An improved block matching and prediction algorithm for multi-view video with distributed video codec

Abstract

With the advance of multi-view video codec (MVC) technology, the multimedia platform can display videos of different views. The distributed video coder (DVC) that adopts the Wynzer-Ziv (WZ) codec can shift encoding complexity to decoder under the MVC framework, denoted as multi-view DVC (MDVC), for possible low-complexity encoder applications. For side information (SI) generation, the intra- and inter-view video correlations among images in MDVC were exploited to improve the SI confidence to yield better reconstructed WZ images. We proposed a new block matching and prediction (BMP) algorithm based on Scale Invariant Feature Transform, abbreviated as SIFT-BMP, to yield more accurate SI to improve the reconstructed video quality. Simulations verified that the proposed SIFT-BMP yielded more accurate SI and higher PSNR of reconstructed images, as compared to previous methods. The PSNR improvements are 1.6~2.5 dB and higher, as compared to MCTI and H.264/AVC, for medium to high complexity videos.