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Range image quality assessment by structural similarity
W. Malpica and A.C. Bovik
IEEE International Conference on Acoustics, Speech and Signal Processing
Abstract
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
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