In this paper, a new optimised method of coding stereoscopic image sequences is presented and compared with already known methods. Two basic methods of coding a stereoscopic image sequence are the compatible and joint. The first one uses MPEG for coding the left channel and takes advantage of the spatial disparity redundancy between the two sequences for coding the right channel. The second one employs MPEG for coding the left channel but takes advantage of both temporal redundancy among the right channel frames and spatial redundancy between the corresponding frames of the two channels. The proposed method, which is called IMDE, estimates the P and B type of frames of the right channel by an interpolative scheme that takes in to account both the temporal and disparity characteristics. Investigating the effectiveness of the joint motion and disparity vectors estimation as well as the choice of the weighting factors that participate in the proposed interpolative scheme optimises the whole framework.
A new optimised technique for coding stereoscopic image sequences is presented and compared with already known methods. The proposed technique, called enhanced interpolated motion and disparity estimation (EIMDE), is based on the joint method, which encodes the frames of the right image sequence by exploiting both the temporal redundancy of the same sequence and the disparity redundancy with the left image sequence. In the proposed method, a variable block size scheme has been employed for motion and disparity estimation. The block size is controlled by quad-tree decomposition of the processed frame based on a rate-distortion splitting criterion. For the prediction of a macroblock, optimised motion and disparity vectors are jointly estimated and the participating proportion of each similarity is suitably searched. In this way, the energy of the resulted residual frame is minimised and the whole framework is optimised. Finally, the residual frame is decomposed by a discrete wavelet transform and is further compressed by morphological encoding the resulting coefficients. The proposed coder has been experimentally evaluated on real image sequences, where it produced good performance over other known methods.
This paper presents a stereoscopic image coder based on the MRF model and MAP estimation of the disparity field. The MRF model minimizes the noise of disparity compensation, because it takes into account the residual energy, smoothness constraints on the disparity field, and the occlusion field. Disparity compensation is formulated as an MAP-MRF problem in the spatial domain, where the MRF field consists of the disparity vector and occlusion fields. The occlusion field is partitioned into three regions by an initial double-threshold setting. The MAP search is conducted in a block-based sense on one or two of the three regions, providing faster execution. The reference and residual images are decomposed by a discrete wavelet transform and the transform coefficients are encoded by employing the morphological representation of wavelet coefficients algorithm. As a result of the morphological encoding, the reference and residual images together with the disparity vector field are transmitted in partitions, lowering total entropy. The experimental evaluation of the proposed scheme on synthetic and real images shows beneficial performance over other stereoscopic coders in the literature.
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