Research On Image Blind Deblurring Method Based On Variational Partial Differential Equation

Image degradation is influenced by many factors during image acquisition,transmission and preservation.Image blur is a common representation of image degradation.Image deblurring refers to a technique of restoring an original clear image as much as possible by using the quality degradation process and prior knowledge of image.It is also widely used in medical treatment,film and television,space exploration,surveillance video and other fields.This paper studies blind image deblurring method based on variational partial differential equations.The main research contents and innovations are as follows:(1)A new blind image deblurring model is proposed by introducing the Tikhonov regularization into Chan model.Also,the corresponding numerical algorithm of the proposed model is designed by using the alternating minimization(AM)method.Experimental results are reported to show that the proposed model can not only get high quality image restoration results,but also has stronger robustness for parameters.(2)The existence of the solutions to blind deblurring model based on the Tikhonov regularization is proved.Furthermore,we design the method of constructing the initial value of blur kernel by introducing a multi-layer image pyramid strategy.(3)A two-stage blind deblurring model is proposed by introducing the second-order Total Generalized Variation(TGV)regularization term.Furthermore,the numerical algorithm for solving the model is designed by combining the alternating minimization and split Bregman algorithm.The parameter adaptive method is also adopted to reduce the freedom of parameter selection.Numerical experimental results verify the effectiveness of the proposed model and algorithm.