2014/02/10 by Kang Zhang, Jiyang Li, Zhang, Kang +9
Computer Science · #Advanced Image and Video Retrieval Techniques #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Enhancement Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.1402.2020
Pattern Recognition (ICPR), 2012 21st International Conference on
arxiv created 2014/02/10 · openalex publication_date 2014/02/10 · arxiv updated 2014/02/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we propose a novel binary-based cost computation and aggregation approach for stereo matching problem. The cost volume is constructed through bitwise operations on a series of binary strings. Then this approach is combined with traditional winner-take-all strategy, resulting in a new local stereo matching algorithm called binary stereo matching (BSM). Since core algorithm of BSM is based on binary and integer computations, it has a higher computational efficiency than previous methods. Experimental results on Middlebury benchmark show that BSM has comparable performance with state-of-the-art local stereo methods in terms of both quality and speed. Furthermore, experiments on images with radiometric differences demonstrate that BSM is more robust than previous methods under these changes, which is common under real illumination.