A Perception-Guided Framework for Cross-Media HDR-to-SDR Reproduction

Abstract

High dynamic range (HDR) images often need to be rendered on standard dynamic range (SDR) displays, where naïve dynamic-range compression can cause highlight clipping, contrast distortion, and hue or saturation shifts. This paper proposes a perception-guided HDR-to-SDR framework that combines tone mapping and color correction using perceptual supervision from a cross-media appearance-matching experiment. In the experiment, color-chart patches were presented under three illuminance levels (50, 1000, and 35 000 lx), and observers adjusted their perceived appearance on a calibrated wide-gamut SDR display. The collected data showed good observer consistency, with mean $∆E_{00}$ values of 1.4 and 3.4 for intra- and inter-observer variation, respectively. Based on these data, a compact tone-compression model was developed using a shared power-law mapping parameterized by adapting-white luminance and applied locally through pixel-wise white estimation. In addition, an appearance-guided colorfulness correction was introduced to reduce colorfulness drift while preserving hue stability. Quantitative evaluation on two benchmark HDR datasets, comprising 105 images from Fairchild's HDR Photographic Survey and 457 images from LVZ-HDR, showed that the proposed method performs competitively in terms of TMQI, FSITM, and HDR-VDP-3, indicating strong performance in both fidelity and perceptual quality.