Secured Image Compression Using Gradient Decent Based ANN Learning

It is well known that the classic image compression techniques such as JPEG and MPEG have serious limitations at high compression rate; the decompressed image gets really indistinguishable. Recent image compression techniques like Genetic algorithm based ANN could not perform well at high compressed rate and finally it leads to poor convergence rate and quality of the image is not good. In this paper, we investigate the performance of ANN with Gradient Decent in the application of image compression for obtaining optimal set of weights. Direct method of compression has been applied with neural network to get the additive advantage for security of compressed data and also this method can be applied for different formats of the image. The experiments reveal that the standard BP with proper parameters provide good generalize capability for compression and is much faster compared to earlier work in the literature, based on cumulative distribution function.