Adaptive weighted fuzzy mean filter

Ch Sh Lee, Yau-Hwang Kuo

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)

Abstract

A new fuzzy filter for the removal of additive impulse noise, called the Adaptive Weighted Fuzzy Mean (AWFM) filter, is proposed and analyzed in this paper. The AWFM is an extensive version of Weighted Fuzzy Mean (WFM) filter [l] and its filtered output signal is either the output of WFM or the processed signal by the detection algorithm. This filter gives very superior performance compared with conventional filters when evaluated by Mean Absolute Error (MAE), Mean Square Error (MSE) and subjective evaluation criteria. For dedicated hardware implementation, AWFM is also much simpler than the conventional median filter.

Original languageEnglish
Pages2110-2116
Number of pages7
Publication statusPublished - 1996 Dec 1
EventProceedings of the 1996 5th IEEE International Conference on Fuzzy Systems. Part 3 (of 3) - New Orleans, LA, USA
Duration: 1996 Sep 81996 Sep 11

Other

OtherProceedings of the 1996 5th IEEE International Conference on Fuzzy Systems. Part 3 (of 3)
CityNew Orleans, LA, USA
Period96-09-0896-09-11

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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