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Proceedings Paper

Statistical learning and prior image modeling
Author(s): Cai-Feng Wang
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Paper Abstract

In order to overcome the limitations of piecewise constant phenomenon and computational burden which exist in Markov Random Field (MRF) with pair wise neighborhood and traditional learning style respectively, this paper proposes a clustering learning method from natural image database, no filters included. By this method, we get the distributive law of the blocks abstracted from natural images. Furthermore, we also do the prior image modeling according to the learned law. And the real application in image restoration illustrates its effectiveness by comparison between high order MRF prior model and pair wise MRF prior model.

Paper Details

Date Published: 12 January 2012
PDF: 5 pages
Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 835012 (12 January 2012); doi: 10.1117/12.920149
Show Author Affiliations
Cai-Feng Wang, Univ. of Science and Technology Beijing (China)


Published in SPIE Proceedings Vol. 8350:
Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies
Safaa S. Mahmoud; Zhu Zeng; Yuting Li, Editor(s)

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