Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Boateng, Kwame Osei
- Improving the Effectiveness of the Median Filter
Abstract Views :253 |
PDF Views:0
Authors
Affiliations
1 Kwame Nkrumah University of Science and Technology,, GH
2 University for Development Studies,, GH
1 Kwame Nkrumah University of Science and Technology,, GH
2 University for Development Studies,, GH
Source
International Journal of Electronics and Communication Engineering, Vol 5, No 1 (2012), Pagination: 85-97Abstract
Digital images are often corrupted by Impulse noise due to errors generated in noisy sensor, errors that occur in the process of converting signals from analog-to-digital and also errors that are generated in the communication channels. This error that occurs inevitably alters some of the pixels intensity while some of the pixels remain unchanged. In order to remove impulse noise and enhance the affected image quality, we have studied the median filter and are proposing a method based on an improved median filtering algorithm. This method removes or effectively suppresses the impulse noise in the image whiles preserving the image edges information and enhancing the image quality. The proposed method is a spatial domain approach and uses the overlapping window to filter the signal based on the selection of an effective median per window. The approach chosen in this work is based on a functional level 2n +1 window that makes the selection of the normal median easier, since the number of elements in the window is odd. The median so chosen is confirmed as the effective median or, where the median is an impulse a more representative value is sought and used as the effective median. The performance of the proposed effective median filter has been evaluated in MATLAB simulations on an image that has been subjected to various degrees of corruption with impulse noise. The results demonstrate the effectiveness of our algorithm vis-à-vis the standard and adaptive median filtering algorithms.References
- Konstantinides, K., and Bhaskaram, V., 1996, “Monolithic architectures for image processing and compression,” IEEE Computer Graphicsand Application, pp.75-86.
- Wang, W., Swamy, M. N. S., and Ahmad, M. O., 2004, “RNS Application for Digital Image Processing,” 4th IEEE international workshop on System-on-chip for Real-time Application, pp. 77-80.
- Nodes, T. A., and Gallagher, N. C., 1982, “Median filters: Some modifications and their properties,” IEEE Trans. Acoust., Speech, Signal Processing. 30(5), pp. 739-7.
- Gonzalez, R.C., and Wood, R.E., 2007, Digital Image Processing, Prentice- Hall, India, Second Edition.
- Umbaugh, S. E., 1998, Computer Vision and Image Processing, Prentice-Hall, Englewood Cliffs, NJ, USA.
- Yli-Harja, O., Astola, J., and Neuvo, Y. , 1991, “Analysis of the properties of median and weighted median filters using threshold logic and stack filter representation,” IEEE Trans. Signal Processing, vol. 39, no. 2, pp. 395–410.
- Ko, S.-J., and Lee, Y. H., 1991, “Center weighted median filters and their applications to image enhancement,” IEEE Trans. Circuits and Systems, vol. 38, no. 9, pp. 984–993.
- Ghandeharian, B., Sadoghi, H., Homayouni, F., 2009, ” Modified Adaptive Center Eighted Median Filter for Uppressingimplusive noise in Images,” international journal of Research and Reviews in Applied Sciences, Vol. 1, Issue 3, pp. 219-227.
- Eng, H.-L., and Ma, K.-K., 2001, “Noise adaptive soft-switching median filter,” IEEE Trans. Image Process., vol. 10, no. 2, pp. 242–251.
- Pok, G., Liu, J.-C., and Nair, A. S., 2003, “Selective removal of impulse noise based on homogeneity level information,” IEEE Trans. Image Processing, vol. 12, no. 1, pp. 85–92.
- Dhanasekaran, D., Bagan, K., 2009, “High Speed Pipeline Architecture for Adaptive Median Filter,” European Journal of Scientific Research, Vol.29, No.4, PP.454-460.
- Chang-Yanab, C., Ji-Xiana, Z., Zheng-Juna, L., 2008, “Study on Methods of Noise Reduction in a Stripped Image, the International Archives of the Photogrammetry,” Remote Sensing and Spatial Information Sciences, Vol XXXVII. Part B6b, Beijing.
- Bezerra Candeias, A. L., Mura, J. C., et al., 1995, “Interferogram phase noise reduction using morphological and modified median filters,”.
- Fisher B., Perkins S., Walker A., and Wolfart E., 2005, Hypermedia Image Processing Reference, University of Edinburgh, UK.
- Hussain, Z., Digital Image Processing–Practical Application of Parallel Processing Techniques, Ellis Hovwood, West sssex, UK, 1991.