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Proceedings Paper

Probabilistic diffusion for MAP-based correspondence estimation and image pairs coding in multiresolution
Author(s): Sang Hwa Lee; Jong-Il Park; ChoongWoong Lee
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Paper Abstract

This paper focuses on the correspondence field estimation and utilizes the estimation performance to compress stereoscopic images. This paper proposes the dense correspondence estimation with new probabilistic diffusion algorithm based on maximum a posteriori (MAP) estimation. The MAP-based correspondence field estimation including occlusion and line field is derived with reflecting the probabilistic distribution of the neighborhoods, and is applied to the compression of stereoscopic images. The proposed probabilistic diffusion algorithm considers the neighborhoods in Markov random field with their joint probability density, which is the main difference from the previous MAP-based algorithms. The joint probability density of neighborhood system is implemented by using the probabilistic plane configuration model. And, the paper derives the upper and lower bounds of the probabilistic diffusion to analyze the applied to quadtree-decomposed blocks.

Paper Details

Date Published: 30 May 2000
PDF: 11 pages
Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); doi: 10.1117/12.386658
Show Author Affiliations
Sang Hwa Lee, Seoul National Univ. (South Korea)
Jong-Il Park, Hanyang Univ. (South Korea)
ChoongWoong Lee, Seoul National Univ. (South Korea)

Published in SPIE Proceedings Vol. 4067:
Visual Communications and Image Processing 2000
King N. Ngan; Thomas Sikora; Ming-Ting Sun, Editor(s)

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