VLSI architectures for Weighted Order Statistic (WOS) filters

Chaitali Chakrabarti, Lori E. Lucke

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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 WOS filters which maintain a weighted rank for each sample in the sample window and update the weighted ranks for each window shift. We present novel (i) array architectures, (ii) stack filter architectures and (iii) sorting network architectures for non-recursive and recursive WOS filters which implement the above procedure. Our analysis shows that the bit-serial stack filter implementation is the one with smallest area while the bit-parallel stack filter is the one with the smallest input-output latency. The sorting network architecture (based on updating a sorted list) has the best area-time performance. Physical implementations verify our analysis.

Original languageEnglish (US)
Pages (from-to)1419-1433
Number of pages15
JournalSignal Processing
Issue number8
StatePublished - Aug 2000

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


Dive into the research topics of 'VLSI architectures for Weighted Order Statistic (WOS) filters'. Together they form a unique fingerprint.

Cite this