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A Stereo Matching Method Based on Adaptive Weight and Local Entropy

An adaptive weight and stereo matching technology, which is applied in image analysis, instrumentation, calculation, etc., can solve problems such as low precision and high computational complexity

Active Publication Date: 2021-01-05
KUNMING UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is to propose a stereo matching method based on adaptive weights and local entropy to solve the problems of low precision and high computational complexity of the current traditional local matching algorithm

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  • A Stereo Matching Method Based on Adaptive Weight and Local Entropy
  • A Stereo Matching Method Based on Adaptive Weight and Local Entropy
  • A Stereo Matching Method Based on Adaptive Weight and Local Entropy

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Embodiment 1

[0058] Embodiment 1: as figure 1 As shown, a stereo matching method based on adaptive weights and local entropy, first redefines the calculation of window weights according to gray similarity and spatial proximity under the framework of adaptive weight theory; then introduces in the cost function The data smoothing item and the image local entropy are used to determine its penalty coefficient; finally, the left-right consistency test and weighted median filter are used to refine the disparity for the initial disparity map obtained by cost aggregation to obtain a higher-precision disparity map;

[0059] Specific steps are as follows:

[0060] Step 1: Calculation of data items: When determining the weight value in each matching window, according to the principle of similarity and proximity under Gestalt theory, use the gray similarity and spatial similarity of the image to construct the weight value Calculation;

[0061] Step 2: Calculation of smoothing items: Based on the ass...

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Abstract

The invention relates to a stereo matching method based on a self-adaptive weight and local entropy, belonging to the technical field of binocular stereo vision. The method includes redefining the calculation of the window weight according to the gray similarity and the spatial similarity under a self-adaptive weight theory framework; introducing a data smoothing item into the cost function, and determining the penalty coefficient of the data smoothing item by applying the image local entropy; and performing parallax refinement by applying left-right consistency check and weighted median filtering on the initial parallax map obtained by cost aggregation to obtain a high-precision parallax image. The accurate parallax map can be obtained, and the parallax accuracy is improved.

Description

technical field [0001] The invention relates to a stereo matching method based on self-adaptive weight and local entropy, which belongs to the technical field of binocular stereo vision. Background technique [0002] The essence of stereo matching is to search for the positions of points in different views after imaging in the space, and thus obtain the corresponding disparity images. Generally speaking, stereo matching algorithms can be divided into local matching algorithms and global matching algorithms. In general, the local algorithm has the advantage of fast algorithm speed, but the matching accuracy is not high in occlusion, no texture and repeated texture areas; the global algorithm has the advantage of high matching accuracy, but the disadvantage is that not only the calculation speed is much faster than most local matching Algorithms, and there are often many parameters whose values ​​are difficult to determine. For the local matching algorithm, the calculation a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/33
Inventor 李文国陈田
Owner KUNMING UNIV OF SCI & TECH
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