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Double-Level Binary Tree Bayesian compressed sensing for block sparse image

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成果类型:
期刊论文
作者:
Qian, Yongqing;Chen, Weizhen
作者机构:
[Qian, Yongqing; Chen, Weizhen] School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China
语种:
英文
关键词:
Bayesian compressed sensing;block sparse image;double-level binary tree
期刊:
Proceedings of 2017 6th International Conference on Computer Science and Network Technology, ICCSNT 2017
年:
2018
卷:
2018-January
页码:
453-457
机构署名:
本校为第一机构
院系归属:
电气与电子工程学院
摘要:
Based on the fact that some image signals possess the block sparsity in practical application environment, a novel Compressed Sensing (CS) algorithm for block sparse image is proposed in this paper. Namely, a Double-level Binary Tree (DBT) Bayesian model is proposed for the block sparse image at the same time the relationship of the root node and the leaf node of this DBT structure is defined as 'genetic characteristic'. Then, the block clustering for the block sparse image can be executed successfully and effectively by utilizing Markov Chain Monte Carlo (MCMC) method. The simulation results ...

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