Article citationsMore>>

G. Qiu, T. J. Terrell and M. R. Varley, “Improved Image Compression Using Back Propagation Networks,” In: P. J. G. Lisbao and M. J. Taylor, Eds., Proceeding of the Workshop on Neural Network Applications and Tools, IEEE Computer Society Press, Washington DC, 1994, pp. 73-81.

has been cited by the following article:

• TITLE: New Approaches for Image Compression Using Neural Network

  AUTHORS: Vilas H. Gaidhane, Vijander Singh, Yogesh V. Hote, Mahendra Kumar

  KEYWORDS: Image Compression, Feed Forward Back Propagation Neural Network, Principal Component Analysis (PCA), Levenberg-Marquardt (LM) Algorithm, PSNR, MSE

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.3 No.4, November 29, 2011

  ABSTRACT: An image consists of large data and requires more space in the memory. The large data results in more transmission time from transmitter to receiver. The time consumption can be reduced by using data compression techniques. In this technique, it is possible to eliminate the redundant data contained in an image. The compressed image requires less memory space and less time to transmit in the form of information from transmitter to receiver. Artificial neural net- work with feed forward back propagation technique can be used for image compression. In this paper, the Bipolar Coding Technique is proposed and implemented for image compression and obtained the better results as compared to Principal Component Analysis (PCA) technique. However, the LM algorithm is also proposed and implemented which can acts as a powerful technique for image compression. It is observed that the Bipolar Coding and LM algorithm suits the best for image compression and processing applications.