JI Jian, LYU Xiaojia, YAO Yafeng. A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space[J]. Chinese Journal of Electronics, 2017, 26(4): 883-888. doi: 10.1049/cje.2017.06.018
Citation: JI Jian, LYU Xiaojia, YAO Yafeng. A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space[J]. Chinese Journal of Electronics, 2017, 26(4): 883-888. doi: 10.1049/cje.2017.06.018

A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space

doi: 10.1049/cje.2017.06.018
Funds:  This work was supported by the Fundamental Research Funds for the Central Universities of China (No.160302).
  • Received Date: 2015-06-22
  • Rev Recd Date: 2016-07-21
  • Publish Date: 2017-07-10
  • This paper proposes a new SAR image segmentation method based on graph and gray level reduction in Independent component analysis (ICA) space. Firstly, according to the grayscale information of SAR image, effective use of gray level reduction for initial segmentation can group the pixels with same or similar values to the same homogeneous region, which can address the problem of over-segmentation. Secondly, the features of regions are extracted in ICA space, and then the similarity degree can be calculated by Euclidean distance. The initial regions are merged in fully connected graph based on minimum spanning tree in ICA space. The process of region merging is divided into two phases; the first phrase is merging the different regions with the largest similarity degree, the second will focus on updating the fully connected graph for iteration. Finally, experimental and comparative results on synthetic and real SAR images verify the efficiency of the proposed algorithm.
  • loading
  • A.E. Zaart, D. Ziou, S. Wang, et al., Huang, “Segmentation of SAR images”, Pattern Recongnition, Vol.35, No.3, pp.713-724, 2002.
    S.M. Bedawi and M.S. Kamel, “A comparative study of clustering methods for urban areas segmentation from high resolution remote sensing image”, Proceedings of 9th International Conference on Intelligent Systems Design and Applications (ISDA), Pisa, pp.169-174, 2009.
    N. Bonnet, J. Cutrona and M. Herbin, “A ‘no-threshold’ histogram-based image segmentation method”, Pattern Recongnition, Vol.35, No.10, pp.2319-2322, 2002.
    B. Sumengen and B. S. Manjunath, “Graph partitioning active contours (GPAC) for image segmentation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.28, No.4, pp.509-521, 2013.
    H. Yao, Q. Duan, D. Li, et al., “An improved K means clustering algorithm for fish image segmentation”, Mathematical and Computer Modeling, Vol.58, No.3, pp.790-798, 2013.
    G.L. Shapiro and C.G. Stockman, Computer Vision, New Jersey, Prentice-Hall, pp.279-325, 2001.
    A. Jurio, D. Paternain, M. Pagola, et al., “Image thresholding by grouping functions: Application to MRI images”, Recent Developments and New Directions in Soft Computing, Springer International Publishing, pp.195-208, 2014.
    J. Kittler and J. Illingworth, “Minimum error thresholding”, Pattern Recognition, Vol.19, No.1, pp.41-47, 1986.
    W. Doyle, “Operation useful for similarity”, Invariant Pattern Recognition, Vol.9, No.2, pp.259-267, 1962.
    J.C. Yen, F.J. Chang and S. Chang, “A new criterion for automatic multilevel thresholding”, IEEE Transactions on Imaging Processing, Vol.4, No.3, pp.370-378, 1995.
    Q. Guo, L. Wang and S. Shen, “Multiple-channel local binary fitting model for medical image segmentation”, Chinese Journal of Electronics, Vol.24, No.4, pp.802-806, 2015.
    L. Hu, Y. JI, P. Hou, et al., “A novel SAR image segmentation method using run-length grouping”, Chinese Journal of Electronics, Vol.22, No.2, pp.396-400, 2013.
    L.Y. Ma and J. Yu, “A convex approach for local statistics based region segmentation”, Chinese Journal of Electronics, Vol.21, No.4, pp.623-626, 2012.
    X. Deng and Y. MA, “PCNN model analysis and its automatic parameters determination in image segmentation and edge detection”, Chinese Journal of Electronics, Vol.23, No.1, pp.97-103, 2014.
    S.H. Kwok and A.G. Constantinides, “A fast recursive shortest spanning tree for image segmentation and edge detection”, IEEE Transactions on Imaging Processing, Vol.6, No.2, pp.328-332, 1997.
    S. Jianbo and M. Jitendra, “Normalized cuts and image segmentation”, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.22, No.8, pp.888-905, 2000.
    Z. Wu and R. Leahy, “An optimal graph theoretic approach to data clustering: theory and its application to image segmentation”, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.15, No.11, pp.1101-1113, 1993.
    B. Banerjee, S. Varma, K.M. Buddhiraju et al., “Unsupervised multi-spectral satellite image segmentation combining modified mean-shift and a new minimum spanning tree based clustering technique”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.7, No.3, pp.888-894, 2014.
    M.K. Quweider, J.D. Scargle and B. Jackson, “Grey level reduction for segmentation, thresholding and binarisation of images based on optimal partitioning on an interval”, IET Image Processing, Vol.1, No.2, pp.103-111, 2007.
    C. Liu and J. Yang, “ICA color space for pattern recognition”, IEEE Trans. Neural Network, Vol.20, No.2, pp.248-257, 2009.
    X. Zhang and C.H. Chen, “A new independent component analysis (ICA) method and its application to SAR images”, Neural Networks for Signal Processing XI, Proceedings of the IEEE Signal Processing Society Workshop, pp.283-292, 2001.
    A. Hyvrinen and E. Qja, “Independent component analysis: Algorithm and applications”, Neural Network, Vol.13, No.4, pp.411-430, 2000.
    A. Rezvanifar and M. Khosravifard, “Including the size of regions in image segmentation by region-based graph”, IEEE Transactions on Imaging Processing, Vol.23, No.2, pp.635-644, 2014.
    Y.C. Mei, L.K.Wei and Y.K.Wei, “Graph based image segmentation using K means clustering and normalized cuts”, CICSyN, Proceeding 4th International Conference, pp.307-312, 2012.
    F.U. Siddiqui and N.A.M. Isa, “Enhanced moving K means (EMKM) algorithm for image segmentation”, IEEE Trans. Consumer Electronics, Vol.57, No.2, pp.833-841, 2011.
    Y. Faliu and M. Inkyu, “Image segmentation: a survey of graph cut methods”, International Conference on Systems and Informatics (ICSAI), Yantai, pp.1936-1941, May, 2012.
    R. Achanta, A. Shaji, K. Smith et al., “Slic superpixels”, École Polytechnique Fédéral de Lausssanne (EPFL), Technical Report, 2010.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (136) PDF downloads(359) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return