A Novel Methodology for Denoising Impulse Noise in Satellite Images through Isolated Vector Median Filter with k-means Clustering

A Novel Methodology for Denoising Impulse Noise in Satellite Images through Isolated Vector Median Filter with k-means Clustering

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© 2022 by IJETT Journal
Volume-70 Issue-8
Year of Publication : 2022
Authors : Y.Vishnu Tej, M. James Stephen, P.V.G.D. Prasad Reddy, Praveen Choppala
DOI : 10.14445/22315381/IJETT-V70I8P229

How to Cite?

Y.Vishnu Tej, M. James Stephen, P.V.G.D. Prasad Reddy, Praveen Choppala, "A Novel Methodology for Denoising Impulse Noise in Satellite Images through Isolated Vector Median Filter with k-means Clustering," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 272-283, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I8P229

Abstract
Satellite image denoising is imperative for improving images' visual quality and making future image processing and analysis chores easier. Noise detection is critical after the noise has been discovered; appropriate filters are applied to eliminate the impulse noise from the image. By attenuating the high-frequency image components and removing noise from the image, essential features are also lost. An efficient denoising approach is necessary to retain important information, improve the visual appearance, and reliably categorize an image. This paper proposes a novel method for denoising satellite images using the isolated vector median filtering with the k-means clustering (IMF-KM) approach. The proposed method has given better performance when compared to the existing algorithms in terms of peak signal-to-noise ratio (PSNR), structure similarity index (SSIM), and root means square error (RMSE).

Keywords
Image De-noising, Vector median filter, Isolated vector median filter, Basic vector directional filter, Directional distance filter, Directional vector median filter, Isolated vector minimum distance filter.

Reference
[1] Yogesh, V. and Yogendra, K, “Removal of Salt and Pepper Noise From Satellite Images,” International Journal of Engineering Research & Technology (IJERT), vol.2, pp.2051-2058.
[2] Pitas, I. and Venetsanopoulos, A.N, “Nonlinear Digital Filters: Principles and Applications ,” Springer Science & Business Media.
[3] Sicuranza, G., “Nonlinear Image Processing. Elsevier,” vol.84, 2000.
[4] Nodes, T. and Gallagher, N, “ Median Filters: Some Modifications and Their Properties,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.30, no.5 pp.739-746.
[5] Khryashchev, V.V., Priorov, A.L., Apalkov, I.V. and Zvonarev, P.S, “Image Denoising Using Adaptive Switching Median Filter,” In IEEE International Conference on Image Processing,vol. 1, pp. I-117, 2005. IEEE.
[6] Yin, L., Yang, R., Gabbouj, M. and Neuvo, Y, “Weighted Median Filters: A Tutorial,” IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, vol.43, no.3, pp.157-192, 1996.
[7] Chanu, R. and Singh, K.M, “ Vector Median Filters—A Survey,” International Journal of Computer Science and Network Security, vol.16, no.12, pp.66-84, 2016.
[8] Astola, J., Haavisto, P. and Neuvo, Y, “Vector Median Filters,” Proceedings of the IEEE, vol.78, no.4, pp.678-689, 1990
[9] Tukey, J.W., 1974. Nonlinear (Nonsuperposable) Methods for Smoothing Data. Proc. Cong. Rec. EASCOM'74, pp.673-681, 1974.
[10] Xu, Q., Zhang, Q., Hu, D. and Liu, J, “ Removal of Salt and Pepper Noise in Corrupted Image Based on Multilevel Weighted Graphs and IGOWA Operator,” Mathematical Problems in Engineering, 2018.
[11] Kumar, N.R. and Kumar, J.U, “A Spatial Mean and Median Filter for Noise Removal in Digital Images,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol.4, no.1, pp.246-253, 2015.
[12] Khryashchev, V., Kuykin, D. and Studenova, A, “ Vector Median Filter with Directional Detector for Color Image Denoising.,” In Proc. of the World Congress on Engineering, vol. 2, pp. 1-6, 2011.
[13] Plataniotis, K.N., Androutsos, D. and Venetsanopoulos, A.N, “Vector Directional Filters: An Overview. In CCECE'97,” Canadian Conference on Electrical and Computer Engineering. Engineering Innovation: Voyage of Discovery. Conference Proceedings , vol. 1, pp. 106-109, 1997. IEEE.
[14] Trahanias, P.E. and Venetsanopoulos, A.N, “ Vector Directional Filters-A New Class of Multichannel Image Processing Filters,” IEEE Transactions on Image Processing, vol.2, no.4, pp.528-534, 1993.
[15] Lukac, R, “ Adaptive Color Image Filtering Based on Center-Weighted Vector Directional Filters,” Multidimensional Systems and Signal Processing, vol.15, no.2, pp.169-196, 2004.
[16] Choppala, P., Meka, J.S. and PVGD, P.R, “Vector Isolated Minimum Distance Filtering for Image De-Noising In Digital Color Images,” International Journal of Recent Technology and Engineering, vol.8, no.4, pp.2401-2405, 2019.
[17] Choppala, P., Meka, J.S. and PVGD, P.R, “Isolated Vector Median Filtering for Noise Reduction in Digital Color Images,” 2020.
[18] Smolka, B., Malik, K. and Malik, D, “ Adaptive Rank Weighted Switching Filter for Impulsive Noise Removal in Color Images,” Journal of Real-Time Image Processing, vol.10, no.2 pp.289-31, 2015.
[19] Harini N, Shaik Majeeth S, Aswanth Kumar G and Abinaya J, "CT Image Denoising using DTCWT with Level Dependent Thresholding," International Journal of Electronics and Communication Engineering, vol. 5, no. 8, pp. 14-21, 2018. Crossref, https://doi.org/10.14445/23488549/IJECE-V5I8P103
[20] D.C. Shubhangi, Anita Totapnor"Survey On Noise Detection Method" International Journal of Engineering Trends and Technology 67.8 (2019): 19-21.
[21] Johnsymol Joy, "Overview of Different Data Clustering Algorithms for Static and Dynamic Data Sets" SSRG International Journal of Computer Science and Engineering 5.3 (2018): 1-3. Crossref, https://doi.org/10.14445/23488387/IJCSE-V5I3P10.