Abstract
In this paper a new image compression scheme using redundant dictionary and sparse coding is proposed. Unlike other sparse coding schemes which use just one dictionary we employ multiple specific dictionaries for compressing a class of facial images. The recursive least square dictionary learning algorithm, RLS-DLA, is used to design the adaptive dictionaries, each tuned to an interval of target compression rate. The evaluation of the presented method shows that in spite of being simple and fast, it outperforms modern standard compression techniques, specially the JPEG2000, by about 0.5 to 1.2 dB. This in turn, displays the effectiveness of the scheme compared to the state-of-the-art sparse coding schemes.
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.
