U. L. Wijewardhana, M. Codreanu and M. Latva-aho, "Bayesian method for image recovery from block compressive sensing," 2016 50th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2016, pp. 379-383. doi: 10.1109/ACSSC.2016.7869064
Bayesian method for image recovery from block compressive sensing
|Author:||Wijewardhana, U. L.1; Codreanu, M.1; Latva-aho, M.1|
1Centre for Wireless Communications, Department of Communications Engineering, University of Oulu, 90014 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202003238720
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-03-23
We consider the problem of recovering an image using block compressed sensing (BCS). Traditional BCS algorithms recovers each image block independently and utilizes post-processing methods for removing the blocking artifacts. In contrast, we propose an image recovery method free of post-processing, where we utilize a lapped transform (LT) for the sparse representation of the image in order to reduce the blocking artifacts. Specifically, we derive an iterative image reconstruction method, where a small number of adjacent measurement blocks are jointly processed for recovering an image block. For this purpose, we propose a novel sparse Bayesian learning (SBL) algorithm.
Asilomar Conference on Signals, Systems & Computers
|Pages:||379 - 383|
50th Asilomar Conference on Signals, Systems, and Computers, 6 – 9 November 2016, Pacific Grove, USA
Asilomar Conference on Signals, Systems, and Computers
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research was supported by Academy of Finland and Infotech Oulu Doctoral Program.
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