Abstract
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.
Highlights
The perception of a scene with 3D realism may be accomplished by a stereo image pair which consists of two images of the same scene recorded from two slightly different perspectives
The initial disparity compensated difference (DCD) or the initial residual image is attained after disparity estimation for all the macroblocks employing block-matching algorithm (BMA)
An algorithm employing the Markov random field (MRF) model is proposed for the disparity estimation of a stereo image pair
Summary
The perception of a scene with 3D realism may be accomplished by a stereo image pair which consists of two images of the same scene recorded from two slightly different perspectives. The two images are distinguished as Left and Right images that present binocular redundancy, and for that reason can be encoded more efficiently as a pair than independently. A typical compression scenario is the encoding of one image, which is called reference and the disparity compensation of the other, which is called target. Disparity compensation procedure estimates the best prediction of the target image from the reference and results in an error image, which is called residual, together with a disparity vector field. The encoded reference and residual images together with the disparity vectors are entropy coded and transmitted. The effectiveness of the encoding algorithm, the energy of the residual image, and the smoothness of the disparity vector field affect the overall performance of the stereo coder
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