Information Content Weighting for Perceptual Image Quality Assessment

• Published in: IEEE transactions on image processing Vol. 20; no. 5; pp. 1185 - 1198
• Main Authors: Wang, Zhou, Li, Qiang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2011; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Assessments; Biomimetics; Computational modeling; Distortion; Distortion measurement; Gaussian scale mixture (GSM); Humans; Image Enhancement - methods; Image quality; image quality assessment (IQA); information content measure; Information Storage and Retrieval - methods; Mathematical models; peak signal-to-noise-ratio (PSNR); pooling; Reproducibility of Results; Sensitivity and Specificity; Signal to noise ratio; statistical image modeling; structural similarity (SSIM); Studies; Transforms; Visualization; Weight measurement; Weighting

Many state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage structure: local quality/distortion measurement followed by pooling. While significant progress has been made in measuring local image quality/distortion, the pooling stage is often done in ad-hoc way...