Stereo Matching Techniques for High Dynamic Range Image Pairs

We investigate the stereo matching techniques for high dynamic range (HDR) image pairs. It is an emerging topic in computer vision and multimedia applications due to the availability of HDR image capture devices. The disparity computation will eventually take the stereo HDR input. In this work, three state-of-the-art stereo matching algorithms are modified and used to test the advantages of HDR stereo matching. By performing the HDR bit-plane slicing, it is found that only about 16 bits per channel is required for the HDR image format. We propose a 16-bit unsigned integer format to store the HDR image, which allows the available stereo matching algorithms to be adopted for disparity computation. Experiments and performance evaluation are carried out using Middlebury stereo datasets.