Novel Sgmentation Technique for Synthetic Aperture Radar Target Tracking using Hybrid PSO Method

  • Authors

    • B Malakonda Reddy
    • Md Zia Ur Rahman
    2018-04-15
    https://doi.org/10.14419/ijet.v7i2.17.11566
  • Electromagnetic Imaging, synthetic aperture radars, remote sensing, terrain features, segmentation methods.

  • Abstract

    In remote sensing applications, it is evidently electromagnetic imaging has more advantages than optical imaging due to its horizon. In such a contest synthetic aperture radars (SAR) plays a vital role. In SAR image processing, segmentation is a key step in identifying and tracking targets, terrain features.  Hence, this paper, we present an Improved hybrid PSO method proposed based on multilevel threshold for enhancing the image for segmentation. Experimental results indicate, the proposed methods enhance the edge features effectively with compare to Otsu, Modified Otsu and Region Based Active contour methods.

     

  • References

    1. [1] Yongjian Yu, Acton, S.T.†Speckle reducing anisotropic diffusionâ€IEEE Transactions on Image processing,volume 11,issue 11,November 2002.

      [2] Junling Zhu; Jianguo Wen; YafengZhangâ€A new algorithm for SAR image despeckling using an enhanced Lee filter and median filterâ€IEEE Conference Publications Image and signal processing, Volume: 01,Pages: 224 - 228,2013

      [3] Akl, Tabbara, K,Yaacoub.C†An enhanced Kuan filter for suboptimal speckle reduction†Advances in Computational Tools for Engineering Applications (ACTEA), Pages: 91 – 95,2012

      [4] T.C.Aysal,K.E.Barner,â€Rayleigh maximum like hood Filtering for speckle reduction of Ultrasound Imagesâ€IEEE transactions on Medical Imaging,vol.26.no.5,pp.712-727,2007.

      [5] Firoju,Loana,CorinaNafomita,J-M Boucher and AlexandruIsar â€Image Denoising using new implementation of the hyper analytic wavelet transformâ€IEEEtaransactions on Instrumentation and Measurement,vol 58,no.8,pp.2410-2416,August 2009.

      [6] Mencattini,Arianna,MarcelloSalmeri,RobertoLojacono,MarcoFrigerio and Federica Caselli “Mammographic images enhancement and denoising for breast cancer detection using dyadic wavelet processingâ€,IEEE Transaction on Instrumentation and Measurement,vol.57,no.7,pp.1422-1430,july 2008.

      [7] F.Russoâ€An Image Enhancement system based on noise estimationâ€IEEE Transaction on Instrumentation and Measurement,Vol.56,no.4,pp.1435-1442,August 2007.

      [8] Gifani,P.H.Behnam and Z.A.Sani “Noise reduction of ECG Images based on temporal informationâ€IEEE Transaction on Ultrasonic, Ferroelectrics and frequency Control,vol.61,no.4,pp.620-630,April 2004.

      [9] W. X. Kang, Q. Q. Yang, R. R. Liang ,“The Comparative Research on Image Segmentation Algorithmsâ€, IEEE Conference on ETCS, pp. 703-707, 2009

      [10] Er. Nirpjeetkaur and ErRajpreeetkaur, “A review on various method of image thresholdingâ€,IJCSE-2011.

      [11] ZhongQuandLiHangâ€Research on Iimage Segmentation Based on the Improved Otsu Algorithm.â€,2010

      [12] W. X. Kang, Q. Q. Yang, R. R. Liang ,“The Comparative Research on Image Segmentation Algorithmsâ€, IEEE Conference on ETCS, pp. 703-707, 2009.

      [13] Z. Ningbo, W. Gang, Y. Gaobo, and D. Weiming, “A fast 2d otsuthresholding algorithm based on improved histogram,†in Pattern Recognition, 2009. CCPR 2009. Chinese Conference on, 2009, pp. 1–5.

      [14] T.Chan and L.Vese,â€Active contours with outedgesâ€IEEE Transactions Image Processing,vol.10,issue 2,pp.266-277,2001..

      [15] S.-C. Zhu and A. Yuille, “Region competition: Unifying snakes, regiongrowing, and Bayes/MDL for multiband image segmentation,†IEEETrans. Pattern Anal. Mach. Intell., vol. 18, no. 9, pp. 884–900, Sep.1996..

      [16] S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, and A. Yezzi,“Gradient flows and geometric active contour models,†in Proc. 5th Int.Conf. Comput. Vis., 1995, pp. 810–815.

      [17] R. Ronfard, “Region-based strategies for active contour models,†Int.J. Comput. Vis., vol. 13, no. 2, pp. 229–251, Oct. 1994.

      [18] C. Samson, L. Blanc-Feraud, G. Aubert, and J. Zerubia, “A variationalmodel for image classification and restoration,†IEEE Trans. PatternAnal. Mach. Intell., vol. 22, no. 5, pp. 460–472, May 2000.

      [19] J. Kennedy, and R. Eberhart, Swarm Intelligence, San Francisco: Morgan Kaufmann Publishers, 2001.

      [20] Gao,Hao,WenboXu,Junsun and Yulan Tang†Multilevel thresholding for image segmentation through an improved quantum-behaved particle swarm algorithm “IEEE Transactions on Instrumentation and Measurement,vol.59,no.4,pp.934-946,April 2010.

      [21] Y. zhiwei, C. hongwei, L wei and Z. jinping, "Automatic threshold selection based on Particle Swarm Optimization algorithm," in the proceedings International Conference on Intelligent Computation Technology and Automation, pp. 36-39, 2008 .

      [22] C. Wei and F. Kangling, "Multilevel Thresholding Algorithm Based on Particle Swarm Optimization for Image Segmentation," in the Proceedings of the 27th Chinese Control Conference, July 16-18, Kunming, Yunnan, China, pp. 348-351, 2008

      [23] P. D. Sathya, R. Kayalvizhi, "PSO-Based TsallisThresholding Selection Procedure for Image Segmentation," International Journal of Computer Applications, Vol. 5, No. 4, pp. 39-46, 2010.

      [24] T. Hongmei, W. Cuixia, H. Liying, and W. Xia, "Image Segmentation Based on Improved PSO," the proceedings of the International Conference on Computer and Communication Technologies in Agriculture Engineering(CCTAE2010), pp. 191-194, 2010.

      [25] Y. Shi, and R. Eberhart, "A modified particle swarm optimizer," in the Proceedings of the IEEE International Conference on Evolutionary Computation, Piscataway, NJ, pp. 69-73, 1998.

      [26] Liu J., Yang Y. H., "Multiresolution Color Image Segmentation," IEEE Trans. on PAMI, Vol. 16, No. 7, pp. 689-700, 1994.

      [27] E.J.S. Pires, J.A.T. Machado, P.B.M. Oliveira, J.B. Cunha, L. Mendes, “Particle swarm optimization with fractional-order velocity,†Journal on Nonlinear Dynamics, vol. 61, pp. 295–301,2010.

      [28] J. Fan, M. Han, and J. Wang, “Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation,†Pattern Recognition, vol. 42 (2009), pp. 2527 – 2540, 2009.

      [29] K. Hammouche, M. Diaf, and P. Siarry, “A comparative study of various meta-heuristic techniques applied to the multilevel thresholding problem,†Engineering Applications of Artificial Intelligence, vol. 23 (2010), pp. 676–688, 2010.

      [30] M. Jiang, Y.P. Luo, and S.Y. Yang, “Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm,†Information Processing Letters, vol. 102, no. 1, pp. 8-16, 2007.

      [31] K. Yasuda, N. Iwasaki, G. Ueno, and E. Aiyoshi, “Particle Swarm Optimization: A Numerical Stability Analysis and Parameter Adjustment Based on Swarm Activity,†IEEJ Transactions on Electrical and Electronic Engineering, Wiley InterScience, vol. 3, pp. 642-659, 2008.

      [32] Md Zia Ur Rahman, B.Malakonda Reddy, “Efficient SAR Image Segmentation Techniques using Biasfield Estimationâ€,

      Journal of Scientific and Industrial Research, vol. 76, pp. 335- 338, 2017.

      [33] M.L.M. Lakshmi, K.Rajkamal, S.V.A.V.Prasad, Md.Zia Ur Rahman, “Amplitude Only Linear Array Synthesis With Desired Nulls Using Evolutionary Computing Techniqueâ€, The Applied of Computational Electromagnetics Society Journal, vol.31, no.11, pp. 1357-1361, November, 2016

      [34] P.V.V. Kishore, A.S.C.S. Sastry, Md. Zia Ur Rahman, “Double Technique for Improving Ultrasound Medical Imagesâ€, Journal of Medical Imaging and Health Informatics, vol.6, no.3, pp.667-675, 2016.

      [35] M. Lakshmi, Md Zia Ur Rahman, “Efficient Speckle Noise Reduction Techniques for Synthetic Aperture Radars in Remote Sensing Applicationsâ€, International Review of Aerospace Engineering Vol.9, no.10, 2016, pp.114-122.

      [36] M. Lakshmi, Md Zia Ur Rahman, “Analysis of Synthetic Aperture Radar Images using Brute Force Thresholding and Gradient Guide Filtersâ€, Journal of Theoretical and Applied Information Technology,Vol.93, no.1, 2016, pp.152-163.

      [37] B. Mala Konda Reddy, Md. Zia Ur Rahman, “Novel Segmentation Technique for Target Tracking in Synthetic Aperture Radarsâ€, International Journal of Control Theory and Applications,Vol.10, no.35, 2017, pp.335-341.

      [38] Y. Murali Krishna, Md. Zia Ur Rahman and Dr B.V. Rama Mohana Rao, “Beam Steering in Smart Antennas using an Efficient Adaptive Signal Processing Algorithm,†International Journal of Research and Reviews in Signal Acquisition and Processing, Vol. 1(3), Sep. 2011.

      [39] K. Murali Krishna, Md. Zia Ur Rahman, “Lung Parenchyma Detection using Levelset Segmentationâ€, International Journal of Control Theory and Applications, Vol.10, no.35, 2017, pp.207-215.

      [40] K. Sarath Kumar, Md. Zia Ur Rahman, “A New Computation Method for Pointing Accuracy of Cassegrain Antenna in Satellite Communicationâ€, Journal of Theoretical and Applied Information Technology,Vol.95, no.13, 2017, pp.3062-3074.

      [41] Md. Zia Ur Rahmna, K. Murali Krishna, “Efficient Adaptive Beamforming Algorithms for Smart Antennasâ€, International Journal of Control Theory and Applications,Vol.10, no.35, 2017, pp.173-181.

      [42] Md. Zia Ur Rahman, et al., “A Low Complex adaptive algorithm for Antenna beam steeringâ€, IEEE 2011 International Conference on Signal Processing, Communications, Computing and Networking Technology (ICSCCN 2011), ISBN: 978-1-61284-653-8, pp.317-321, 2011.

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  • How to Cite

    Malakonda Reddy, B., & Zia Ur Rahman, M. (2018). Novel Sgmentation Technique for Synthetic Aperture Radar Target Tracking using Hybrid PSO Method. International Journal of Engineering & Technology, 7(2.17), 95-100. https://doi.org/10.14419/ijet.v7i2.17.11566

    Received date: 2018-04-15

    Accepted date: 2018-04-15

    Published date: 2018-04-15