Stereo Matching Algorithm Based on a Generalized Bilateral Filter Model

Stereo matching is a kernel problem in stereo vision systems. Stereo algorithms can be roughly classified into local and global approaches. Local algorithms use Winner-Take-All strategy, simply taking disparity level that minimizes the aggregation costs. In this paper, the authors present a local stereo matching algorithm with an adaptive cost aggregation strategy based on a generalized bilateral filter model. The range weight computation in the original bilateral filter is extended by the inner and outer weighted average processes. A pixel is assigned a high range weight to the central pixel not only if the patches of the two pixels are similar but also if the neighbouring patches around the two pixels are similar.

Provided by: Academy Publisher Topic: Software Date Added: Oct 2011 Format: PDF

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