Qpso Based Stack Filters Optimization

Stack filters are a class of slip window nonlinear digital filters that satisfy a weak superposition property known as the threshold decomposition and stacking property. They are suitable to parallel processing. Stack filters include many kinds of nonlinear filters in theory, being an important tool for nonlinear research. Beginning with stack filters's fundamental theory, optimization algorithms and their application in image processing of stack filters are studied in this paper. Experimental results show that optimal stack filters based on MAE criteria, which are found by Binary QPSO (BQPSO) algorithms preserve details of images perfectly and suppress noise passably.