Overlapped block disparity compensation with adaptive windows for stereo image coding

TLDR: This work shows that OBM techniques can be successfully applied to stereo image coding, and takes advantage of the smoothness properties typically found in disparity fields to further improve the performance of OBM in this particular application.

Abstract: We propose a modified overlapped block-matching (OBM) scheme for stereo image coding. OBM has been used in video coding but, to the best of our knowledge, it has not been applied to stereo image coding to date. In video coding, OBM has proven useful in reducing blocking artifacts (since multiple vectors can be used for each block), while also maintaining most of the advantages of fixed-size block matching. There are two main novelties in this work. First, we show that OBM techniques can be successfully applied to stereo image coding. Second, we take advantage of the smoothness properties typically found in disparity fields to further improve the performance of OBM in this particular application. Specifically, we note that practical OBM approaches use noniterative estimation techniques, which produce lower quality estimates than iterative methods. By introducing smoothness constraints into the noniterative DV computation, we improve the quality of the estimated disparity as compared to standard noniterative OBM approaches. In addition, we propose a disparity estimation/compensation approach using adaptive windows with variable shapes, which results in a reduction in complexity. We provide experimental results that show that our proposed hybrid OBM scheme achieves a PSNR gain (about 1.5-2 dB) as compared to a simple block-based scheme, with some slight PSNR gains (about 0.2-0.5 dB) in a reduced complexity, as compared to an approach based on standard OBM with half-pixel accuracy.