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Application of the adaptive noise removal technique to the enhancement of cDNA microarray images

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper a novel class of filters designed for the removal of impulsive noise in colour images is presented. The proposed filter family is based on the kernel function which controls the noise suppression properties of the new filtering scheme. The comparison of the new filtering method with the standard techniques used for impulsive noise removal indicates its superior noise removal capabilities and excellent structure preserving properties. The proposed filtering scheme has been successfully applied to the denoising of the cDNA microarray images. Experimental results proved that the new filter is capable of removing efficiently the impulses present in multichannel images, while preserving their textural features.
Rocznik
Tom
Strony
131--142
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
autor
  • Silesian University of Technology, Dept. of Automatic Control, Akademicka 16, 44-100 Gliwice, Poland
autor
  • Silesian University of Technology, Dept. of Automatic Control, Akademicka 16, 44-100 Gliwice, Poland
Bibliografia
  • [1] ALPARONE L., M. BARNI, F. BARTOLINI, V. CAPPELLINI, Adaptively weighted vector-median filters for motion-fields smoothing, Proc. of IEEE Int. Conf. on Acoustics, Speech and Signal Processing, 2267-2270, May 7-10, 1996.
  • [2] ASTOLA J., P. HAAVISTO, Y. NEUVO, Vector median filters, Proc. of the IEEE, 78, 4, 678-689, 1990.
  • [3] CHEN T., H.R. WU, Adaptive impulse detection using center-weighted median filters, IEEE Signal Processing Letters, 8, 1, 1-3, 2001.
  • [4] EISEN MB, BROWN PO. DNA arrays for analysis of gene expression, Methods in Enzymology, 303, 179-205, 1999.
  • [5] GABBOUJ M., F.A. CHEICKH, Vector median - vector directional hybrid filter for colour image restoration, Proc. of EUSIPCO, Trieste, Italy, September 10-13, 879-881, 1996.
  • [6] KARAKOS D., P.E. TRAHANIAS, Generalized multichannel image filtering structures, IEEE Trans. on Image Processing, 6, 7, 1038-1045, 1997.
  • [7] LEE J.S., Digital image enhancement and noise filtering by use of local statistics, IEEE Trans. on PAMI, 2, 2, 165-168, 1980.
  • [8] LUKAC R., Adaptive color image filtering based on center-weighted vector directional filters, Multidimensional Systems and Signal Processing, 15, 2, 169-196, 2004.
  • [9] LUKAC R, PLATANIOTIS KN, SMOLKA B, VENETSANOPOULOS AN. cDNA microarray image processing using fuzzy vector filtering framework. Journal of Fuzzy Sets and Systems: Special Issue on Fuzzy Sets and Systems in Bioinformatics, 152, 1, 17-35, 2005.
  • [10] LUKAC R, PLATANIOTIS KN, SMOLKA B, VENETSANOPOULOS AN. A multichannel order-statistic technique for cDNA microarray image processing. IEEE Transactions on Nanobioscience, 3, 4, 272-285, 2004.
  • [11] LUKAC R., B. SMOLKA, K. Martin, K.N. PLATANIOTIS, A.N. VENETSANOPOULOS, Vector filtering for color imaging, IEEE Signal Processing Magazine, Special Issue on Color Image Processing, 22, 1, 74-86, January 2005.
  • [12] PLATANIOTIS K.N., A.N. VENETSANOPOULOS, "Color Image Processing and Applications", Springer Verlag, August 2000.
  • [13] PLATANIOTIS K.N., D. ANDROUTSOS, A.N. VENETSANOPOULOS, Color image processing using adaptive vector directional filters, IEEE Trans. on Circuits and Systems II, 45, 10, 1414-1419, 1998.
  • [14] SMOLKA B., Efficient modification of the central weighted vector median filter, Lecture Notes in Computer Science, LNCS 2449, 166-173, 2002.
  • [15] SMOLKA B., M.K. SZCZEPANSKI, K.N. PLATANIOTIS, A.N. Venetsanopoulos, On the modified weighted vector median filter, Proc. of Digital Signal Processing (DSP), Santorini, Greece, 2, 939-942, 2002.
  • [16] SMOLKA B., R. LUKAC, K.N. PLATANIOTIS, New algorithm for noise attenuation in color images based on the central weighted vector median filter, Proc. of the 9th Int. Workshop on Systems, Signals and Image Processing (IWSSIP), Manchester, UK, 544-548, November 7-8, 2002.
  • [17] SMOLKA B., K.N. PLATANIOTIS, A.N. VENETSANOPOULOS, Nonlinear techniques for color image processing, in "Nonlinear Signal and Image Processing: Theory, Methods, and Applications", 445-505, CRC Press, 2004.
  • [18] SMOLKA B., On the new robust algorithm of noise reduction in color images, Computers & Graphics, 27, 503-513, 2003.
  • [19] SUN T., M. GABBOUJ, Y. NEUVO, Adaptive L-filters with applications in signal and image processing, Signal Processing, 38, 331-344, 1994.
  • [20] SUN T., M. GABBOUJ, Y. NEUOVO, Center weighted median filters, some properties and applications in image processing, Signal Processing, 35, 213-229, 1994.
  • [21] TADEUSIEWICZ R., M.R. OGIELA, "Medical Image Understanding Technology", Artificial Intelligence and Soft-Computing for Image Understanding, Series: Studies in Fuzziness and Soft Computing, Vol. 156, Springer-Verlag, 2004.
  • [22] TANG K., J. ASTOLA, Y. NEUVO, Nonlinear multivariate image filtering techniques, IEEE Trans. on Image Processing, 4, 788-798, 1995.
  • [23] TRAHANIAS P.E., D.G. KARAKOS, A.N. VENETSANOPOULOS, Directional processing of color images: theory and experimental results, IEEE Trans. on Image Processing, 5, 6, 868-881, 1996.
  • [24] VIERO T., K. ÖISTÄMÖ, Y. NEUVO, Three-dimensional median-related filters for color image sequence filtering, IEEE Trans. on Circiuts and Systems for Video Technology, 4, 2, 129-142, 1994.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0012-0014
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