Earticle

초록

영어

In this paper, a new switch median filter is presented for suppression of impulsive noise in image. 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 clustering method, training procedure using LMS algorithm then freezing weights in each block are applied to test image. The proposed method includes fuzzy clustering part for clustering the observed vector of each pixel into one of M mutually exclusive blocks. In the training phase, Least Mean Square (LMS) algorithm use to train center weight in each block then obtained weights used in testing phase. Final results shows 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. Structure of MACWM filter
 4. Partitioning of observation vector space
 5. Experimental results
 6. Conclusion
 References

키워드

저자

• Hadi Sadoghi Yazdi [ Computer Department, Ferdowsi University of Mashhad, Mashhad, Iran ]
• Faranak Homayouni [ Computer Department, Ferdowsi University of Mashhad, 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