

Problems solved by technology

[0002] When a stereo camera is used to shoot a stereo image, due to sensor defects or changes in the environment, the captured stereo image pair (that is, the left-eye image and the right-eye image) often has serious grayscale distortion and geometric distortion, thereby greatly increasing the stereoscopic image quality. Difficulty of image matching

[0003] In order to ensure the correctness of the results in any case, the conventional matching algorithm always takes a maximum disparity value d as the search length. For each point of the reference image, a search of length d is required on the image to be matched. In this way, a lot of time will be wasted on non-matching points, resulting in a waste of system resources and a reduction in matching efficiency.

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