Perception-based high dynamic range video compression with optimal bit-depth transformation

High Dynamic Range (HDR) technology is able to offer high levels of immersion with a dynamic range comparable to the Human Visual System (HVS). A primary drawback of HDR is that its memory and bandwidth requirements are significantly higher than for conventional video. The challenge is thus to develop means for efficiently compressing the video to a manageable bitrate without compromising perceptual quality. In this paper, we propose an HDR compression method based on an optimized bit-depth transformation, and HVS model based wavelet transform denoising. Experimental results indicate that the proposed method outperforms previous approaches and operates in accordance with characteristics of the HVS, tested objectively using a Visible Difference Predictor (VDP).