Publication Type : Conference Paper
Publisher : ICMLC 2010 - The 2nd International Conference on Machine Learning and Computing
Source : ICMLC 2010 - The 2nd International Conference on Machine Learning and Computing, Bangalore, p.121-124 (2010)
ISBN : 9780769539775
Keywords : After-images, Artificial Neural Network, Backpropagation, Backpropagation network, Compression ratios, Digital image storage, Image compressing, Image compression, Learning systems, Mean square error, Neural networks, Peak signal-to-noise ratio, Signal to noise ratio
Year : 2010
Abstract : This paper explores the application of artificial neural networks to image compression. An image compressing algorithm based on Back Propagation (BP) network is developed after image pre-processing. By implementing the proposed scheme the influence of different transfer functions and compression ratios within the scheme is investigated. It has been demonstrated through several experiments that peak-signal-to-noise ratio (PSNR) almost remains same for all compression ratios while mean square error (MSE) varies. © 2010 IEEE.
Cite this Research Publication : P. Va Rao, Madhusudana, Sb, Nachiketh, S. Sb, and Keerthi, Kc, “Image compression using artificial neural networks”, in ICMLC 2010 - The 2nd International Conference on Machine Learning and Computing, Bangalore, 2010, pp. 121-124.