Abstract
In this paper a new two-dimensional method for blind image restoration, based on an L 1 regularization cost function is presented. A generalized gradient algorithm is proposed by using a weak derivative of the absolute value function to deal with the non-differentiable case. Unlike the double regularization (DR) approach, the proposed method uses the L 1 estimation and is suitable for blind image restoration under non-Guassian noise environments. Compared with the NAS-RIF approach, the proposed method doesn't require the image object with a known support. Experimental results show that the proposed algorithm can obtain a better image estimate with a faster speed than three conventional blind image restoration algorithms.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.