Visual attention guided quality assessment of Tone-Mapped images using scene statistics

Abstract

Measuring visual quality, as perceived by human observers, is becoming increasingly important in the many applications in which humans are the ultimate consumers of visual information. This paper assesses the visual quality in mapping of high dynamic range (HDR) images to standard dynamic range (SDR) images with 8 bits/color/pixel. In previous work, the Tone-Mapped image Quality Index (TMQI) compares the original HDR image with the rendered SDR image. TMQI quantifies distortions locally and pools them by uniform averaging, in addition to measuring naturalness of the SDR image. For SDR images, perceptual pooling strategies have improved correlation of image quality assessment (IQA) algorithms with subjective scores. The primary contributions of this paper are: (1) integrating local information-based pooling strategies in the TMQI IQA algorithm, (2) measuring image naturalness by using mean-subtracted contrast-normalized pixels, and (3) testing the proposed methods on JPEG compressed tone-mapped images and tone-mapped images for SDR displays using subjective scores.