Range image quality assessment by Structural Similarity

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.

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: W. S. Malpica, Alan C. Bovik
• Keywords: ICASSP 2009, Middlebury Stereo Vision, Multi-scale Structural Similarity, Range Images, Signal Processing