Image Compression Using Adaptive Neural Network Based on Pixels Information

Abstract

The aim of this work is to create an image compression technique
using one hidden layer feed forward neural network in which the number of
the input neurons is determined adaptively according to pixels values.
The technique proposes scanning the image pixels values and takes onesample value from the occurring values ranging from 0 to 255 gray scales.The taken values are fed into the neural network as input signals instead ofthe original image pixels. This process exhibits decreasing the number of the
input neurons, the computing size, memory space and better rate of convergence of the back propagation training algorithm.
The proposed work has been demonstrated through several experiments and shows very promising results in compression rates as well as in the
reconstructed image.