Digital Image Denoising by Adaptive Median Filtering and Wavelet Transform
DOI:
https://doi.org/10.55630/dipp.2014.4.25Keywords:
Digital image processing, adaptive median filter, wavelet denoisingAbstract
Digital image processing is an important area of preservation and representation of cultural and historical objects. Part of it is the task of cleaning images corrupted by noise. Many different methods and approaches have been successfully implemented, but still filtering and denoising techniques are developing and improving intensively. Herein, we report numeric simulations of 2D image filtering. Effects of impulse noise are very efficiently reduced by adaptive median filtering. The situation of additive noise, which itself depends on the intensity of the original image, is more complicated. However, we demonstrate that in this case the use of wavelet transforms in the denoising procedure is very productive and promising.References
Gonzalez, R. C., Woods, R. E.: Digital Image Processing. Prentice Hall, NJ (2008)
Arce G. R.: Nonlinear Signal Processing: A Statistical Approach. Wiley, New Jersey (2005)
Piccardi, M.: Background subtraction techniques: a review. In: IEEE International Conference on Systems, Man and Cybernetics, 4., 3099--3104 (2004)
Eng, H.-L., Ma, K.-K.: Noise Adaptive Soft-Switching Median Filter. IEEE Trans. Image Proc., 10, 242--251 (2001)
Penland, C., Ghil, M., Weickmann, K. M.: Adaptive filtering and maximum entropy spectra with application to changes in atmospheric angular momentum. J. Geophys. Res., 96, 22659-22671 (1991)
Mallat S., A wavelet tour of signal processing. Academic Press, London (1999)
Petrou M., Petrou, C.: Image Processing: The Fundamentals. John Wiley & Sons (2010)
Akansu, A.N., Serdijn, W.A., Selesnick, I.W.: Wavelet Transforms in Signal Processing: A Review of Emerging Applications. Physical Comm. 3, 1--18 (2010)
