A Novel Neural Network Approach for Image Compression & Decompression (International Journal of Scientific Research and Management (IJSRM), 2016)
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 network with feed forward back propagation technique can be used for image compression. In this paper, the Bipolar Coding Technique and Levenberg-Marquardt (LM) algorithms are proposed and implemented for image compression and obtained the better results as compared to Principal Component Analysis (PCA) technique. It is observed that the Bipolar Coding and LM algorithm suits the best for image compression and processing applications