80‐2: Spatiochromatic Model for Image‐Quality Prediction of High‐Dynamic‐Range and Wide‐Color‐Gamut Content

Abstract

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 ICTCP 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.