Image quality equivalence between peak luminance and chromaticity gamut

Abstract

This paper introduces a psychophysical experiment to investigate the image quality trade‐off relationship between peak luminance and the chromaticity area of the color gamut of a display device and models to predict equivalent image quality based on the experimental results. Our experimental results confirmed the hypothesis that the peak luminance required to maintain equivalent image quality tends to decrease as the color gamut area expands. At the same time, the relationship between peak luminance and color gamut strongly depends on image content. Based on the experimental results, two models are suggested. These models show good performance in terms of predicting the required luminance levels for given color gamut areas. Notably, the model built using an observer‐chosen region of interest (ROI) in an image slightly outperforms the model generated without this information.

Perceived Color Gamut in Images: From Boundary to Difference

“…The CIELAB space does not perform well in this regard because the lightness L* dimension only considers partially perceptual lightness without incorporating higher-order effects such as the Helmholtz–Kohlrausch effect. Park and Murdoch ( 2020 ) studied the trade-off between chromaticity gamut area and luminance for image quality and found more chroma can equivalently compensate for the deficiency in lightness. Recent efforts have been made to address this problem by adding the compensation component in gamut mapping (Zamir et al, 2019 ) and proposing more independent color scales (Xie and Fairchild, 2021 ).…”

P‐141: Late‐News Poster: Chroma Remapping Power Saving Technique for OLEDs

“…A simple yet naïve way to lower this power consumption is to lower the per-pixel luminance of the entire screen at the same ratio [1], but another yet better way is to minimize the user's perception of image quality changes while maintaining the relative luminance to be similar by increasing the 'saturation' in HSV of each pixel. This is the rationale behind the Helmholtz-Kohl [2] effect and its effectiveness has already been proven in various papers and many studies have been conducted along this line [3][4] [5]. Though the Helmholtz-Kohl effect is a significant discovery in the area of visual recognition for HVS, its implementation has not been industry standardized.…”