DocumentCode
3397015
Title
Improving vector quantization in image compression with Hilbert scan
Author
Orest, Vascan O. ; Mircea, Weingart
Author_Institution
BUIT Dept., Crescendo Int., Bucharest, Romania
fYear
2013
fDate
7-9 July 2013
Firstpage
79
Lastpage
82
Abstract
This paper presents the improvement of the reconstructed image quality when using Hilbert scan of the image sub-blocks prior to vector quantization stage. Two methods for image vector quantization have been considered: Linde-Buzo-Gray algorithm and Self-Organizing Map neural network.
Keywords
data compression; image coding; image reconstruction; self-organising feature maps; set theory; vector quantisation; Hilbert scan; Linde-Buzo-Gray algorithm; image compression; image subblocks; image vector quantization; reconstructed image quality; self-organizing map neural network; Image coding; Indexes; Neural networks; Neurons; Training; Vector quantization; Vectors; Hilbert Scan; Image Compression; LBG Algorithm; SOM Neural Network;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference on
Conference_Location
Bucharest
ISSN
2157-8672
Print_ISBN
978-1-4799-0941-4
Type
conf
DOI
10.1109/IWSSIP.2013.6623454
Filename
6623454
Link To Document