  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.
