Maximum-A-Posteriori estimation for global spatial coherence recovery based on Matting Laplacian

Chen Yu Tseng*, Sheng-Jyh Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Global spatial coherence is an important criterion in the performance evaluation of many image applications, such as image segmentation, image enhancement, depth estimation, motion estimation, and many others. In this paper, we treat the recovery of spatial coherence as a Maximum-A-Posteriori (MAP) estimation problem, with a generalized spatial-coherence prior model based on Matting Laplacian (ML) matrix. Besides, to enhance computational efficiency, a cell-based Matting-Laplacian (CML) framework is further proposed. In our experiments, we demonstrate that the proposed approach can greatly improve the spatial coherence of the output results in variant applications, like the shape-from-focus process and the SIFT-flow refinement process.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages293-296
Number of pages4
DOIs
StatePublished - 1 Dec 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: 30 Sep 20123 Oct 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2012 19th IEEE International Conference on Image Processing, ICIP 2012
CountryUnited States
CityLake Buena Vista, FL
Period30/09/123/10/12

Keywords

  • depth estimation
  • image filtering
  • matting Laplacian
  • spatial coherence
  • spectral graph

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    Tseng, C. Y., & Wang, S-J. (2012). Maximum-A-Posteriori estimation for global spatial coherence recovery based on Matting Laplacian. In 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings (pp. 293-296). [6466853] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2012.6466853