Algorithm of blur identification and image restoration based on parameter estimation
Xu Dong · Infrared and Laser Engineering · 2010
The point spread function(PSF) of the imaging system and the observation noise,are unknown a priori information in general applications.The identification of the PSF is a challenging and difficult problem in the world.In order to solve the problem of the identification and restoration when the degradation type is known,the algorithm of identification of the PSF and the restoration of the blurred images based on parameter estimation is proposed.First,the changing scope and the increment step length of the parameters are provided based on the original estimation.Second,the criterion in which the Frobenius norm of the difference between the estimated image with the corresponding PSF and the blurred image is minimized in every iteration step,and incorporated in order to determine the parameter of the PSF.Therefore,the PSF can be identified with the estimated parameter and the original image can be estimated via the general image restoration algorithms.In this paper,the frequency domain restoration algorithm based on the Wiener filtering is applied to restore the original images.The experimental results show that the identified result of the PSF is reliable and accurate,and the restoration effect via the identified PSF is better when the degraded image has high SNR.