By Topic

Interframe coding of images using lattice vector quantization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sampson, D.G. ; Essex Univ., Colchester, UK ; Ghanbari, M.

Vector Quantization (VQ) is a well-established technique for low bitrate source coding due to its inherent theoretical superiority over the scalar quantization. In product code VQ the input vector is decomposed to different elements and separate codebooks are designed for each element. In the paper, a new variation of SVQ is presented, which vastly reduces the encoding complexity. Fast Lattice-based Spherical Vector Quantization (FLSVQ), enables the use of very fast lattice quantizing algorithms instead of the exhaustive search of all the codebook points. Fast lattice nearest neighbour algorithms have been developed by conway and Sloane (1982). In this method an extension of these algorithms is used. Then, a novel two-stage lattice vector quantization method based on FLSVQ is tested for interframe coding of images sequences and simulation results are provided to assess the performance of the proposed method

Published in:

Image Processing and its Applications, 1992., International Conference on

Date of Conference:

7-9 Apr 1992