University of Oulu

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

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Author: Wijewardhana, U. L.1; Codreanu, M.1; Latva-aho, M.1
Organizations: 1Centre for Wireless Communications, Department of Communications Engineering, University of Oulu, 90014 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2016
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.

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Series: Asilomar Conference on Signals, Systems & Computers
ISSN: 1058-6393
ISSN-E: 1058-6393
ISSN-L: 1058-6393
ISBN Print: 978-1-5386-3954-2
Pages: 379 - 383
DOI: 10.1109/ACSSC.2016.7869064
Host publication: 50th Asilomar Conference on Signals, Systems, and Computers, 6 – 9 November 2016, Pacific Grove, USA
Conference: 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
Funding: This research was supported by Academy of Finland and Infotech Oulu Doctoral Program.
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