Earticle

초록

영어

Aiming at the impulse noise generated in capturing the images of insulator on power lines, a denoising method based on peer groups is proposed. The center pixel variance σcenter
is defined, the minimum of neighborhood variance and center σmin is treated as threshold
σmin and the peer group is determined by comparing the relation between absolute value of gray value difference and σmin . According to the size of peer group and its complement set, center pixel is estimated when noisy pixels exist in the neighborhood window. Otherwise, the size of window is adjusted adaptively and center pixel is estimated on the basis of mean value of non-noisy pixels within adjusted window. The experimental results show that the method can get a higher peak signal to noise ratio, IEF and SSIM when there is high density impulse noise in an image.

목차

Abstract
 1. Introduction
 2. Peer Group
 3. Adaptive Denoising Algorithm based on Modified Peer Groups-MPGAD
  3.1. The Improvement of Peer Group Selection and the Adaptive Adjustment of Neighborhood Window
  3.2. Steps of the Algorithm
 4. Experiments and Results
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Cui Kebin [ Department of Computer, North China Electric Power University, Baoding, China ]
• Li Baoshu [ Department of Electrical Engineering, North China Electric Power University, Baoding, China ]
• Yuan Jinsha [ Department of Electronics, North China Electric Power University, Baoding, China ]
• Wang Ping [ Department of Computer, North China Electric Power University, Baoding, China ]

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