Abstract: In order to overcome the low operating efficiency and poor reconstruction quality in the total variation blind image restoration model of the regularization theory, an iterative algorithm of blind restoration based on alternating direction method of multipliers algorithm was proposed. The restored image and the point spread function were estimated alternatively by alternating iteration to improve the running speed and reconstruction quality through a way without updating the penalty term. The normalization and threshold constraint condition of the point spread function, and the positive definite condition of the image were added while calculating. In the numerical experimentation, the blind restoration of the images with different fuzzy types were carried out, and it was compared with other existing blind image restoration methods. The proposed algorithm could improve the quality and the resolution ratio of the image. Through objective comparison, the peak signal to noise ratio of the proposed algorithm could be increased by 1.2 dB at most,the average structural similarity was increased maximumly by 1% and the computation time was saved maximumly by about half.

Key words: blind image restoration, point spread function, alternating direction method of multipliers algorithm, structural similarity index, total variation regularization, peak signal to noise ratio