Nonlinear filtering by threshold decomposition

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 ne w class of filters known as linear and order-statistic (LOS) filters result from the intersection of the class of TD and L1-filters. Performance compa rison among several filters are then presented. It was found that TD is com patible with L1, LOS, and linear filters in suppressing Gaussian noise, and is superior in suppressing salt-and-pepper noise. LOS filters, however, pr ovide a better compromise in performance and complexity.