Abstract
For memory constrained high-order entropy coding, (i) the number of Huffman tables and (ii) the size of each Huffman table have to be appropriately reduced. Recently, we developed a Huffman table sharing and a memory allocation methods, each of which efficiently reduces either (i) or (ii) to meet the given memory constraint while keeping the increase in average bitrate as small as possible. However, given a memory constraint, the Huffman table sharing and the memory allocation methods have to be employed at the same time to achieve the better result. This paper presents several efficient schemes for combining the two methods along with simulation results.
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.
