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 :
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