Degraded Reference Image Quality Assessment
Shahrukh Athar, Zhou Wang

TL;DR
This paper introduces degraded-reference image quality assessment (DR IQA), a new paradigm leveraging intermediate degraded references for more reliable quality evaluation in multi-stage distortion scenarios.
Contribution
It establishes the first large-scale DR IQA database, proposes novel models, and analyzes distortion behaviors, advancing beyond traditional FR and NR IQA methods.
Findings
DR IQA outperforms existing models in multi-distortion environments
Large-scale database enables comprehensive evaluation
New insights into multi-stage distortion behaviors
Abstract
In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve as a reference for quality assessment. As a result, full-reference (FR) and reduced-reference (RR) image quality assessment (IQA) methods are generally infeasible. Although no-reference (NR) methods are readily applicable, their performance is often not reliable. On the other hand, intermediate references of degraded quality are often available, e.g., at the input of video transcoders, but how to make the best use of them in proper ways has not been deeply investigated. Here we make one of the first attempts to establish a new paradigm named degraded-reference IQA (DR IQA). Specifically, we lay out the architectures of DR IQA and introduce a…
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Taxonomy
TopicsImage and Video Quality Assessment · Image Enhancement Techniques · Advanced Image Processing Techniques
