DocumentCode
3505473
Title
Neural concurrent subsampling and interpolation for images
Author
Kim, Jong-Ok ; Choi, Byung-Tae ; Morales, Aldo ; Ko, Sung-Jea
Author_Institution
Dept. of Electron. Eng., Korea Univ., Seoul, South Korea
Volume
2
fYear
1999
fDate
36495
Firstpage
1327
Abstract
This paper presents a new method for image subsampling and interpolation based on the feedforward neural network (FNN). The proposed technique employs a single FNN with three hidden layers for both subsampling and interpolation, providing the advantages of high speed, parallel processing capability, and good image reproduction quality. Experimental results show that the proposed technique exhibits an increased performance over conventional ones
Keywords
feedforward neural nets; image sampling; interpolation; parallel processing; experimental results; feedforward neural network; hidden layers; high speed method; image interpolation; image reproduction quality; image subsampling; neural concurrent subsampling; parallel processing; performance; Educational institutions; Feedforward neural networks; Image coding; Image quality; Image reconstruction; Image restoration; Interpolation; Neural networks; Parallel processing; Spatial resolution;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 99. Proceedings of the IEEE Region 10 Conference
Conference_Location
Cheju Island
Print_ISBN
0-7803-5739-6
Type
conf
DOI
10.1109/TENCON.1999.818674
Filename
818674
Link To Document