Data Adaptive Median Filters for Signal and Image Denoising Using a Generalized SURE Criterion

• Published in: IEEE signal processing letters Vol. 13; no. 9; pp. 561 - 564
• Main Authors: Hsin-Cheng Huang, Lee, T.C.M.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-09-2006; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive filters; Covariance penalty; Criteria; cross-validation; Filtering; Filtration; Gaussian mixtures; generalized Stein's unbiased risk estimation (GSURE); Handles; Image denoising; Image restoration; Noise; Noise reduction; Noise robustness; Nonlinear filters; outlier modeling; robust smoothing; Signal design; Signal restoration; Simulation; Smoothing methods
• ISSN: 1070-9908; 1558-2361
• DOI: 10.1109/LSP.2006.874463

Due to its effectiveness for removing heavy-tail noise and preserving abrupt structures hidden in noisy data, median filtering has long been a popular tool for signal restoration. In practice, an important issue of applying median filtering is the choice of the span. In this letter, we develop a data adaptive criterion for choosing this span. This criterion is derived using the generalized SURE technique recently proposed by Shen and Huang. It is designed to handle outliers and heavy-tail noise, and it aims to minimize the mean-squared error between the true and restored signals. Results from simulation experiments suggest that the proposed criterion is superior to its competitors