Multi-Stage Vector Quantization Based On The Self-Organization Feature Maps

J. Li; C. N. Manikopoulos

doi:10.1117/12.970114

1 November 1989 Multi-Stage Vector Quantization Based On The Self-Organization Feature Maps

J. Li, C. N. Manikopoulos

Proceedings Volume 1199, Visual Communications and Image Processing IV; (1989) https://doi.org/10.1117/12.970114
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

A neural network clustering algorithm, termed Self-Organization Feature Maps(SOFM) proposed by Kohoneni, is used to design a vector quantizer. The SOFM algorithm differs from the LBG algorithm in that the former forms a codebook adaptively but not iteratively. For every input vector,the weight between the input node and the corresponding output node is updated by encouraging a shift toward the center of gravity in the due influence region. Some important properties are discussed, demonstrated by examples, and compared with the LBG algorithm. Based on this clustering algorithm, a very practical image sequence coding scheme is proposed, which consists of two cascade neural networks. The first stage network is adapted with every frame so that the coder can quickly track the local changes in the picture. Simulation results have shown that quite robust performance can be achieved with high signal to noise ratio using the absolute value distortion measure. Additionally, the cascade scheme substantially reduces the computation complexity.

Citation Download Citation

J. Li and C. N. Manikopoulos "Multi-Stage Vector Quantization Based On The Self-Organization Feature Maps", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970114

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