Paper
17 April 2020 A multi-frame blind deconvolution algorithm with the consistency constraints
Author Affiliations +
Proceedings Volume 11455, Sixth Symposium on Novel Optoelectronic Detection Technology and Applications; 1145536 (2020) https://doi.org/10.1117/12.2564488
Event: Sixth Symposium on Novel Photoelectronic Detection Technology and Application, 2019, Beijing, China
Abstract
The atmospheric turbulence is a principal limitation to space objects imaging with ground-based telescopes. In order to obtain high-resolution images, post-processing is a necessary tool to overcome the effects of atmospheric turbulence. In this paper, we propose a multi-frame blind deconvolution algorithm based on the consistency constraints. We apply parametrization on the image and the PSFs, and present the minimization problem by conjugate gradient method through an alternating iterative framework. We also determine the regularization parameter adaptively at each step. Experimental results show that the proposed method can recover high quality image from turbulence degraded images effectively.
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Jin Liu, Zhilei Ren, Zhitao Chen, and Yonghui Liang "A multi-frame blind deconvolution algorithm with the consistency constraints", Proc. SPIE 11455, Sixth Symposium on Novel Optoelectronic Detection Technology and Applications, 1145536 (17 April 2020); https://doi.org/10.1117/12.2564488
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KEYWORDS
Point spread functions

Deconvolution

Image processing

Atmospheric turbulence

Turbulence

Adaptive optics

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