Asymmetric Multiframe Blind Restoration for Adaptive Optics Images via Alternating Recursion

Abstract

Blind Restoration of adaptive optics images is important in the field of astronomical imaging and space object surveillance. Using multi frame blind deconvolution as main technique means for high resolution restoration, a general cost function is deduced to deconvolve Poisson noise model image under the Bayesian-MAP estimate framework. To minimize the cost function, a solution algorithm based on alternating recursion method is proposed. In addition, asymmetric iteration method is introduced into solution process to avoid converging to local minima and maintain robustness of restored image. Experimental results show that the proposed method can recover high quality image from turbulence degraded images effectively and alleviate the negative influence of noise on the restoration result.