HDR image compression and evaluation based on local adaptation using a retinal model

Abstract— The retinal adaptation process helps the human visual system to see high-dynamic-range (HDR) scenes in the real world. A simple static local adaptation method for HDR image compression based on a retinal model is presented. The proposed simple model aims at recreating the same sensations of the human visual system between the real-world scene and the range compressed image on the display device when viewed after the human visual system reaches the steady local adaptation state, respectively. In computing scene local adaptation, the use of a non-linear edge-preserving bilateral filter not only presents a better tonal rendition in compressing local contrast and preserving details but also avoids banding artifacts across high-gradient edges. Our new model relates the display adaptation with the scene adaptation based on the retinal model. In order to verify the effectiveness, a subjective evaluation is made by comparing the real scene and the display image using the paired comparison technique.