title: Salt-and-Pepper noise removal by median-type noise detectors and detail-preserving regularization.
abstract: This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.
authors.affiliation: Department of Mathematics, The Chinese University of Hong Kong, Shatin, Hong Kong. rchan@math.cuhk.edu.hk
authors.forename: Raymond H
authors.initials: RH
authors.lastname: Chan
authors.forename: Chung-Wa
authors.initials: CW
authors.lastname: Ho
authors.forename: Mila
authors.initials: M
authors.lastname: Nikolova
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D013269:Stochastic Processes