Cleaning Method of Impulse Noise Using Mean Shift Segmentation

평균이동 분할을 이용한 임펄스 잡음제거

  • 권영만 (을지대학교 의료산업학부) ;
  • 임명재 (을지대학교 의료산업학부)
  • Received : 2009.09.10
  • Published : 2009.12.30

Abstract

In this paper, We proposed the efficient method of cleaning impulse noise using mean shift segmentation. This method do its job for the pixel which is identified as impulse noise using mean shift segmentation instead of all pixel of image by the existing method. we found that the quality of image is improved by measuring the sum of square error in result image and impulse noise is cleaned efficiently by doing experiment.

본 논문에서는 평균이동 분할을 이용해서 임펄스 잡음을 제거하는 효과적인 방법을 제안한다. 이 방법은 영상에 모든 화소에 대해서 필터링 작업을 하는 기존의 방법과는 달리 평균이동 분할을 사용해서 임펄스 잡음의 위치를 추정하고 그 위치에서만 필터링 작업을 수행하는 방식이다. 실험을 통해 결과 영상의 오차의 제곱의 합을 측정하여 화질이 개선되고, 임펄스 잡음이 효과적으로 제거되는 것을 확인하였다.

Keywords

References

  1. M. Emre Celebi, Hassan A. Kingravi, Y. Alp Aslandogan, "Nonlinear vector filtering for impulse noise removal from color images," Journal of Electronic Imaging 16(3), Jul-Sep. 2007
  2. H. Hwang and R. A. Hadded, "Adaptive median filter: New algorithms and results," IEEE Trans. Image Process., vol. 4, no.4, pp. 499-502, Apr. 1995. https://doi.org/10.1109/83.370679
  3. Raymond H. Chan, Chung-Wa Ho, and Mila Nikolova, "Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-Preserving Regularization," IEEE Trans. On Image Processing, vol. 14, no. 10, Oct. 2005
  4. Milan Sonka, Vaclav Hlavac, Roger Boyle, Image Processing, Analysis, and Machine Vision, Thomson, 2008.
  5. Dorin Comaniciu and Peter Meer, ''Mean Shift: A Robust Approach Toward Feature Space Analysis," IEEE Trans. Pattern Analysis and machine intelligence," vol. 24, no. 5, May 2002
  6. Gonzalez, Woods, Eddins, "Digital Image Processing Using Matlab," Prentice Hall, 2004
  7. Alasdair McAndrew, "Introduction To Digital Image Processing with Matlab," Thomson, 2004.