Bayesian image separation with natural image prior

Haichao Zhang, Yanning Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Image separation from a set of observed mixtures has important applications in many fields such as intrinsic image extraction. We investigate in this work a natural image prior based image separation algorithm. The natural image prior is modeled via a high-order Markov Random Field (MRF) and is integrated into a Bayesian framework for estimating all the component images. Due to the usage of the natural image prior, which typically leading to non-convex optimization problems, there is no closed form solution for estimating the component images. Therefore, a Markov chain Monte-Carlo based sampling algorithm is developed for solution. Based on this, a Minimum Mean Square Error (MMSE) estimation can be achieved. The proposed method exploits both the mixing observations and the prior distribution of natural images, modeled via an MRF model. Experimental results indicate that the proposed method can generate better results than state-of-the-art image separation algorithms.

源语言英语
主期刊名2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
2097-2100
页数4
DOI
出版状态已出版 - 2012
活动2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, 美国
期限: 30 9月 20123 10月 2012

出版系列

姓名Proceedings - International Conference on Image Processing, ICIP
ISSN(印刷版)1522-4880

会议

会议2012 19th IEEE International Conference on Image Processing, ICIP 2012
国家/地区美国
Lake Buena Vista, FL
时期30/09/123/10/12

指纹

探究 'Bayesian image separation with natural image prior' 的科研主题。它们共同构成独一无二的指纹。

引用此