Stereo Image Coder Based on the MRF Model for Disparity Compensation
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Stereo Image Coder Based on the MRF Model for Disparity Compensation J. N. Ellinas and M. S. Sangriotis Department of Informatics and Telecommunications, National & Kapodistrian University of Athens, Panepistimiopolis, Ilissia, 15784 Athens, Greece Received 4 November 2004; Revised 23 May 2005; Accepted 25 July 2005 Recommended for Publication by King Ngan 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. Copyright © 2006 J. N. Ellinas and M. S. Sangriotis. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
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. The stereoscopic vision has a very wide field of applications in robot vision, virtual machines, medical surgery, and so forth. Typically, the transmission or the storage of a stereo image requires twice the bandwidth or the capacity of a single image. The objective on a bandwidth-limited transmission system is to develop an efficient coding scheme that will exploit the redundancies of the two images, that is, intraimage and cross-image correlation or similarities. 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. In this work, the Left image is assigned as reference and the Right image as target. Transform coding is a method used to remove intraspatial redundancy both from reference and target images. The
cross-image redundant information is evaluated by cons
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