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80‐2: Spatiochromatic Model for Image‐Quality Prediction of High‐Dynamic‐Range and Wide‐Color‐Gamut Content
Author(s) -
Wanat Robert,
Choudhury Anustup,
Daly Scott
Publication year - 2020
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/sdtp.14092
Subject(s) - gamut , color space , artificial intelligence , color difference , computer vision , computer science , tone mapping , high dynamic range , chromatic scale , pixel , color image , contrast (vision) , achromatic lens , image quality , lightness , range (aeronautics) , rgb color space , mathematics , image (mathematics) , dynamic range , image processing , optics , enhanced data rates for gsm evolution , engineering , physics , combinatorics , aerospace engineering
This paper presents an approach to predicting image quality by spatially filtering images before generating color difference maps with pixel‐based color difference metrics. The resulting difference maps can then be pooled across the whole image. This approach was originally developed for CIELAB color space under the name S‐CIELAB. We extend this approach to use the recently developed IC T C P color space to improve the prediction accuracy for high dynamic range and wide color gamut images. The filtering is based on the chromatic and achromatic contrast sensitivity function of the human visual system. Our results on four existing subjective image quality databases containing high dynamic range and wide color gamut images show substantial improvements at low computational cost, outperforming existing color difference metrics.