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Range image quality assessment by Structural Similarity

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2 Author(s)
Malpica, W.S. ; Lab. for Image & Video Eng., Univ. of Texas at Austin, Austin, TX ; Bovik, A.C.

We propose a new quality metric for range images that is based on the multi-scale structural similarity (MS-SSIM) index. The new metric operates in a manner to SSIM but allows for special handling of missing data. We demonstrate its utility by reevaluating the set of stereo algorithms evaluated in the Middlebury stereo vision page http://vision.middlebury.edu/stereo/. The new algorithm which we term Range SSIM (R-SSIM) index possesses features that make it an attractive choice for assessing the quality of range images.

Published in:

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Date of Conference:

19-24 April 2009