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Journal of Spectroscopy
Volume 2014, Article ID 468619, 7 pages
Research Article

Heliograph Imaging Based on Total Variation Constraint and Nonlocal Operator

School of Computer Science and Technology, Xidian University, Xi’an 710071, China

Received 28 October 2013; Revised 15 January 2014; Accepted 15 January 2014; Published 19 February 2014

Academic Editor: Lu Yang

Copyright © 2014 S. Z. Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Heliograph imaging is the process to reconstruct the solar image from sparse frequency domain data, and compressed sensing (CS) algorithm has shown potential power to accurately recover images from highly undersampled data. However, the available compressed sensing based models available for heliograph imaging are not able to reconstruct fine solar structures and often suffer from undesired convolutive artifacts. This paper presents an imaging model with total variation constraint and nonlocal operator based on compressed sensing theory, with particular objective to suppress convolutive artifacts and reconstruct fine structures. In particular, an efficient algorithm is presented to solve the formulated model. Finally, a set of simulations has been conducted by using both synthetic and real images, and the results demonstrate that our proposed algorithm has surprisingly lower reconstruction errors than other methods.