An Adaptive Patch-Based Reconstruction Scheme for View Synthesis by Disparity Estimation Using Optical Flow

Abstract

Due to the rapid growth of technology and the dropping cost of cameras, multiview imaging applications have attracted many researchers in recent years. Free viewpoint and 3D Televisions are among these interesting applications. One of the problems that should be solved to realize such applications is rendering. In this paper, we propose an optical flow-assisted adaptive patch-based view synthesis algorithm. This patch-based scheme reduces the size and number of holes during reconstruction. The size of patch is determined in response to edge information for better reconstruction, especially near the boundaries. In the first stage of the algorithm, disparity is obtained using optical flow estimation. Then, a reconstructed version of the left and right views is generated using our adaptive patch-based algorithm. The mismatches between each view and its reconstructed version are obtained in the mismatch detection steps. This stage results in two masks as outputs, which help with the refinement of disparities and the selection of the best patches for final synthesis. Finally, the remaining holes are filled using our simple hole-filling scheme and the refined disparities. The objective and subjective performances of the proposed algorithm are compared with recent methods. The results show that the proposed algorithm achieves an improvement of 2.14 dB on average.