An Improved Adaptive Support-weight Stereo Matching Algorithm with Sparse Region

LU Di; LIN Xue

doi:10.15938/j.jhust.2016.01.

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An Improved Adaptive Support-weight Stereo Matching Algorithm with Sparse Region

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- An Improved Adaptive Support-weight Stereo Matching Algorithm with Sparse Region
- Vol. 21, Issue 1, Pages: 83-88(2016)
- 作者机构：
  
  哈尔滨理工大学电气与电子工程学院,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2016.01.
  CLC： TP391.4
- Published：2016
- 稿件说明：
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LU Di, LIN Xue. An Improved Adaptive Support-weight Stereo Matching Algorithm with Sparse Region[J]. 2016, 21(1): 83-88.
DOI：

LU Di, LIN Xue. An Improved Adaptive Support-weight Stereo Matching Algorithm with Sparse Region[J]. 2016, 21(1): 83-88. DOI： 10.15938/j.jhust.2016.01..

摘要

立体匹配是根据两幅或者多幅具有一定视差的图像，获得图像之间视差图的过程．针对自适应权重立体匹配算法难以同时满足精度和速度的不足，提出一种符合人眼视觉特性的改进自适应权重稀疏区域立体匹配算法．首先对权重公式进行改进，改进后根据公式计算每个点的权重，其次对图像进行稀疏的区域匹配获得稠密视差图，然后将所得视差图进行左右一致性检测及遮挡填充，最后对视差图进行中值滤波，以去除孤立的误匹配点和噪声点．实验结果表明，改进方法比Yoon的自适应权重算法匹配效率提高了90多倍，比SSD精度提高了12．34％，能够快速的获得精确的视差图，满足系统对实用性的要求．

Abstract

Stereo matching is to obtain disparity map from two or more images whose pixels show disparity between each other. Because adaptive support-weight algorithm is difficult to meet both accuracy and speed

an improved adaptive support-weight sparse region approach based on HVS （human visual system） is proposed. First

we improve the traditional support-weight formula

and the support-weight of the points can be calculated according to the improved support-weight formula. Second

the dense disparity map is obtained by using sparse region-based matching. Third

left-right consistency check and blocking filling is performed for the obtained disparity map. Final- ly

median filter is used to remove isolated mismatching points and noise points. Experiment results show that

by using the presented method

the matching efficiency is above 90 times faster than that of the adaptive support-weight algorithm proposed rithm is verified for by Yoon

and the matching accuracy is 12. 34% higher than that of SSD

so the improved algoobtaining accurate disparity map at a fast pace and meeting the requirements of system practicability.

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Related Institution

School of Computer Science and Technology, Harbin University of Science and Technology

1School of Computer and Information Engineering, Harbin University of Commerce

2School of Computer Science and Technology, Harbin University of Science and Technology

The Higher Educational Key Laboratory for Measuring and Control Technology and Instrument of Heilongjiang Province

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