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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.