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Proceedings Paper

Multiresolutional region-based segmentation scheme for stereoscopic image compression
Author(s): Sriram Sethuraman; Mel Siegel; Angel G. Jordan
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Paper Abstract

Stereoscopic image sequence transmission over existing monocular digital transmission channels, without seriously affecting the quality of one of the image streams, requires a very low bit-rate coding of the additional stream. Fixed block-size based disparity estimation schemes cannot achieve such low bit-rates without causing severe edge artifacts. Also, textureless regions lead to spurious matches which hampers the efficient coding of block disparities. In this paper, we propose a novel disparity-based segmentation approach, to achieve an efficient partition of the image into regions of more or less fixed disparity. The partitions are edge based, in order to minimize the edge artifacts after disparity compensation. The scheme leads to disparity discontinuity preserving, yet smoother and more accurate disparity fields than fixed block-size based schemes. The smoothness and the reduced number of block disparities lead to efficient coding of one image of a stereo pair given the other. The segmentation is achieved by performing a quadtree decomposition, with the disparity compensated error as the splitting criterion. The multiresolutional recursive decomposition offers a computationally efficient and non-iterative means of improving the disparity estimates while preserving the disparity discontinuities. The segmented regions can be tracked temporally to achieve very high compression ratios on a stereoscopic image stream.

Paper Details

Date Published: 17 April 1995
PDF: 10 pages
Proc. SPIE 2419, Digital Video Compression: Algorithms and Technologies 1995, (17 April 1995); doi: 10.1117/12.206365
Show Author Affiliations
Sriram Sethuraman, Carnegie Mellon Univ. (United States)
Mel Siegel, Carnegie Mellon Univ. (United States)
Angel G. Jordan, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 2419:
Digital Video Compression: Algorithms and Technologies 1995
Arturo A. Rodriguez; Robert J. Safranek; Edward J. Delp, Editor(s)

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