Feed Forward Backpropagation Neural Network Image Compression for Better SNR, PSNR and BPP

Artificial Neural Networks (ANNs) as the name suggest are based on network of neurons in the human brain. Neural Networks have a parallel processing network. Neural networks are make adaptations of highly interactive communications between its basic elements. They form a multilayered and multiprocessing scheme with simple logic building components which are extensively interconnected to perform specific tasks for which they are created in a simplistic order. Neural Networks are used many digital image processing applications and image compression and decompression is one of the fields where use of neural networks has been highly appreciated. Image Compression techniques are employed to reduce the size of image without reducing the quality of the image. This reduction in size saves a lot of storage space and makes image data transmission and reception faster over different channels of communication. This paper proposes as new improved lossless image compression technique which uses Huffman Coding and Artificial Neural Networks. The use of a new improved feed-forward back propagation neural network enhances the previously available Huffman Coding Technique and provides better image compression results. The system is implemented using MATLAB and the results are presented.