Adaptive impulse detection based approaches for the noise reduction in heart image sequences

• Autorzy: Smolka B. , Lukac R.
• Języki publikacji: EN

Abstrakty

EN

This paper focuses on three-dimensional (3-D) adaptive median filters based on the impulse detection approach designed to effectively remove the impulse noise from cardiographic image sequences. Impulse noise affects the useful information in the form of bit errors and it introduces to the image high frequency changes that prohibit to process and to evaluate the heart dynamics correctly. Therefore biomedical imaging such as vascular imaging and quantification of heart dynamics is closely related to digital filtering. In order to suppress impulse noise effectively, well-known non-linear filters based on the robust order-statistic theory provide interesting results. Although median filters have excellent impulse noise attenuation characteristics, their performance is often accompanied by undesired processing of noise-free samples resulting in edge blurring. The reason is that median filters do not satisfy the superposition property and thus the optimal filtering situation where only noisy samples are affected can never be fully obtained. The presented adaptive impulse detection based median filters, can achieve the excellent balance between the noise suppression and the signal-detail preservation. In this paper, the performance of the proposed approaches is successfully tested for the heart image sequence of 38 frames and the wide range of noise corruption intensity. The results are evaluated in terms of mean absolute error, mean square error and cross correlation.

Słowa kluczowe

EN

heart sequence; impulse noise; non-linear filtering; median filter

PL

sekwencja serca; zakłócenia impulsowe; nieliniowa filtracja; mediana filtra

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2002
• Tom: Vol. 3
• Strony: MI21--29
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Smolka B.

• Dept. of Automatic Control, Silesian University of Technology, Akademicka 16 Str., 44-101 Gliwice, Poland

autor

Lukac R.

• Dept. of Electronics and Multimedia Communications, Technical University of Kosice, Park Komenskeho 13, 041 20 Kosice, Slovak Republic

Bibliografia

• [1] Abreu, E., Lighstone, M., Mitra, S.K., Arakawa, K., A New Efficient Approach for the Removal of Impulse Noise from Highly Corrupted Images. IEEE Transactions on Image Processing, Vol. 5, No. 6, pp. 1012- 1025, June 1996.
• [2] Arce, G.R., Multistage Order Statistic Filters for Image Sequence Processing. IEEE Transactions on Signal Processing, Vol. 39, No. 5, pp. 1146-1163, May 1991.
• [3] Astola, J., Kuosmanen, P., Fundamentals of Nonlinear Digital Filtering. CRC Press, 1997.
• [4] Bosnjak, A., Torrealba, V., Montilla, G., Villegas, H., Burdin, V., Solaiman, B., Roux, C., Segmentation, Reconstruction, Modeling and 3D Visualization of the Ventricles in Echocardiographics Images. Proc. IEEE - EURASIP ISPA'01, Pula, Croatia, pp. 260-265, 2001.
• [5] Boncelet, C., Image Noise Models, in Handbook of Image & Video Processing (ed. A. Bovik), Academic Press, pp. 325-336, 2000.
• [6] Kleihorst, R.P., Lagendijk, R.L., Biemond, J., Noise Reduction of Image Sequences Using Motion Compensation and Signal Decomposition. IEEE Transactions on Image Processing, Vol. 4, No. 3, pp. 274-284, - March 1995.
• [7] Kokaram, A. Motion Picture Restoration. Springer-Verlag, London, 1998.
• [8] Lee, J.S., Digital Image Smoothing and the Sigma Filter. Computer Vision, Graphics, and Image Processing, Vol. 24, No. 2, pp. 255-269, November 1983.
• [9] Lukac, R., Marchevsky, S., Lum Smoother with Smooth Control for Noisy Image Sequences. EURASIP Journal on Applied Signal Processing, Vol. 2001, No. 2, pp. 110-120, June 2001.
• [10] Lukac, R., Impulse Detectors for Noised Sequences. Radioengineering, Vol. 10, No. 2, pp. 24-31, July 2001.
• [11] Lukac, R., Reconstruction of Noisy Hearth Dynamics by Optimised Permutation Filters. 16th Biennial International EURASIP Conference BIOSIGNAL 2002 in Brno, Czech Republic, 2002, pp.289-291.
• [12] Lukac, R., Smolka, B., Hearth Dynamics Filtered by Optimised Adaptive Median. Proc. of the 2nd European Medical & Biological Engineering Conference EMBEC’02 in Vienna, Austria, 2002, (accepted for publication).
• [13] Nikolaidis, N., Pitas, I., 3-D Image Processing Algorithms. Wiley, 2000.
• [14] Park, J., Kurz, L., Image Enhancement Using the Modified ICM Method. IEEE Transactions on Image Processing, Vol. 5, No. 5, pp.765-771, May 1996.
• [15] Peltonen, S., Gabbouj, M., Astola, J., Nonlinear Filter Design: Methodologies and Challenges. Proc. IEEE Region 8-EURASIP Symposium ISPA'01 in Pula, Croatia, pp. 102-103, 2001.
• [16] Pitas, I. Venetsanopoulos, A.N., Order Statistics in Digital Image Processing. Proceedings of the IEEE, Vol. 80, No. 12, pp. 1892-1919, December 1992.
• [17] Plebe, A., Gallo, G., Filtering Echocardiographic Image Sequences in Frequency Domain. Proc. IEEE Region 8-EURASIP ISPA'01, Pula, Croatia, pp. 238-243, 2001.
• [18] Smolka, B., Wojciechowski, K., Random Walk Approach to Image Enhancement. Signal Processing, Vol. 81, No. 3, pp. 465-482, 2001.
• [19] Viero, T., Oistamo, K., and Neuvo, Y., Three-Dimensional Median Related Filters for Color Image Sequence Filtering. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 4, No. 2, pp. 129- 142, April 1994.