DOI QR코드

DOI QR Code

Noise Estimation Using Edge Detection

에지 검출을 이용한 잡음 예측

  • Received : 2013.02.18
  • Published : 2013.05.25

Abstract

In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

본 논문에서는 에지 검출을 이용한 잡음 예측 방법을 제안하였다. 이 방법은 필터 기반으로 한 잡음 예측 방법이다. 에지 검출은 잡음 예측에 영향을 미치는 구조나 세밀한 정보들을 제거하기 위함이다. 에지 검출을 하기 위하여, 영상의 세밀함에 안정적인 수정한 래셔널 필터를 사용하였다. 제안한 잡음 예측 방법은 다양한 형태의 영상들의 잡음 예측에 더욱 효율적으로 적용되며 기존의 필터 기반으로 한 잡음 예측 방법들보다 좋은 결과를 얻는다.

Keywords

References

  1. L. Sendur and I. W. Selesnick, "Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency," IEEE Trans. Signal Processing, vol. 50, pp. 2744-2756, Nov. 2002. https://doi.org/10.1109/TSP.2002.804091
  2. B. Tang, G. Sapiro, and V. Caselles, "Color image enhancement via chromaticity diffusion," IEEE Trans. Image Processing, vol. 10, pp. 701-707, 2001. https://doi.org/10.1109/83.918563
  3. M. K. Ozkan, M. I Sezan, and A. M. Tekalp, "Adaptive motion-compensated filtering of noisy image sequences," IEEE Trans. Circuits Sys. Video Technol., vol. 3, pp. 277-290, Aug. 1993. https://doi.org/10.1109/76.257217
  4. J. Kim and J. W. Woods, "3-D Kalman filter image motion estimation," IEEE Trans. Image Processing, vol. 7, pp. 42-52, Jan. 1998. https://doi.org/10.1109/83.650849
  5. S. -C. Tai and S. -M. Yang, "A fast method for image noise estimation using laplacian operator and adaptive edge detection," In Proc. ISCCSP 2008, Malta, pp. 12-14, Mar. 2008.
  6. J. Immerkaer, "Fast Noise Variance Estimation," Computer Vision and Image Understanding, Vol. 64, No. 2, pp. 300-302, Sep. 1996. https://doi.org/10.1006/cviu.1996.0060
  7. J. S. Lee and K. Hoppel, "Noise modeling and estimation of remotely sensed images," in Proc. 1989 Int. Geoscience and Remote Sensing, Vancouver, Canada, vol. 2, pp.1005-1008, Jun. 1989.
  8. A. Amer, A. Mitiche, and E. Dubois, "Reliable and fast structure oriented video noise estimation," in Proc. IEEE Int. Conf. Image Processing, Montreal, Quebec, Canada, vol. 1, pp.840-843, Jul. 2002.
  9. S. G. Chang, B. Yu, and M. Vetterli, "Adaptive wavelet thresholding for image denoising and compression," IEEE Trans. Image Process., vol. 9, no. 9, pp. 1532-1546, Sep. 2000. https://doi.org/10.1109/83.862633
  10. S. G. Chang, B. Yu, and M. Vetterli, "Spatially adaptive wavelet thresholding with context modeling for image denoising," IEEE Trans. Image Process., vol. 9, no. 9, pp. 1522-1531, Sep. 2000. https://doi.org/10.1109/83.862630
  11. D. L. Donoho and I. M. Johnstone, "Ideal spatial adaption via wavelet shrinkage," Biometrika, vol. 81, pp. 425-455, 1994. https://doi.org/10.1093/biomet/81.3.425
  12. A. Hashemi and S. Beheshti, "Adaptive noise variance estimation in BayesShrink," IEEE Signal Processing Letters, vol. 17, no. 1, Jan. 2010.
  13. B. -C. Song, "Motion-compensated noise estimation for effective video processing," IEEK 46SP-5-14, pp.120-125, Sep. 2009.
  14. G. Ramponi, "A rational filter for image smoothing," IEEE Signal Processing Letters, vol. 3, no. 3, pp. 63-65, March 1996. https://doi.org/10.1109/97.481156
  15. R. Castagno, S. Marsi, and G. Ramponi, "A simple algorithm for the reduction of blocking artifacts in images and its implementation," IEEE Trans. on Consumer Electronics, vol. 4, pp 1062-1070, Aug. 1998.

Cited by

  1. Multi-scale Crack Detection Using Scaling vol.50, pp.9, 2013, https://doi.org/10.5573/ieek.2013.50.9.194
  2. Pothole Detection Method in Asphalt Pavement vol.51, pp.10, 2014, https://doi.org/10.5573/ieie.2014.51.10.248