Neural Network in Image Compression

Abstract

Computer images are extremely data intensive and hence require large amounts of memory for storage. As a result, the transmission of an image from one machine to another can be very time consuming. By using data compression techniques, it is possible to remove some of the redundant information contained in images, requiring less storage space and less time to transmit. Neural network can be used for the purpose of image compression. It is apparent that neural network derives its computing power through, first its massively parallel distribution structure and second, its ability to learn and therefore generalize. Generalization refers to the neural network producing reasonable outputs for inputs not encountered during training(learning).These two information processing capabilities make it possible for neural network to solve complex problem that are currently intractable.