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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 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