Title :
Image Compression using Artificial Neural Networks
Author :
Rao, Pachara V. ; Madhusudana, Suhas ; Nachiketh, S.S. ; Keerthi, Kusuma
Author_Institution :
ECE, Dr MGR Univ., Bangalore, India
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.
Keywords :
backpropagation; data compression; image coding; mean square error methods; neural nets; transfer functions; MSE; PSNR; artificial neural network; back propagation network; image compression; mean square error; peak-signal-to-noise ratio; transfer function; Artificial neural networks; Image coding; Machine learning; Artificial Neural Network; BP; MSE; PSNR; image compression;
Conference_Titel :
Machine Learning and Computing (ICMLC), 2010 Second International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-6006-9
Electronic_ISBN :
978-1-4244-6007-6
DOI :
10.1109/ICMLC.2010.33
