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 :
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