A Method of Image Restoration Based on Sparse Regularization
Shu Zhen Wang, Zi Jian Zou, Li Li, Xiao Ping Zhang · Applied Mechanics and Materials · 2012
Blind deconvolution is the restoration of original image from a blurred one when the blur kernel is unknown. While recent algorithms have afforded dramatic progress, the results are still far from perfect in terms of efficiency and stability. In order to gain a stable, unique and effective solution, this paper uses a scale invariant and sparse regularization function to exert regularization constraints on the original image and PSF simultaneously. An experiment is conducted to verify that our image blind recovery algorithm is robust and has stable convergence.