DocumentCode
2653474
Title
New image compression algorithm using proposed quantization approach
Author
Moghadas, Seyed Mehdi ; Pourghasem, Hossein ; Amirfattahi, Rasoul
Author_Institution
Najafabad Branch, Dept. of Electr. Eng., Islamic Azad Univ., Najafabad, Iran
Volume
1
fYear
2011
fDate
28-29 June 2011
Firstpage
8
Lastpage
12
Abstract
A new quantization method is proposed in this paper. This method is useful for enhancement of compression quality when each kind of neural network is used to compress the image. By quantizing the image with the proposed method, the numbers of samples which must be reconstructed by neural network is reduced. This causes a remarkable increase in quality of the reconstructed image. For testing the proposed method we use autoassociative transform coding and by merging it with the proposed quantization method a new compression algorithm is obtained. Then results of compression by the merged method are compared with some previous works. Obtained results show that the proposed compression algorithm increases the compression quality of the images remarkably. Compression time and complexity in the merged method is also better than JPEG and make it suitable for the systems with low processor and hardware implementation.
Keywords
image coding; image reconstruction; neural nets; transform coding; autoassociative transform coding; compression quality; image compression algorithm; image reconstruction; neural network; quantization approach; Biological neural networks; Image coding; Image reconstruction; Neurons; PSNR; Training; Transform coding; artificial neural network; autoassociative transform coding; image compression; quantization algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Analysis and Intelligent Robotics (ICPAIR), 2011 International Conference on
Conference_Location
Putrajaya
Print_ISBN
978-1-61284-407-7
Type
conf
DOI
10.1109/ICPAIR.2011.5976903
Filename
5976903
Link To Document