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Gaussian noise estimation using adaptive filtering  

Joh, Beom Seok (명지전문대학 컴퓨터정보과)
Kim, Young Ro (명지전문대학 컴퓨터정보과)
Publication Information
Journal of Korea Society of Digital Industry and Information Management / v.8, no.4, 2012 , pp. 13-18 More about this Journal
Abstract
In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.
Keywords
Gaussian Noise; Estimation; Adaptive Filtering;
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1 L. Sendur and I. W. Selesnick, "Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency," IEEE Trans. Signal Processing, vol. 50, Nov. 2002, pp. 2744-2756.   DOI
2 B. Tang, G. Sapiro, and V. Caselles, "Color image enhancement via chromaticity diffusion," IEEE Trans. Image Processing, vol. 10, 2001, pp. 701-707.   DOI
3 K. J. Boo and N. K. Bose, "A motioncompensated spatio-temporal filter for image sequences with signal-depending noise," IEEE Trans. Circuits Sys. Video Technol., vol. 8, June 1998, pp.287-298.   DOI
4 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, Aug. 1993, pp. 277-290.   DOI
5 S. I. Osen, "Estimation of noise in images: An evaluation," Graphical Models and Image Process., vol. 55, July 1993, pp.319-323.   DOI
6 K. Rank, M. Lendl, and R. Unbehauen, "Estimation of image noise variance," IEE Proc. Vis. Image Signal Process., vol. 146, Apr. 1999, pp.80-84.
7 H. Y. Han, H. M. Kwon, S. M. Lee, G. D. Lee, and B. S. Kang, "An Effective noise estimator for use in noise reduction," International Journal of KIMICS, vol. 9, no. 1, Feb. 2011.
8 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, Jun. 1989, pp. 1005-1008.
9 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, Jul. 2002, pp. 840-843.