Effective Reconstruction of Stereoscopic Image Pair by using Regularized Adaptive Window Matching Algorithm

In this paper, an effective method for reconstruction of stereoscopic image pair through the regularized adaptive disparity estimation is proposed. Although the conventional adaptive disparity window matching can sharply improve the PSNR of a reconstructed stereo image, but there still exist some problems of overlapping between the matching windows and disallocation of the matching windows, because the size of the matching window tend to changes adaptively in accordance with the magnitude of the feature values. In the proposed method, the problems relating to the conventional adaptive disparity estimation scheme can be solved and the predicted stereo image can be more effectively reconstructed by regularizing the extimated disparity vector with the neighboring disparity vectors. From the experimental results, it is found that the proposed algorithm show improvements the PSNR of the reconstructed right image by about 2.36${\sim}$2.76 dB, on average, compared with that of conventional algorithms.