Perceptual Depth Compression for Stereo Applications

Abstract

Conventional depth video compression uses video codecs designed for color images. Given the performance of current encoding standards, this solution seems efficient. However, such an approach suffers from many issues stemming from discrepancies between depth and light perception. To exploit the inherent limitations of human depth perception, we propose a novel depth compression method that employs a disparity perception model. In contrast to previous methods, we account for disparity masking, and model a distinct relation between depth perception and contrast in luminance. Our solution is a natural extension to the H.264 codec and can easily be integrated into existing decoders. It significantly improves both the compression efficiency without sacrificing visual quality of depth of rendered content, and the output of depth-reconstruction algorithms or depth cameras.