
Characterization of a high dynamic range (HDR) display’s performance can be largely defined by its contrast and peak luminance. Prior work has studied this question for virtual reality (VR) using a haploscopic HDR setup, but it is not obvious if those results are transferrable to a more traditional viewing setting, such as direct view. In this work, we conducted a study to measure user preference for different contrast and peak luminance parameters in this scenario, and develop a perceptual just-objectionable-difference (JOD) scale to quantify preference scores. This is accomplished by studying contrast and peak luminance conditions across several orders of magnitude, shown on a professional HDR display with peak luminance of 1,000 nits and 1,000,000:1 contrast. The data is used to develop a computational model that can drive display design and future standardization of the definition of HDR, in terms of human preference.

The existing tone mapping operators (TMOs), compress either the high dynamic range (HDR) image luminance or RGB channels and assume uniform adaptation conditions, contrary to human vision that adapts colorfulness under varying adaptation luminance conditions. One of the challenges in tone mapping is maintaining perceptual consistency of both lightness and colorfulness under varying adaptation luminance. Unlike traditional approaches, this work proposes CIECAM16 lightness based, spatially adaptive tone mapping and allows colorfulness according to local adaptation luminance. Furthermore, it uses spatial white point instead of a global one aligning the human perceptual phenomenon. The paper further analyzes the performance of the proposed TMO across various spatial conditions, demonstrating that it preserves local contrast and maintains detail in both highlight and shadow regions while adaptively regulating colorfulness under various adaptation conditions. Hence, this adaptive approach for HDR to standard dynamic range (SDR) mapping offers perceptually faithful representation.

A significant challenge in tone mapping is to preserve the perceptual quality of high dynamic range (HDR) images when mapping them to standard dynamic range (SDR) displays. Most of the tone mapping operators (TMOs) compress the dynamic range without considering the surround viewing conditions such as average, dim and dark, leading to the unsatisfactory perceptual quality of the tone mapped images. To address this issue, this work focuses on utilizing CIECAM16 brightness, colorfulness, and hue perceptual correlates. The proposed model compresses the perceptual brightness and transforms the colors from HDR images using CIECAM16 color adaptations under display conditions. The brightness compression parameter was modeled via a psychophysical experiment. The proposed model was evaluated using two psychophysical experimental datasets (Rochester Institute of Technology (RIT) and Zhejiang University (ZJU) datasets).