DocumentCode
3373701
Title
Lossy image compression using a modular structured neural network
Author
Watanabe, Eiji ; Mori, Katsumi
Author_Institution
Dept. of Inf. Sci. & Syst. Eng., Konan Univ., Kobe, Japan
fYear
2001
fDate
2001
Firstpage
403
Lastpage
412
Abstract
A lossy compression method for gray images is proposed on the basis of a modular structured neural network. This modular structured neural network consists of multiple neural networks with different block sizes (the numbers of input units) for the region segmentation. By the region segmentation procedure, each neural network is assigned to each region such as the edge or the flat region. From simulation results it is shown that the proposed compression method gives better compression performance compared with the conventional compression method using a single neural network
Keywords
data compression; image coding; image segmentation; neural nets; gray images; image compression; lossy compression; modular structured neural network; neural network; region segmentation; Image coding; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop
Conference_Location
North Falmouth, MA
ISSN
1089-3555
Print_ISBN
0-7803-7196-8
Type
conf
DOI
10.1109/NNSP.2001.943144
Filename
943144
Link To Document