Image blind deblurring with half-quadratic penalty method
Liao Yong-zhon · Optics and Precision Engineering · 2015
As existing image blind deblurring algorithms have larger and more complex computing,this paper proposes a new image blind deblurring algorithm based on half-quadratic penalty method,and verifies the feasibility of the algorithm by experiments.It formulates the optimization function by using the higher-order partial derivatives of image noise and the hyper-Laplacian priors of image gradients,then uses an efficient optimization scheme that alternates between PSF and latent image estimation to solve the proposed formula.As the fast Fourier transform has been used in iterative processing,the computing time is reduced greatly,and the restoration effects are improved.An debluring experimental is performed on an image with pixel levels of 1×106 and the results demonstrate that the proposed method is more robust and more computationally efficiency than that of current blind deblurring algorithm and its computing time has been reduced by about 60%.The algorithm provides a new way for blind deblurring of video images in real time.