A multi-frame blind deconvolution algorithm with the consistency constraints
Jin Liu, Zhilei Ren, Zhitao Chen, Yonghui Liang · Sixth Symposium on Novel Optoelectronic Detection Technology and Applications · 2020
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.