Title: Blind image deblurring based on regularization method
Abstract: Aiming at the inaccuracy of estimating the complex blur kernel,which was based on the regularization method of the image normalized sparse prior,this paper introduced the image preprocessing and proposed a novel method of blind image deblurring. The method divided blind image deblurring into three procedures. Firstly,it adopted the bilateral filter and impact filter to preprocess the image. It could strengthen image edge and reduce noise,which would be good for estimating blur kernel. Then,estimated blur kernel based on the regularization method of the image normalized sparse prior. Finally,it adopted TV regularization method in non-blind deconvolution processing. Fast iterative shrinkage-thresholding algorithm solved the model of image blur kernel estimation,simultaneously fast total variation image restoration algorithm solved non-blind deconvolution mode. Experimental results show that the proposed method is fast and very robust,and can accurately estimate the blur kernel. Moreover,it can improve the restoration effect of the blur image.
Publication Year: 2014
Publication Date: 2014-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 1
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot