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19 January 2009 Most apparent distortion: a dual strategy for full-reference image quality assessment
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Proceedings Volume 7242, Image Quality and System Performance VI; 72420S (2009) https://doi.org/10.1117/12.810071
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
The mainstream approach to image quality assessment has centered around accurately modeling the single most relevant strategy employed by the human visual system (HVS) when judging image quality (e.g., detecting visible differences; extracting image structure/information). In this paper, we suggest that a single strategy may not be sufficient; rather, we advocate that the HVS uses multiple strategies to determine image quality. For images containing near-threshold distortions, the image is most apparent, and thus the HVS attempts to look past the image and look for the distortions (a detection-based strategy). For images containing clearly visible distortions, the distortions are most apparent, and thus the HVS attempts to look past the distortion and look for the image's subject matter (an appearance-based strategy). Here, we present a quality assessment method (MAD: Most Apparent Distortion) which attempts to explicitly model these two separate strategies. Local luminance and contrast masking are used to estimate detection-based perceived distortion in high-quality images, whereas changes in the local statistics of spatial-frequency components are used to estimate appearance-based perceived distortion in low-quality images. We show that a combination of these two measures can perform well in predicting subjective ratings of image quality.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric C. Larson and Damon M. Chandler "Most apparent distortion: a dual strategy for full-reference image quality assessment", Proc. SPIE 7242, Image Quality and System Performance VI, 72420S (19 January 2009); https://doi.org/10.1117/12.810071
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