Title :
Nonlinear filtering by threshold decomposition
Author :
Lin, Jean-Hsang ; Ansari, Nirwan ; Li, Jinhui
Author_Institution :
Comput. Commun. Lab., Ind. Technol. Res. Inst., Hsinchu, Taiwan
fDate :
7/1/1999 12:00:00 AM
Abstract :
A new threshold decomposition architecture is introduced to implement stack filters. The architecture is also generalized to a new class of nonlinear filters known as threshold decomposition (TD) filters which are shown to be equivalent to the class of L1-filters under certain conditions. Another new class of filters known as linear and order statistic (LOS) filters result from the intersection of the class of TD and L1-filters. Performance comparisons among several filters are then presented. It was found that TD is compatible with L1, LOS, and linear filters in suppressing Gaussian noise, and is superior in suppressing salt-and-pepper noise. LOS filters, however, provide a better compromise in performance and complexity
Keywords :
Gaussian noise; image processing; interference suppression; nonlinear filters; Gaussian noise suppression; L1-filters; LOS filters; TD filters; architecture; linear and order statistic filters; nonlinear filtering; salt-and-pepper noise; stack filters; threshold decomposition filters; AWGN; Additive noise; Additive white noise; Boolean functions; Computer architecture; Digital filters; Filtering; Finite impulse response filter; Gaussian noise; Nonlinear filters;
Journal_Title :
Image Processing, IEEE Transactions on