Laser & Optoelectronics Progress, Volume. 57, Issue 22, 222801(2020)

Super-Pixel Segmentation of Remote Sensing Image Based on Improved Simple Linear Iterative Clustering Algorithm

Xinlei Ren1、* and Yangping Wang1,2,3,4
Author Affiliations
  • 1School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • 2National Experimental Teaching Demonstration Center of Computer Science and Technology, Lanzhou Jitotong University, Lanzhou, Gansu 730070, China
  • 3Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, Lanzhou, Gansu 730070, China;
  • 4Gansu Provincial Key Laboratory of System Dynamics and Reliability of Rail Transport Equipment, Lanzhou, Gansu 730070, China
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    References(24)

    [1] Li P, Yang Y, Fang T. A fast superpixel algorithm with biased-clustering using visual saliency[J]. Journal of Xi'an Jiaotong University, 49, 112-117, 138(2015).

    [3] Ren X, Malik J. Learning a classification model for segmentation. [C]//Proceedings Ninth IEEE International Conference on Computer Vision, October 13-16, 2003, Nice, France. New York: IEEE, 10-17(2003).

    [4] Wang S, Lu H, Yang F et al. Superpixel tracking. [C]//2011 International Conference on Computer Vision, November 6-13, 2011, Barcelona, Spain. New York: IEEE, 1323-1330(2011).

    [6] Comaniciu D, Meer P. Mean Shift: a robust approach toward feature space analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 603-619(2002).

    [9] Kanungo T, Mount D M, Netanyahu N S et al. An efficient K-means clustering algorithm: analysis and implementation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 881-892(2002).

    [10] Achanta R, Süsstrunk S. Superpixels and polygons using simple non-iterative clustering. [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 4895-4904(2017).

    [11] Wu C, Zhang L, Zhang H W et al. Improved superpixel-based fast fuzzy C-means clustering for image segmentation. [C]//2019 IEEE International Conference on Image Processing (ICIP), September 22-25, 2019, Taipei, Taiwan, China. New York: IEEE, 1455-1459(2019).

    [12] Vincent L, Soille P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13, 583-598(1991).

    [13] Lei T, Jia X H, Liu T L et al. Adaptive morphological reconstruction for seeded image segmentation[J]. IEEE Transactions on Image Processing, 28, 5510-5523(2019).

    [14] Lei T, Zhang Y N, Wang Y et al. A conditionally invariant mathematical morphological framework for color images[J]. Information Sciences, 387, 34-52(2017).

    [15] Levinshtein A, Stere A, Kutulakos K N et al. TurboPixels: fast superpixels using geometric flows[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 2290-2297(2009).

    [16] Gong Y J, Zhou Y C. Differential evolutionary superpixel segmentation[J]. IEEE Transactions on Image Processing, 27, 1390-1404(2018).

    [17] Wang H, Shen J B, Yin J B et al. Adaptive nonlocal random walks for image superpixel segmentation[J]. IEEE Transactions on Circuits and Systems for Video Technology, 30, 822-834(2020).

    [19] Shi J B, Malik J. Normalized cuts and image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 888-905(2000).

    [20] Moore A P. Prince S J D, Warrell J, et al. Superpixel lattices. [C]//2008 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2008, Anchorage, AK, USA. New York: IEEE, 1-8(2008).

    [21] Liu M Y, Tuzel O, Ramalingam S et al. Entropy rate superpixel segmentation. [C]//Proceedings of 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 20-25, 2011, Colorado Springs, USA. New York: IEEE, 978, 97-104(2011).

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    Xinlei Ren, Yangping Wang. Super-Pixel Segmentation of Remote Sensing Image Based on Improved Simple Linear Iterative Clustering Algorithm[J]. Laser & Optoelectronics Progress, 2020, 57(22): 222801

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Mar. 16, 2020

    Accepted: Apr. 20, 2020

    Published Online: Nov. 4, 2020

    The Author Email: Xinlei Ren (121931236@qq.com)

    DOI:10.3788/LOP57.222801

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