Image Reconstruction Using Analysis Model Prior
Joint Authors
Du, Huiqian
Han, Yu
Mei, Wenbo
Lam, Fan
Fang, Liping
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-09
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods.
Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data.
In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator.
We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior.
Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance.
Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims.
American Psychological Association (APA)
Han, Yu& Du, Huiqian& Lam, Fan& Mei, Wenbo& Fang, Liping. 2016. Image Reconstruction Using Analysis Model Prior. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1100196
Modern Language Association (MLA)
Han, Yu…[et al.]. Image Reconstruction Using Analysis Model Prior. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-15.
https://search.emarefa.net/detail/BIM-1100196
American Medical Association (AMA)
Han, Yu& Du, Huiqian& Lam, Fan& Mei, Wenbo& Fang, Liping. Image Reconstruction Using Analysis Model Prior. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1100196
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100196