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