Anisotropic Median Filtering for Stereo Disparity Map Refinement

Nils Einecke, Julian Eggert


In this paper we present a novel method for refining stereo disparity maps that is inspired by both simple median filtering and edge-preserving anisotropic filtering. We argue that a combination of these two techniques is particularly effective for reducing the fattening effect that typically occurs for block-matching stereo algorithms. Experiments show that the newly proposed post-refinement can propel simple patch-based algorithms to much higher ranks in theMiddlebury stereo benchmark. Furthermore, a comparison to state-of-the-artmethods for disparity refinement shows a similar accuracy improvement but at only a fraction of the computational effort. Hence, this approach can be used in systems with restricted computational power.


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Paper Citation

in Harvard Style

Einecke N. and Eggert J. (2013). Anisotropic Median Filtering for Stereo Disparity Map Refinement . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 189-198. DOI: 10.5220/0004200401890198

in Bibtex Style

author={Nils Einecke and Julian Eggert},
title={Anisotropic Median Filtering for Stereo Disparity Map Refinement},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},

in EndNote Style

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Anisotropic Median Filtering for Stereo Disparity Map Refinement
SN - 978-989-8565-48-8
AU - Einecke N.
AU - Eggert J.
PY - 2013
SP - 189
EP - 198
DO - 10.5220/0004200401890198