DocumentCode :
2288876
Title :
Progressive image transmission using adaptive multistage vector quantization
Author :
Chan, Chok-Ki ; Chan, Yin-Hei
Author_Institution :
Dept. of Electron. Eng., City Polytech. of Hong Kong, Kowloon, Hong Kong
fYear :
1994
fDate :
13-16 Apr 1994
Firstpage :
189
Abstract :
A new technique based on adaptive multistage vector quantization (MSVQ) using variable block sizes is proposed for progressive image transmission. The authors employ larger block sizes in the low bit rate range and the block size is gradually decreased when the bit rate is increased. Variable block size is achieved by segmenting from the largest selected block size with a quadtree data structure. The adaptive encoding scheme is also applied to increase the compression efficiency by allocating variable bit rates according to the information detail of each vector block. Classification of blocks with different information detail is achieved by recursively identifying each of the blocks into edge or shade blocks in each stage in order to obtain different classes. Experimental results shows that adaptive MSVQ achieves an excellent reconstructed image quality at rates between 0.15 and 1.0 bpp (bits per pixel)
Keywords :
adaptive systems; computational complexity; image coding; image recognition; image reconstruction; image segmentation; tree data structures; vector quantisation; video signals; visual communication; MSVQ; adaptive encoding scheme; adaptive multistage vector quantization; bit rate; classification; compression efficiency; edge blocks; information detail; progressive image transmission; quadtree data structure; reconstructed image quality; recursive identification; segmentation; shade blocks; variable bit rates; variable block sizes; vector block; Bit rate; Cities and towns; Computational efficiency; Data structures; Image communication; Image quality; Image resolution; Image segmentation; Image storage; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on
Print_ISBN :
0-7803-1865-X
Type :
conf
DOI :
10.1109/SIPNN.1994.344935
Filename :
344935
Link To Document :
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