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

Author

Chen-Yu Tseng ; Sheng-Jyh Wang

Author_Institution

Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

fYear

2012

fDate

Sept. 30 2012-Oct. 3 2012

Firstpage

293

Lastpage

296

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.

Keywords

image enhancement; image segmentation; matrix algebra; maximum likelihood estimation; motion estimation; CML framework; MAP estimation; ML matrix; SIFT-flow refinement process; cell-based matting-Laplacian framework; depth estimation; global spatial coherence recovery; image enhancement; image segmentation; matting Laplacian matrix; maximum-a-posteriori estimation; motion estimation; scale invariant feature transform; shape-from-focus process; Computational efficiency; Computational modeling; Estimation; Image color analysis; Laplace equations; Spatial coherence; Vectors; depth estimation; image filtering; matting Laplacian; spatial coherence; spectral graph;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2012 19th IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1522-4880

Print_ISBN

978-1-4673-2534-9

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2012.6466853

Filename

6466853