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Three-Component Weighted Structural Similarity Index
C. Li and A. C. Bovik
SPIE Conference on Image Quality and System Performance
Abstract
The assessment of image quality is very important for numerous image processing applications, where the goal of
image quality assessment (IQA) algorithms is to automatically assess the quality of images in a manner that is consistent
with human visual judgment. Two prominent examples, the Structural Similarity Image Metric (SSIM) and Multi-scale
Structural Similarity (MS-SSIM) operate under the assumption that human visual perception is highly adapted for
extracting structural information from a scene. Results in large human studies have shown that these quality indices
perform very well relative to other methods. However, the performance of SSIM and other IQA algorithms are less
effective when used to rate amongst blurred and noisy images. We address this defect by considering a three-component
image model, leading to the development of modified versions of SSIM and MS-SSIM, which we call three component
SSIM (3-SSIM) and three component MS-SSIM (3-MS-SSIM).
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