On the adaptive impulsive noise reduction in color images

• Autorzy: Smolka B.
• Języki publikacji: EN

Abstrakty

EN

In this paper a novel class of noise attenuating and edge enhancing filters for color image processing is introduced and analyzed. The proposed adaptive filter design is minimizing the cumulative dissimilarity measure of a cluster of pixels belonging to the sliding filtering window and outputs the centrally located pixel. The proposed filter is computationally efficient, easy to implement and very effective in suppressing impulsive noise, while preserving image details and enhancing its edges. Therefore it can be used in any application in which simultaneous denoising and edge enhancement is a prerequisite for further steps of the color image processing pipeline.

Słowa kluczowe

EN

color image processing; impulsive noise removal; image enhancement

PL

przetwarzania obrazu kolorowego; impulsywne usuwanie szumu

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2010
• Tom: Vol. 16
• Strony: 193--200
• Opis fizyczny: Bibliogr. 11 poz., rys.

Twórcy

autor

Smolka B.

• Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland

Bibliografia

• [1] PLATANIOTIS K.N., VENETSANOPOULOS A.N., Color image processing and applications, Springer Verlag, 2000.
• [2] LUKAC R., SMOLKA B., MARTIN K., PLATANIOTIS K.N., VENETSANOPOULOS A.N., Vector filtering for color imaging, IEEE Signal Processing Magazine, Special Issue on Color Image Processing, Vol. 22, No.1, 2005, pp. 74-86.
• [3] SMOLKA B., PLATANIOTIS K.N., VENETSANOPOULOS A.N., Nonlinear techniques for color image processing, in "Nonlinear Signal and Image Processing: Theory, Methods, and Applications", Editors K.E. Barner, G.R. Arce, CRC Press, Boca Raton, FL., USA, 2004, pp. 445-505.
• [4] SMOLKA B., VENETSANOPOULOS A.N., Noise reduction and edge detection in color images, in "Color Image Processing: Methods and Applications", Editors: Lukac R., Plataniotis K.N., CRC Press, 2006, pp. 75-100.
• [5] ASTOLA J., HAAVISTO P., NEUVO Y., Vector median filters, Proc. of the IEEE, Vol. 78, No. 4, 1990, pp. 678-689.
• [6] KENNEY C., Deng Y., MANJUNATH B.S., Hewer G., Peer group image enhancement, IEEE Transactions on Image Processing, Vol. 10, No. 2, 2001, pp. 326-34.
• [7] SMOLKA B., PLATANIOTIS K.N., CHYDZINSKI A., SZCZEPANSKI M., VENETSANOPULOS A.N., WOJCIECHOWSKI K., Self-adaptive algorithm of impulsive noise reduction in color images, Pattern Recognition, Vol. 35, No. 8, 2002, pp. 1771-1784.
• [8] SMOLKA B., LUKAC R., CHYDZINSKI A., PLATANIOTIS K.N., WOJCIECHOWSKI K., Fast adaptive similarity based impulsive noise reduction filter, Real Time Imaging, Vol. 9, No. 4, 2003, pp. 261-276.
• [9] SMOLKA B., CHYDZINSKI A., Fast detection and impulsive noise removal in color images, Real-Time Imaging, Vol. 11, 2005, pp. 389–402.
• [10] LUKAC, R., SMOLKA, B., PLATANIOTIS, K.N.: Sharpening Vector Median Filters. Signal Processing, Vol. 87, No. 9, 2007, pp. 2085-2099.
• [11] LUKAC R., PLATANIOTIS K.N., SMOLKA B., VENETSANOPOULOS A.N., A multichannel order-statistic technique for cDNA microarray image processing, IEEE Transactions on Nanobioscience, Vol. 3, No. 4, 2004, pp. 272-285.