Abstract
In this paper, we propose a kernel estimation algorithm using fast best kernel retrieval (FBKR) from spectral irregularities to achieve the deblurring. In daily life, when people take a photograph by any kinds of camera equipment, image motion blur caused by camera motion often happens. Camera motion during exposure will produce a blurred image, this kind of blur is often non-liner mode. Motion blur always causes the decline of image quality, as long as the users using the hand-held photography equipment often have a similar experience. Based on this reason, reconstructing a clear image from blurred image is the main objective in this paper. Reconstruction is an ill-pose problem. In current motion blur estimation algorithms, these algorithms usually use the recursive method to estimate motion blur kernel. However, recursive process is quite time-consuming. In order to enhance time-consuming, in this paper, based on iterative phase retrieval algorithm and normalized sparsity measure, we propose a fast and effective blur kernel retrieval algorithm, which can find the best kernel in a short time. Experiments verify that our method can effectively reduce the execution time and obtain the best motion blur kernel to deblur a deblurred image and keep the quality of image deblurring.
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.