A 2-D filtering scheme for stereo image compression using sequential orthogonal subspace updating

Stereo image compression involves estimating the disparity vectors that rep resent the amount of binocular parallax. The mismatching problems between t he left and right images greatly impact the accuracy of the reconstructed i mage, and hence the visual effects of the reproduced 3-D image. This paper presents a new method for compensating the mismatching effects in stereo im age pairs. This 2-D filtering-based scheme uses a sequential orthogonal sub space updating (SOSU) process to project an image block onto a subset of be st-basis vectors. The basis vectors are selected one by one from the neighb oring blocks, as well as some typical edge blocks, forming an image-depende nt set of basis vectors. This leads to the optimal representation of an ima ge block with fewer coefficients. Simulation results on two different image pairs demonstrate the effectiveness of the SOSU scheme when compared to th ose of the standard least squares 2-D filtering and the hybrid disparity-co mpensated discrete cosine transform residual encoding schemes.