Image denoising using wavelet transform modulus sum

For conventional MPEG-1 video decoding, one of the major sources of noise appearing in the decoded image sequence is the blocking effect, which is incurred by the quantization errors of the image blocks of the key frames. Recently, the wavelet transform modulus maxima (WTMM) approach was proposed to significantly reduce the blocking effect of the decoded image sequence. This algorithm improves the quality of the decoded image sequence in the sense of signal-to-noise ratio as well as visual quality. Nonetheless, the WTMM deblocking algorithm is an iterative algorithm that requires a long computation time to reconstruct the processed WTMM to obtain the deblocked image. In this paper, another wavelet-based deblocking algorithm is studied. The algorithm has the advantage of the WTMM approach that it can effectively identify the edges and the smooth regions of an image irrespective the discontinuities introduced by the blocking effect. It improves over the WTMM approach in that only a simple inverse wavelet transform is required to reconstruct the processed wavelet coefficients to obtain the deblocked image sequence