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• W1520563248 abstract "This paper presents a novel computational model for quantifying the perceptual quality of color images consistently with subjective evaluations. The proposed full-reference color metric, namely, a directional statistics-based color similarity index, is designed to consistently perform well over commonly encountered chromatic and achromatic distortions. In order to accurately predict the visual quality of color images, we make use of local color descriptors extracted from three perceptual color channels: 1) hue; 2) chroma; and 3) lightness. In particular, directional statistical tools are employed to properly process hue data by considering their periodicities. Moreover, two weighting mechanisms are exploited to accurately combine locally measured comparison scores into a final score. Extensive experimentation performed on large-scale databases indicates that the proposed metric is effective across a wide range of chromatic and achromatic distortions, making it better suited for the evaluation and optimization of color image processing algorithms." @default.
• W1520563248 created "2016-06-24" @default.
• W1520563248 creator A5059152392 @default.
• W1520563248 creator A5087398451 @default.
• W1520563248 date "2015-11-01" @default.
• W1520563248 modified "2023-09-24" @default.
• W1520563248 title "Towards a Full-Reference Quality Assessment for Color Images Using Directional Statistics." @default.
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• W1520563248 doi "https://doi.org/10.1109/tip.2015.2456419" @default.
• W1520563248 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26186778" @default.
• W1520563248 hasPublicationYear "2015" @default.
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