Open AccessStereo Matching by Filtering-Based Disparity Propagation
Author(s) -
Xingzheng Wang,
Yushi Tian,
Haoqian Wang,
Yongbing Zhang
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0162939
Subject(s) - matching (statistics) , computer science , belief propagation , artificial intelligence , window (computing) , enhanced data rates for gsm evolution , filter (signal processing) , computer vision , stereopsis , pixel , depth map , computer stereo vision , pattern recognition (psychology) , algorithm , image (mathematics) , mathematics , statistics , decoding methods , operating system
Stereo matching is essential and fundamental in computer vision tasks. In this paper, a novel stereo matching algorithm based on disparity propagation using edge-aware filtering is proposed. By extracting disparity subsets for reliable points and customizing the cost volume, the initial disparity map is refined through filtering-based disparity propagation. Then, an edge-aware filter with low computational complexity is adopted to formulate the cost column, which makes the proposed method independent on the local window size. Experimental results demonstrate the effectiveness of the proposed scheme. Bad pixels in our output disparity map are considerably decreased. The proposed method greatly outperforms the adaptive support-weight approach and other conditional window-based local stereo matching algorithms.