Binary Stereo Matching

TL;DR

This paper introduces Binary Stereo Matching (BSM), a fast and robust local stereo matching algorithm using binary cost computation, which achieves comparable accuracy to state-of-the-art methods with improved efficiency and robustness to radiometric differences.

Contribution

The paper presents a novel binary-based cost computation and aggregation method for stereo matching, enhancing computational efficiency and robustness over existing approaches.

Findings

BSM achieves similar accuracy to state-of-the-art methods.

BSM is faster due to binary and integer computations.

BSM is more robust under radiometric variations.

Abstract

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.