Artifact reduction in low bit rate wavelet coding with robust nonlinear filtering

A postprocessing algorithm for compression artifact reduction in low-bit-rate wavelet coding is proposed in this work. We first formulate the artifact reduction problem as a robust estimation problem. Under this framework, the artifact-free image is obtained by minimizing a cost function that accounts for the smoothness constraint as well as image fidelity. Unlike the traditional approach that adopts gradient descent search for optimization, a set of nonlinear filters is used to calculate the approximate global minimum. The nonlinear filtering approach reduces the number of the objective function evaluation and increases the speed of convergence. It is shown by experimental results that the proposed approach can alleviate wavelet coding artifacts efficiently with a low computational cost.