Information permeability for stereo matching

• A novel edge-aware stereo matching with constant time complexity.
• Recursive weighted summation yielding window size independency.
• Soft weighting via effective connected support regions.
• Low number of operations per pixel per disparity (6adds and 4muls) during aggregation.
• The fastest local stereo approach in literature with competitive performance.

A novel local stereo matching algorithm is introduced to address the fundamental challenge of stereo algorithms, accuracy and computational complexity dilemma. The time consuming intensity dependent aggregation procedure of local methods is improved in terms of both speed and precision. Providing connected 2D support regions, the proposed approach exploits a new paradigm, namely separable successive weighted summation (SWS) among horizontal and vertical directions enabling constant operational complexity. The weights are determined by four-neighborhood intensity similarity of pixels and utilized to model the information transfer rate, permeability, towards the corresponding direction. The same procedure is also utilized to diffuse information through overlapped pixels during occlusion handling after detecting unreliable disparity assignments. Successive weighted summation adaptively cumulates the support data based on local characteristics, enabling disparity maps to preserve object boundaries and depth discontinuities. According to the experimental results on Middlebury stereo benchmark, the proposed method is one of the most effective local stereo algorithm providing high quality disparity models by unifying constant time filtering and weighted aggregation. Hence, the proposed algorithm provides a competitive alternative for various local methods in terms of achieving precise and consistent disparity maps from stereo video within fast execution time.

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