Maximum a posteriori image restoration based on a new directional continuous edge image prior

被引：0

作者：

Chantas, G ^{[1
]}

Galatsanos, N ^{[1
]}

Likas, A ^{[1
]}

机构：

[1] Univ Ioannina, Dept Comp Sci, GR-45110 Ioannina, Greece

来源：

2005 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), VOLS 1-5 | 2005年

关键词：

image restoration; non-staionary prior; maximum a posteriori estimation; spatially adaptive regularization;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we propose a new hierarchical non stationary image prior for image restoration. This prior captures the directional edges using a continuous model and regularizes accordingly the restored images. In addition, the corresponding generative graphical model does not contain cycles, thus learning this model is easy and fast. Based on this prior image model, a maximum a posteriori (MAP) estimation algorithm is derived. Numerical experiments are provided that demonstrate the advantages of the proposed non stationary model as compared with algorithms that use stationary models.

引用

页码：949 / 952

页数：4

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