Enhancement of block transform coded images using residual spectra adaptive postfiltering

Image block transform techniques usually introduce several types of spatial periodic distortion which are mostly noticeable at low bit rates. One way to reduce these artifacts to obtain an acceptable visual quality level is to postfilter the decoded images using nonlinear space-variant adaptive filters derived from the structural relationships and residual spectral information provided by the discrete-time Fourier transform (DTFT) of block transforms such as the discrete cosine transform (DCT) and the lapped orthogonal transform (LOT). A method for analyzing and filtering the DCT blocking noise and the LOT ringing noise for moderate and highly compressed images is described and several test cases are presented. A generalized Fourier analysis of the block transform distortion as seen in the frequency domain is discussed in conjunction with an outline of a separable adaptive postfiltering algorithm for decoded image enhancement.<>