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http://dx.doi.org/10.5573/ieie.2015.52.4.207

Noise Estimation using Edge Detection in Moving Pictures  

Kim, Young-Ro (Dept. of Computer Science and Information, Myongji College)
Oh, Tae-Myung (Dept. of Computer Science and Information, Myongji College)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.52, no.4, 2015 , pp. 207-212 More about this Journal
Abstract
We propose a noise estimation method using edge detection in moving pictures. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use Sobel and morphological closing operators which are robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of moving images and has better results than those of existing noise estimation methods. Also, proposed algorithm can be efficiently applied to image and video applications.
Keywords
Noise estimation; Edge detection; Sobel; Morphological closing operation;
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1 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.
2 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.   DOI   ScienceOn
3 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.   DOI   ScienceOn
4 D. L. Donoho and I. M. Johnstone, "Ideal spatial adaption via wavelet shrinkage," Biometrika, vol. 81, pp. 425-455, 1994.   DOI   ScienceOn
5 A. Hashemi and S. Beheshti, "Adaptive noise variance estimation in BayesShrink," IEEE Signal Processing Letters, vol. 17, no. 1, Jan. 2010.
6 S. -D. Kim and K. -W. Lim, "Motion Adaptive Temporal-Spatial Noise Reduction Scheme with Separated Pre- and Post-Spatial Filter," IEIE 46SP-5-14, pp. 40-47, Sep. 2009.
7 B. -C. Song, "Motion-compensated noise estimation for effective video processing," IEIE 46SP-5-14, pp. 120-125, Sep. 2009.
8 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.   DOI   ScienceOn
9 J. Kim and J. W. Woods, "3-D Kalman filter image motion estimation," IEEE Trans. Image Processing, vol. 7, pp. 42-52, Jan. 1998.   DOI   ScienceOn
10 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.   DOI   ScienceOn
11 B. Tang, G. Sapiro, and V. Caselles, "Color image enhancement via chromaticity diffusion," IEEE Trans. Image Processing, vol. 10, pp. 701-707, 2001.   DOI   ScienceOn
12 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.
13 J. Immerkaer, "Fast noise variance estimation," Computer Vision and Image Understanding, Vol. 64, No. 2, pp. 300-302, Sep. 1996.   DOI   ScienceOn
14 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.