Performance Analysis of Neural Network Architecture Combined with DWT for Image Compression
Neural networks are significantly used in signal and image processing techniques for pattern recognition and template matching. In this paper neural networks are used for image compression. In order to improve the performances image compression algorithm, DWT is combined with NN for achieving better MSE and increase in compression ration greater than 100%. NN architecture achieves maximum of 98% with use of four neurons in the hidden layer, with selection of LL sub band only the compression is improved by another 75%. The proposed architecture is analyzed for 20 images and MSE is found to be improved by a factor of 20%.