Image Compression using a Direct Solution Method Based Neural Network

In this paper, we present a direct solution method based neural network for image compression. The proposed technique includes steps to break down large images into smaller windows and to eliminate redundant information. Furthermore, the technique employs a neural network trained by a non-iterative, direct solution method. An error backpropagation algorithm is also used to train the neural network, and both training algorithms are compared. The proposed technique has been implemented in C on the SP2. A number of experiments have been conducted. The results obtained, such as compression ratio and transfer time of the compressed images are presented in this paper.