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Proceedings Paper

Stereo image compression with disparity compensation using the MRF model
Author(s): Woontack Woo; Antonio Ortega
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Paper Abstract

In coming years there will be an increasing demand for realistic 3-D display of scenes using such popular approaches as stereo or multi-view images. As the amount of information displayed increases so does the need for digital compression to ensure efficient storage and transmission of the sequences. In this paper, we introduce a new approach to stereo image compression based on the MRF model and MAP estimation. The basic strategy will be to encode the right image as a reference, then estimate the disparity between blocks in the right and left images and transmit the disparity and the error between the disparity compensated left image and the original. This approach has been used in the literature and is akin to the block matching technique used for motion compensation in video coders. The main drawback in this approach is that as the block size becomes smaller the overhead required to transmit the disparity map becomes too large. Also, simple block matching algorithms frequently fail to provide good matching results because the correspondences are locally ambiguous due to noise, occlusion, and repetition or lack of texture. The novelty in our work is that to compute the disparity map we introduce an MRF model with its corresponding energy equation. This allow us to incorporate smoothness constraints, to take into account occlusion, and to minimize the effect of noise in the disparity map estimation. Obtaining a smooth disparity is beneficial as it reduces the overhead required to transmit the disparity map. It is also useful for video coding since the robustness against noise ensures that disparity maps in successive frames will be very similar. We describe this new formulation in detail and provide compression results.

Paper Details

Date Published: 27 February 1996
PDF: 14 pages
Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); doi: 10.1117/12.233256
Show Author Affiliations
Woontack Woo, Univ. of Southern California (United States)
Antonio Ortega, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 2727:
Visual Communications and Image Processing '96
Rashid Ansari; Mark J. T. Smith, Editor(s)

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