DocumentCode
2905904
Title
Vector quantization and progressive image transmission using Kohonen self-organizing feature map
Author
Gong, Wei ; Rao, K.R. ; Manry, Michael T.
Author_Institution
Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
fYear
1991
fDate
4-6 Nov 1991
Firstpage
477
Abstract
Vector quantization is implemented using a modified Kohonen self-organizing feature map algorithm, called KVQ. To alleviate edge distortion a classification technique is applied to vector quantization. The classification technique is based on edge detection, since the human visual system is more sensitive to edges. A simple spatial domain progressive image transmission is presented, which uses separating mean KVQ. In simulation results, very good intermediate images were obtained at reasonable bit rates
Keywords
data compression; encoding; neural nets; picture processing; self-adjusting systems; visual communication; KVQ; Kohonen self-organizing feature map; algorithm; classification; edge detection; neural nets; spatial domain progressive image transmission; vector quantisation; Bit rate; Clustering algorithms; Euclidean distance; Humans; Image coding; Image communication; Image edge detection; Rate-distortion; Vector quantization; Visual system;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location
Pacific Grove, CA
ISSN
1058-6393
Print_ISBN
0-8186-2470-1
Type
conf
DOI
10.1109/ACSSC.1991.186495
Filename
186495
Link To Document