Blind image deblurring with reinforced use of edges.

Blind image deblurring tries to restore a blurred image to a clear image without the blurring kernel known in advance, which is widely required in applications such as computer vision and medical image processing. With regard to this, the key issues here are to accurately estimate the blurring kernel for deconvolution of a blurred image, and avoid the ringing artifacts in the restored image, which are both related to high-quality detection of edge information in the blurred image. Though much endeavor has been made, it is still difficult to extract edge information well in blurred images and lacks investigation how edge information causes ringing artifacts. In this paper, we make a study on this and develop novel measures to optimize edge extraction and determine suitable width and weights for the extracted edges for reinforcing their use in deblurring, by which image deblurring can be improved with ringing artifacts considerably suppressed. Experimental results demonstrate our improvements over the existing methods. [ABSTRACT FROM AUTHOR]