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射电天文图像重建算法研究综述
A Review of Radio Astronomical Image Reconstruction Algorithms

DOI: 10.12677/JISP.2021.101002, PP. 9-18

Keywords: 射电天文，图像重建，CLEAN算法，最大熵算法
Radio Astronomy, Image Reconstruction, The Clean Algorithm, Maximum Entropy Algorithm

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Abstract:

由于射电望远镜采样不完备，导致观测到的天文图像质量下降，影响天文与天体物理研究。为了得到质量更好的天体图像，图像重建算法成为射电天文领域具有研究价值的方向。本文综述了射电天文成像重建领域应用广泛的算法。对H？gbom CLEAN算法、Cornwell提出的多尺度CLEAN算法和最大熵算法进行具体的分析研究，并分别将其应用于射电成像的重建；通过对比这些算法在成像中的实现结果，提出领域内亟待解决的问题与挑战。
Due to the incomplete sampling of radio telescope, the quality of the observed astronomical image is reduced, which seriously affects the scientific research work. In order to obtain better celestial images, image reconstruction algorithms have become a valuable research field in radio astronomy. In this paper, we research the radio field of astronomical imaging reconstruction algorithms used widely, and then take H？gbom CLEAN algorithm, the multi-scale CLEAN algorithm and the maximum entropy algorithm detailed analysis and the imaging reconstruction was applied to the radio, finally compare the algorithm implemented in the imaging results and put forward challenges and problems to be solved within the territory.

References

[1]  Jansky, K.G. (1961) Electrical Disturbances Apparently of Extraterrestrial Origin. In: Classics in Radio Astronomy, Springer, Berlin, 1387-1398.
https://doi.org/10.1007/978-94-009-7752-5_2
[2]  Reber, G. (1940) Notes: Cosmic Static. The Astrophysical Journal, 91, 621-624.
https://doi.org/10.1086/144197
[3]  McIntosh, G. (2016) Essential Radio Astronomy. American Journal of Physics, 84, 975.
https://doi.org/10.1119/1.4964904
[4]  Hewish, A.R., Bell, S.J., Pilkington, J.D.H., et al. (1968) Observation of a Rapidly Pulsating Radio Source. Nature, 217, 709-713.
https://doi.org/10.1038/217709a0
[5]  Penzias, A.A. and Wilson, R.W. (1965) A Measurement of Excess Antenna Temperature at 4080 Mc/s. Astrophysical Journal, 142, 419-421.
https://doi.org/10.1086/148307
[6]  Ryle, M., Hewish, A. and Shakeshaft, J. (2003) The Synthesis of Large Radio Telescopes by the Use of Radio Interferometers. IRE Transactions on Antennas & Propagation, 7, 120-124.
https://doi.org/10.1109/TAP.1959.1144745
[7]  Alonso, M.A., Korotkova, O. and Wolf, E. (2006) Propagation of the Electric Correlation Matrix and the van Cittert-Zernike Theorem for Random Electromagnetic Fields. Journal of Modern Optics, 53, 969-978.
https://doi.org/10.1080/09500340500419821
[8]  Hogbom, J.A. (1974) Aperture Synthesis with a Non-Regular Distribution of Interferometer Baselines. Astronomy and Astrophysics Supplement Series, 15, 417-426.
[9]  Schwarz, U.J. (1978) Mathematical-Statistical Description of the Iterative Beam Removing Technique (Method CLEAN). Astronomy and Astrophysics, 65, 345-356.
[10]  Clark, B.G. (1980) An Efficient Implementation of the Algorithm “CLEAN”. Astronomy & Astrophysics, 89, 377-378.
[11]  邱耀辉, 刘忠, 卢汝为, 等. CLEAN算法在天文图像空域重建中的应用[J]. 天文研究与技术, 2000(2): 1-9.
[12]  Bhatnagar, S. and Cornwell, T.J. (2004) Scale Sensitive Deconvolution of Interferometric Images I. Adaptive Scale Pixel (Asp) Decomposition. Astronomy and Astrophysics, 426, 747-754.
https://doi.org/10.1051/0004-6361:20040354
[13]  Cornwell, T.J. (2008) Multiscale CLEAN Deconvolution of Radio Synthesis Images. IEEE Journal of Selected Topics in Signal Processing, 2, 793-801.
https://doi.org/10.1109/JSTSP.2008.2006388
[14]  Zhang, L., Bhatnagar, S., Rau, U., et al. (2016) Efficient Implementation of the Adaptive Scale Pixel Decomposition Algorithm. Astronomy and Astrophysics A, 128, 592-600.
https://doi.org/10.1051/0004-6361/201628596
[15]  Shore, J. and Johnson, R. (1980) Axiomatic Derivation of the Principle of Maximum Entropy and the Principle of Minimum Cross-Entropy. IEEE Transactions on Information Theory, 26, 26-37.
https://doi.org/10.1109/TIT.1980.1056144
[16]  Frieden, B.R. (1972) Restoring with Maximum Likelihood and Maximum Entropy. Journal of the Optical Society of America, 62, 511.
https://doi.org/10.1364/JOSA.62.000511
[17]  Skilling, J. and Bryan, R.K. (1984) Maximum Entropy Image Reconstruction: General Algorithm. MNRAS, 211, 111-124.
https://doi.org/10.1093/mnras/211.1.111
[18]  Cornwell, T.J. and Evans, K.F. (1985) A Simple ma35ximum Entropy Deconvolution Algorithm. Astronomy & Astrophysics, 143, 77-83.
[19]  Starck, J.L. and Pantin, E. (1996) Multiscale Maximum Entropy Image Restoration. Vistas in Astronomy, 40, 563-569.
https://doi.org/10.1016/S0083-6656(96)00042-6
[20]  Bonavito, N., et al. (1993) Maximum Entropy Restoration of Blurred and Oversaturated Hubble Space Telescope Imagery. Applied Optics, 32, 5768-5774.
https://doi.org/10.1364/AO.32.005768
[21]  Lyon, R.G., Hollis, J.M. and Dorband, J.E. (2009) A Maximum Entropy Method with a Priori Maximum Likelihood Constraints. Astrophysical Journal, 478, 658-662.
https://doi.org/10.1086/303837
[22]  Rau, U. and Cornwell, T.J. (2012) A Multi-Scale Multi-Frequency Deconvolution Algorithm for Synthesis Imaging in Radio Interferometry. Astronomy & Astrophysics A, 71, 532-549.
https://doi.org/10.1051/0004-6361/201117104
[23]  La Camera, A., Schreiber, L., Diolaiti, E., et al. (2015) A Method for Space-Variant Deblurring with Application to Adaptive Optics Imaging in Astronomy. Astronomy & Astrophysics, 579, A1.
https://doi.org/10.1051/0004-6361/201525610
[24]  张利, 徐龙, 米立功, 等. 射电天文图像的反卷积算法研究[J]. 天文学报, 2018, 59(6): 117-124.

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