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REal-time local stereo matching using guided image filtering

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5 Author(s)
Hosni, A. ; Vienna Univ. of Technol., Vienna, Austria ; Bleyer, M. ; Rhemann, C. ; Gelautz, M.
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Adaptive support weight algorithms represent the state-of the-art in local stereo matching. Their limitation is a high computational demand, which makes them unattractive for many (real-time) applications. To our knowledge, the algorithm proposed in this paper is the first local method which is both fast (real-time) and produces results comparable to global algorithms. A key insight is that the aggregation step of adaptive support weight algorithms is equivalent to smoothing the stereo cost volume with an edge-preserving filter. From this perspective, the original adaptive support weight algorithm [1] applies bilateral filtering on cost volume slices, and the reason for its poor computational behavior is that bilateral filtering is a relatively slow process. We suggest to use the recently proposed guided filter [2] to overcome this limitation. Analogously to the bilateral filter, this filter has edge preserving properties, but can be implemented in a very fast way, which makes our stereo algorithm independent of the size of the match window. The GPU implementation of our stereo algorithm can process stereo images with a resolution of 640 × 480 pixels and a disparity range of 26 pixels at 25 fps. According to the Middlebury on-line ranking, our algorithm achieves rank 14 out of over 100 submissions and is not only the best performing local stereo matching method, but also the best performing real-time method.

Published in:

Multimedia and Expo (ICME), 2011 IEEE International Conference on

Date of Conference:

11-15 July 2011