Post-processing Block Coded Images Using Artificial Neural Networks

In this paper, a technique employing artifkial neural networks for post-processing block coded images is presented. Visually important image features are extracted from the decompressed image and used as input to a feedforward neural network. The neural network learns to reconstruct the difference image between the original (uncompressed) and the decompressed image. Coding artifact reduction is achieved by adding the neural networks output to the de-compressed image. Experimental results using the new technique for post-processing quadtree coded images are presented. It is shown the new technique can sigmficantly improve the compressed image both in terms of peak signal to noise ratio (PSNR) and visual quality of the image.