Research On Blind Deblurring Algorithm For Motion Blurred Image And Realization

Image motion blur is a common problem in reality.The reason for the motion blur is that there is relative motion between the lens and the object during image acquisition.The purpose of image deblurring is to restore a clear image from blurred image.In the image blind deblurring,blur kernel estimation directly affects the effect of image restoration.An image blind blurring method based on sparse prior and relative total variational is proposed: A smoothing algorithm based on weighted L0 is employed to adaptively extract image main structure which does not contain the bad factors for kernel estimation that are noise,details and edges of an object whose scale is small.An approximate solution method is employed to solve L0 problem;A relative total variation algorithm is employed to overcome the inaccuracy of estimating the complex blur kernel by the regularization method of sparse prior.The iterative weighting least squares(IRLS)and numerical analysis are used to solve problem.The experimental results show that the blur kernel obtained by this algorithm has good sparseness and continuity.In the non-blind image deblurring,the regularization method of Super-Laplacian prior is employed to estimate the latent image.The experimental results show that the latent image have better structure and less artifacts based on the proposed method than it based on existing image deblurring method.The proposed method can recover the latent image well.Aiming at the blurred image with noise,based on the image non-blind deblurring algorithm of Super-Laplacian prior,the dictionary is introduced to take advantage of the local information of the image and suppress the noise.At the same time,the Super-Laplacian prior overcome the block effect brought about by the dictionary.The experimental results show that the algorithm of super-Laplacian priori with dictionary works better both in the subjective and objective criteria.The core algorithm of this image blind deblurring is obscured to the C674 x DSP.First,the code is converted to standard C code.Then,we optimize the code,including software flow optimization,internal memory optimization,compiler optimization,arithmetic optimization and so on.Finally,hardware simulation is carried out under CCS development software.The experimental results show that the DSP platform can quickly realize the image deblurring algorithm and achieve good latent image.