期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2011
卷号：2
期号：1
出版社：Ayushmaan Technologies
摘要：With the growth of multimedia and internet, compression techniques have become the thrust area in the fields of computers. Popularity of multimedia has led to the integration of various types of computer data. Multimedia combines many data types like text, graphics, still images, animation, audio and video. Image compression is a process of efficiently coding digital image to reduce the number of bits required in representing image. Its purpose is to reduce the storage space and transmission cost while maintaining good quality. Many different image compression techniques currently exist for the compression of different types of images. In this back propagation neural network training algorithm has been used. The neural network model has been trained and tested for the different types of images. Back propagation neural network algorithm helps to increase the performance of the system and to decrease the convergence time for the training of the neural network. The aim of this work is to develop an edge preserving image compressing technique using one hidden layer feed forward neural network of which the neurons are determined adaptively .The processed image block is fed as a single input pattern while single output pattern has been constructed from the original image unlike other neural network based technique where multiple image blocks are fed to train the network
关键词：Neural Network; Back Propagation; Communication technology;Feed Forward Network.6
