30 November 2012 Compound algorithm for restoration of heavy turbulence-degraded image for space target
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Abstract
Restoration of atmospheric turbulence degraded image is needed to be solved as soon as possible in the field of astronomical space technology. Owing to the fact that the point spread function of turbulence is unknown, changeable with time, hard to be described by mathematics models, withal, kinds of noises would be brought during the imaging processes (such as sensor noise), the image for space target is edge blurred and heavy noised, which making a single restoration algorithm to reach the requirement of restoration difficult. Focusing the fact that the image for space target which was fetched during observation by ground-based optical telescopes is heavy noisy turbulence degraded, this paper discusses the adjustment and reformation of various algorithm structures as well as the selection of various parameters, after the combination of the nonlinear filter algorithm based on noise spatial characteristics, restoration algorithm of heavy turbulence degrade image for space target based on regularization, and the statistics theory based EM restoration algorithm. In order to test the validity of the algorithm, a series of restoration experiments are performed on the heavy noisy turbulence-degraded images for space target. The experiment results show that the new compound algorithm can achieve noise restriction and detail preservation simultaneously, which is effective and practical. Withal, the definition measures and relative definition measures show that the new compound algorithm is better than the traditional algorithms.
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Liang-liang Wang, Liang-liang Wang, Ru-jie Wang, Ru-jie Wang, Ming Li, Ming Li, Zi-qian Kang, Zi-qian Kang, Xiao-qin Xu, Xiao-qin Xu, Xin Gao, Xin Gao, } "Compound algorithm for restoration of heavy turbulence-degraded image for space target", Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85581G (30 November 2012); doi: 10.1117/12.981862; https://doi.org/10.1117/12.981862
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