Saliency weighted quality assessment of tone-mapped images

Abstract

Different Tone-Mapping operators (TMOs) produce different Low Dynamic Range (LDR) images based on a single High Dynamic Range (HDR) image. The Tone-Mapped image Quality Index (TMQI) algorithm provides a quantitative means of assessing the quality of resultant LDR images. In this paper we test the hypothesis that TMQI predictions of human image quality can be further aligned with human judgement of image quality in considering visual attention, or regions that humans are predicted to fixate within a scene. We propose a modified version of the TMQI algorithm, a Saliency weighted Tone-Mapped Quality Index (STMQI) which demonstrates higher correlation with subjective ranking scores than the standard TMQI metric.