Postprocessing algorithm in block-based coded images using wavelet transform and adaptive MLP

A novel postprocessing algorithm for reducing the blocking artifacts in block-based coded images is proposed using an adaptive neural network filter (NNF) in the wavelet transform domain. We use two characteristics, knowing the positions of the blocking artifacts in each band and discriminating between the horizontal and the vertical blocking artifacts using the wavelet transformed signals. At first, after performing a 3-level wavelet transform of the decompressed image, a different one-dimensional (1D) or 2D NNF is used to reduce the blocking artifacts according to the characteristic of each level. Experimental results show that the proposed algorithm produces better results than those of conventional algorithms, both subjectively and objectively.