Robust view synthesis under varying illumination conditions using segment-based disparity estimation

An intermediate view synthesis scheme under varying illumination conditions is proposed in this work. First, we estimate the disparity map based on cumulative color histograms. Since the cumulative histogram of an image represents the brightness ranks of pixels, the disparity estimation is robust against varying illumination conditions. More specifically, we divide each image into segments, and compute the cumulative histogram of the representative values for these segments. Then, we estimate the disparity map based on the similarity of the cumulative histograms between stereo images. Second, we transform the colors of stereo images adaptively using the disparity map. Finally, we synthesize intermediate views using the transformed stereo images and the disparity map. Simulation results demonstrate that the proposed algorithm provides better disparity maps and intermediate views under varying illumination conditions than the conventional techniques.