Earticle

초록

영어

In this paper, a new median filter switcher is presented for suppression of impulsive noise in gray-level images. The proposed filter is Modified Adaptive Center Weighted Median (MACWM) filter with an adjustable central weight obtained by partitioning the observation vector space. Dominant points of the proposed approach are partitioning of observation vector space using fuzzy c-means clustering method, training procedure using LMS algorithm and then applying the freezing weights of each block to test image. The exprimental results show better performance in the impulse noise reduction over standard images relative the median (MED) filter, the switching scheme I (SWM-I) filter, the signal dependent rank order mean (SD-ROM) filter, the tristate median (TSM) filter, the fast peer group filter (FPGF), the fuzzy median (FM) filter, the PFM filter and the adaptive center weighted median (ACWM) filter.

목차

Abstract
 1. Introduction
 2. Adaptive center-weighted median filtering
 3. The structure of MACWM filter
 4. Partitioning of observation vector space
 5. Experimental results
 6. Conclusion
 Appendix
  a. FCM clustering method
  b. Training the weight by LMS algorithm:
 References

키워드

저자

• Mahdipour Hossein-Abad Hadi [ Electrical Engineering Department, Ferdowsi University of Mashhad, Iran ]
• Khademi Morteza [ Electrical Engineering Department, Ferdowsi University of Mashhad, Iran ]
• Sadoghi Yazdi Hadi [ Computer Department, Ferdowsi University of Mashhad, Iran ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605