Abstract
Aiming at the deficiency of losing texture information in image filtering process, an image filtering algorithm based on uncorrelated dictionary learning is proposed. Firstly, the noisy image is divided into overlapping image blocks, and the image blocks are randomly extracted. The uncorrelated redundant dictionary is obtained by using uncorrelated dictionary learning technology. Finally, the sparse representation coefficients of each image block under the redundant dictionary are obtained by sparse coding algorithm, and the original image is restored by using the sparse representation coefficients. The experimental results show that the irrelevant redundant dictionary has a strong ability to express the texture information of the image. It can keep the details and texture information of the image better and improve the visual effect.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
