Abstract
To solve the image deblurring problem, most of the recently proposed nonblind deblurring approaches focus on regularizing the solutions by adding image priors, such as sparse prior, piece-wise smooth prior (total-variation prior), and so on. This paper, however, presents a new term, which can be viewed as a supplement to the data fidelity term, to improve the nonblind deblurring result. The new term is based on the relative error in frequency domain (REFD) and can suppress the ringing artifacts and preserve the image details. We analyze the properties of REFD for image deconvolution; then, a nonblind image deconvolution algorithm is proposed via introducing the REFD term into the image deconvolution model. The experimental results demonstrate the performance and efficacy of our proposed algorithm when compared to some other state-of-the-art 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.