2-D filter-based disparity compensation using sequential orthogonal subspace updating

Abstract

This paper presents a 2-D filtering scheme for stereo image compression using sequential orthogonal subspace updating (SOSU). The basis vectors for this representation include an extended set of blocks in the support region as well as some edge blocks for providing better compensation ability for edges and boundaries of objects. The desired image block is then projected onto a selected subset of these vectors for optimal expansion. The basis vectors are selected one by one in order of importance using the Gram-Schmidt (GS) orthogonalization procedure. The proposed scheme is inspired from the least-squares (LS) based 2-D filtering scheme of Seo, Azimi-Sadjadi and Tian (see Intl. Conf. Image Processing, vol.3, p.260-3, 1997) while circumventing its limitations by enhancing the compensation ability for the mismatching problems in stereo image pairs. Simulation results demonstrate excellent performance of the proposed scheme when compared to those of the hybrid disparity-compensated discrete cosine transform (DCT) residual coding and the LS-based 2-D filtering schemes.