Optimal multi-stage stack filtering for image restoration

Optimal multistage (MS) stack filtering under the mean absolute error (MAE) criterion is discussed, with image restoration in mind. Using the recently developed techniques, the optimal MS stack filters are designed efficiently. Compared to single-stage (SS) stack filtering, an MS filter provides an additional design flexibility by choosing the window masks at different stages to provide a good compromise between the noise removal and the image-detail preservation. To achieve a comparable performance, MS filters can select considerably smaller window masks. The relationship between the filtering complexity/memory requirement and the window size suggests that the MS stack filtering is much faster and requires much less memory than SS stack filtering. Results of image recovery experiments are reported