Image denoising: a nonlinear robust statistical approach

Authors:
A. Ben Hamza;H. Krim
Affiliations:
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC;-
Venue:
IEEE Transactions on Signal Processing
Year:
2001

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Abstract

Nonlinear filtering techniques based on the theory of robust estimation are introduced. Some deterministic and asymptotic properties are derived. The proposed denoising methods are optimal over the Huber ε-contaminated normal neighborhood and are highly resistant to outliers. Experimental results showing a much improved performance of the proposed filters in the presence of Gaussian and heavy-tailed noise are analyzed and illustrated