Backward compatible HDR stereo matching: a hybrid tone-mapping-based framework

Abstract

Stereo matching under complex circumstances, such as low-textured areas and high dynamic range (HDR) scenes, is an ill-posed problem. In this paper, we introduce a stereo matching approach for real-world HDR scenes which is backward compatible to conventional stereo matchers. For this purpose, (1) we compare and evaluate the tone-mapped disparity maps to find the most suitable tone-mapping approach for the stereo matching purpose. Thereof, (2) we introduce a combining graph-cut based framework for effectively fusing the tone-mapped disparity maps obtained from different tone-mapped input image pairs. And finally, (3) we generate reference ground truth disparity maps for our evaluation using the original HDR images and a customized stereo matching method for HDR inputs. Our experiments show that, combining the most effective features of tone-mapped disparity maps, an improved version of the disparity is achieved. Not only our results reduce the low dynamic range (LDR), conventional disparity errors by the factor of 3, but also outperform the other well-known tone-mapped disparities by providing the closest results to the original HDR disparity maps.