Abstract
Chinese Spectral Radioheliography can generate the images of the Sun with good spatial resolutions. It employs the Aperture Synthesis principle to image the Sun with plentiful solar radio activities. However, due to the limitation of the hardware, specifically the limited number of antennas, the recorded signal is extremely sparse in practice, which results in unsatisfied solar radio image quality. In this paper, we study the image reconstruction of Chinese Spectral RadioHeliograph (CSRH) by the aid of compressed sensing (CS) technique. In our proposed method, we adopt dictionary technique to represent solar radio images sparsely. The experimental results indicate that the proposed algorithm contributes both PSNR and subjective image quality improvements of synthesis imaging of CSRH markedly.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hőgbom, J.A.: Aperture synthesis with a non-regular distribution of interferometer baselines. Astron. Astrophys. Suppl. 15, 417 (1974)
Thompson, A.R., Moran, J.M., Swenson, G.W., Wakker, B.P., Schwarz, U.J.: The Multi-Resolution CLEAN and its application to the short-spacing problem in interferometry. Astron. Astrophys. 200, 312–322 (1988)
Cornwell, T.J.: Multi-Scale Clean Deconvolution of Radio Synthesis Images. arXiv: 0806.2228
Weir, N.: A multi-channel method of maximum entropy image restoration. In: ASP Conference Series 25: Astronomical Data Analysis Software and Systems I, p. 186 (1992)
Cornwell, T.J., Evans, K.F.: A simple maximum entropy deconvolution algorithm. Astron. Astrophys. 143, 77–83 (1985)
Starck, J.L., Pantin, E., Murtagh, F.: Deconvolution in astronomy: a review. Publ. Astr. Soc. Pacific 114, 1051–1069 (2002)
Cand`es, E., Romberg, J., Tao, T.: Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inform. Theory 52, 489–509 (2006)
Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52(4), 1289–1306 (2006)
Donoho, D.L., Huo, X.: Uncertainty principles and ideal atomic decompositions. IEEE Trans. Inform. Theory 47, 2845–2862 (2011)
Elad, M., Aharon, M.: Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. Image Process. 15(12), 3736–3745 (2006)
Buades, A., Coll, B., Morel, J.M.: A review of image denoising algorithms, with a new one. Multiscale Model. Simul. 4(2), 490–530 (2005)
Yang, J., Wright, J., Huang, T.S., et al.: Image super-resolution via sparse representation. IEEE Trans. Image Process. 19(11), 2861–2873 (2010)
Zhang, J., Zhao, D.B., Gao, W.: Group-based sparse representation for image restoration. IEEE Trans. Image Process. (TIP) 23(8), 3336–3351 (2014)
Zhang, J., Zhao, D.B., Xiong, R.Q., Ma, S.W., Gao, W.: Image restoration using joint statistical modeling in a space-transform domain. IEEE Trans. Circuits Syst. Video Technol. (TCSVT) 24(6), 915–928 (2014)
Yan, Y., Wang, W., Liu,F., Geng, L., Zhang, J.: Radio imaging-spectroscopy observation of the sun in decimeteric and centimetric wavelengths. In: Solar and Astrophysical Dynamos and Magnetic Activity, Proceeding of IAU Symposium, no. 294, pp. 489–494 (2012)
Yan, Y., Zhang, J., Wang, W., Liu, F., Chen, Z., Ji, G.: The Chinese spectral Radioheliograph-CSRH. Earth Moon Planet. 104, 97–100 (2009)
Du, J., Yan, Y.H., Wang, W.: A simulation of imaging capabilities for the Chinese Spectral Radioheliograph. In: IAU Symposium, pp. 501–502 (2013)
Li, F., Cornwell, T., de Hoog, F.: The application of compressive sampling to radio astronomy I: deconvolution. Astron. Astrophys. 528(A31), 1–10 (2011)
Li, F., Brown, S., Cornwell, T., de Hoog, F.: The application of compressive sampling to radio astronomy II: faraday rotation measure synthesis. Accepted Astron. Astrophys. 531, A126 (2011)
Wenger, S., Magnor, M., Pihlström, Y., et al.: SparseRI: A compressed sensing framework for aperture synthesis imaging in radio astronomy. Publ. Astron. Soc. Pac. 122(897), 1367–1374 (2010)
Bobin, J., Starck, J.L., Ottensamer, R.: Compressed sensing in astronomy. IEEE J. Sel. Top. Sign. Process. 2(5), 718–726 (2008)
Wiaux, Y., Jacques, L., Puy, G., et al.: Compressed sensing imaging techniques for radio interferometry. Mon. Not. Roy. Astron. Soc. 395(3), 1733–1742 (2009)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)
Acknowledgment
This work was partially supported by a grant from the National Natural Science Foundation of China under Grant 61202242, 100-Talents Program of Chinese Academy of Sciences (No. Y434061V01).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Xu, L., Ma, L., Chen, Z., Yan, Y., Wu, J. (2015). Perceptual Quality Improvement for Synthesis Imaging of Chinese Spectral Radioheliograph. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9315. Springer, Cham. https://doi.org/10.1007/978-3-319-24078-7_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-24078-7_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24077-0
Online ISBN: 978-3-319-24078-7
eBook Packages: Computer ScienceComputer Science (R0)