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A Mask-based Gaussian Noise Removal Algorithm in Spatial Space  

Seo, Hyun-Soo (School of Electrical and Control Engineering, Pukyong National University)
Kim, Nam-Ho (School of Electrical and Control Engineering, Pukyong National University)
Publication Information
Journal of information and communication convergence engineering / v.5, no.3, 2007 , pp. 259-264 More about this Journal
Abstract
According to the development and wide use of broad band internet etc., diverse application technologies using large capacity data such as images have been progressed and in these systems, for accurate acquisition and precise applications of an original signal, the degradation phenomenon generated in the transmission process etc. should be removed. Noises have become known as the main cause of the degradation phenomenon and especially Gaussian noise represents characteristics occurring dependently in image signals and degrades detail information such as edge. In this paper, we removed Gaussian noise using a subdivided nonlinear function according to a threshold value and analyzed the histogram acquired from an edge image to establish a threshold value adaptively, and strengthened detail information of image by using the postprocessing. In simulation results, the proposed method represented excellent performance from comparison of MSE with existing methods.
Keywords
Degradation phenomenon; Gaussian noise removal; histogram; threshold value;
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1 G. R. Arce and J. L. Paredes., 'Image enhancement and analysis with weighted medians,' in Nonlinear Image Processing, S. K Mitra and G. Sicuranza, Eds. New York: Academic, pp. 27-67, 2000
2 R. C. Hardie and K.E Barner, 'Extended permutation filters and their application to edge enhancement,' IEEE Trans. Image Process., vol. 5, no. 6, pp. 855-867, Jun. 1996   DOI   ScienceOn
3 W. M. Morrow, R. B. Paranjape, M. R. Rangayyan, and J. E. Desautels, 'Region-based contrast enhancement of mammograms,' IEEE Trans. Med. Imag., vol. 11, no. 9, pp. 392-406, Sep. 1992   DOI   ScienceOn
4 A. Polesel, G. Ramponi, and V. J. Mathews, 'Image enhancement via adaptive unsharp masking,' IEEE Trans. Image Process., vol. 9, no. 3, pp. 505-510, Mar. 2000   DOI   ScienceOn
5 M. Fischer, J. L. Paredes, and G. R. Arce, 'Image Sharpening using permutation weighted medians,' in Proc. X Eur. Signal Processing Conf. (EUSIPCO), Tampere, Finland, Sep. 4-8, 2000
6 Min-Cheng Pan and Alan H. Lettington, 'Smoothing Images by a Probability Filter,' in Proc. IEEE Int. Joint Symp. Intell. and Syst., pp. 343-346, 1998
7 G. Ramponi, N. Strobl, S. K. Mitra, and T.-H Yu, 'Nonlinear unsharp masking methods for image contrast enhancement,' J. Electron. Imag., vol. 5, no. 3, pp. 353-366, 1996   DOI   ScienceOn
8 J. Tang, E. Peli, and S. Action, 'Image enhancement using a contrast measure in the compressed domain,' IEEE Signal Process. Lett., vol. 10, no.10, pp. 289-292, Oct. 2003   DOI   ScienceOn
9 F. Van der Heijden, Image Based Measurement Systems, New York: Willey, 1994
10 S. K Mitra, H. Li, I.-S. Lin, and T.-H. Yu, ' A new class of nonlinear filters for image enhancement,' in Proc. Int. Conf. Acoustics, Speech and Signal Processing, Toronto, ON, Canada, pp. 2525-2528, Apr. 1991
11 M. Fischer, J. L. Pareces, and G. R. Arce, 'Weighted median image sharpeners for the World Wide Web,' IEEE Trans. Image Process., vol. 11, no. 7, pp. 717-727, Jul. 2002   DOI   ScienceOn
12 S. C. Matz and R. J. P. de Figueiredo, 'A nonlinear technique for image contrast enhancement and sharpening in noisy images,' in Proc. IEEE ISCAS, pp. 175-178, May 30-Jun. 2, 1999
13 G. C. Giakos, M. Pastorino, F. Russo, S. Chowdhury, N. Shah, and W. Davros, 'Noninvasive imaging for the new century,' IEEE Instrum. Meas. Magazine, no. 3, pp. 32-49, Jun. 1999
14 A. K Jain, Fundamental of Digital Image Processing, Englewood Cliffs, NJ: Prentice-Hall, 1989
15 I. Pitas, Digital Image Processing Algorithms and Applications, New York: Wiley, 2000
16 S. Thurnhofer, 'Two-dimensional teager filters,' in Nonlinear Image Processing, S. K. Mitra and G. Sicuranza, Eds. New York:Academic, pp.167-202, 2000