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http://dx.doi.org/10.5303/JKAS.2013.46.5.191

DETECTION AND RESTORATION OF NON-RADIAL VARIATION OVER FULL-DISK SOLAR IMAGES  

Yang, Yunfei (Yunnan Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology)
Lin, Jiaben (Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences)
Feng, Song (Yunnan Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology)
Deng, Hui (Yunnan Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology)
Wang, Feng (Yunnan Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology)
Ji, Kaifan (Yunnan Key Laboratory of Computer Technology Application, Faculty of Information Engineering and Automation, Kunming University of Science and Technology)
Publication Information
Journal of The Korean Astronomical Society / v.46, no.5, 2013 , pp. 191-200 More about this Journal
Abstract
Full-disk solar images are provided by many solar telescopes around the world. However, the observed images show Non-Radial Variation (NRV) over the disk. In this paper, we propose algorithms for detecting distortions and restoring these images. For detecting NRV, the cross-correlation coefficients matrix of radial profiles is calculated and the minimum value in the matrix is defined as the Index of Non-radial Variation (INV). This index has been utilized to evaluate the H images of GONG, and systemic variations of different instruments are obtained. For obtaining the NRV's image, a Multi-level Morphological Filter (MMF) is designed to eliminate structures produced by solar activities over the solar surface. Comparing with the median filter, the proposed filter is a better choice. The experimental results show that the effect of our automatic detection and restoration methods is significant for getting a flat and high contrast full-disk image. For investigating the effect of our method on solar features, structural similarity (SSIM) index is utilized. The high SSIM indices (close to 1) of solar features show that the details of the structures remain after NRV restoring.
Keywords
techniques: image processing; methods: data analysis; Sun: general;
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