Unbalanced tree structure for frame adaptive vector quantization of image sequences

Fabio Lavagetto; Sandro Zappatore

doi:10.1117/12.19520

1 June 1990 Unbalanced tree structure for frame adaptive vector quantization of image sequences

Fabio Lavagetto, Sandro Zappatore

Proceedings Volume 1244, Image Processing Algorithms and Techniques; (1990) https://doi.org/10.1117/12.19520
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States

Abstract

In this paper a coding technique is presented which extends the methodology of vector quantization to image sequence coding. The devised algorithm basically consists of a processing stage encharged to build up the initial codebook and a codebook updating mechanism running on-line with the coding phase, to adaptively track the varying statistics of the incoming images. The codebook is organized in a binary tree structure where each leaf represents a reproduction vector. The tree grows intrinsecally unbalanced in the sense that each node splits or not according to the intensity statistics of the vector population which refers to it. By doing so, the suboptimality of tree structured vector quantization with respect to full search approaches is successfully overcome. During the coding phase the unbalanced tree is left free to plastically track the temporal variations of the incoming data statistics. This results either in some reproduction vectors to be replaced by new ones, or in some changes in the tree topology to be carried out, typically a leaf which needs to split or two leaves which, conversely, shall be cut off. An updating code stream is periodically delivered onto the channel, interlaced with coding data, to replenish the reconstruction codebook. Application to videotelephone sequences has given promising preliminary results which are presented and discussed.

Citation Download Citation

Fabio Lavagetto and Sandro Zappatore "Unbalanced tree structure for frame adaptive vector quantization of image sequences", Proc. SPIE 1244, Image Processing Algorithms and Techniques, (1 June 1990); https://doi.org/10.1117/12.19520

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available