MRF and CRF based Image Denoising and Segmentation

被引：3

作者：

Zhang, Wei ^{[1
]}

Li, Min ^{[1
]}

机构：

[1] Beihua Univ, Sch Math & Stat, Jilin 132033, Jilin, Peoples R China

来源：

2014 5TH INTERNATIONAL CONFERENCE ON DIGITAL HOME (ICDH) | 2014年

关键词：

ALGORITHMS;

D O I：

10.1109/ICDH.2014.32

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this work, we employ a pairwise Markov Random Field (MRF) and a Conditional Random Field (CRF) for bi-level image segmentation and denoising. For both tasks, the Ising pairwise model and the Iterative Conditional Mode (ICM) inference method are implemented, assuming the parameters of the unary and pairwise potentials are known. Experimental results demonstrate the effectiveness of the proposed algorithm.

引用

页码：128 / 131

页数：4

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