VLSI architectures for weighted order statistic (WOS) filters

The class of median filters has been extended to include weighted order statistics (WOS) filters, to improve the flexibility of the filtering operation. The WOS filter weights each input within a sample window, and thus retains the original temporal order information. In this paper, we present efficient VLSI architectures for nonrecursive and recursive WOS filters based on (i) array (ii) stack filter and (iii) sorting network structures. All these architectures maintain a weighted rank for each sample in the sample window. As the window shifts for each new output, the weighted ranks are updated. We analyze the implementation complexity for each architecture and verify our results through physical implementations.