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一种改进的ACM算法及其在鄱阳湖水域监测中的应用

冷英 刘忠玲 张衡 王宇 李宁

冷英, 刘忠玲, 张衡, 王宇, 李宁. 一种改进的ACM算法及其在鄱阳湖水域监测中的应用[J]. 电子与信息学报, 2017, 39(5): 1064-1070. doi: 10.11999/JEIT160870
引用本文: 冷英, 刘忠玲, 张衡, 王宇, 李宁. 一种改进的ACM算法及其在鄱阳湖水域监测中的应用[J]. 电子与信息学报, 2017, 39(5): 1064-1070. doi: 10.11999/JEIT160870
LENG Ying, LIU Zhongling, ZHANG Heng, WANG Yu, LI Ning. Improved ACM Algorithm for Poyang Lake Monitoring[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1064-1070. doi: 10.11999/JEIT160870
Citation: LENG Ying, LIU Zhongling, ZHANG Heng, WANG Yu, LI Ning. Improved ACM Algorithm for Poyang Lake Monitoring[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1064-1070. doi: 10.11999/JEIT160870

一种改进的ACM算法及其在鄱阳湖水域监测中的应用

doi: 10.11999/JEIT160870
基金项目: 

国家自然科学基金优秀青年基金(61422113)

Improved ACM Algorithm for Poyang Lake Monitoring

Funds: 

The National Natural Science Fund of China for Excellent Young Scholars (61422113)

  • 摘要: Sentinel-1合成孔径雷达(SAR)卫星具有测绘带宽、重访周期短、分辨率高等优点,为长时间的水域监测提供数据基础。2016年长江中下游地区洪涝灾害严重,鄱阳湖是长江干流的重要调蓄性湖泊之一,基于SAR图像的鄱阳湖水域提取及其变化检测具有重要意义。然而受相干斑噪声的影响,尤其是在鄱阳湖分布较广、地物背景较复杂、弱边缘和模糊边缘较多的情况下,传统的水域分割方法边缘保持性较差、提取精度较低。针对上述问题,该文提出一种基于局部窄带的ACM边缘提取算法,并将其应用于Sentinel-1A获取的鄱阳湖水域时序观测图像中。该算法首先采用两级Otsu方法获取初始轮廓,随后在初始轮廓附近建立局部窄带,最后在窄带内采用基于区域的ACM方法进行轮廓线演化来解决弱边缘或模糊边缘问题。实验结果表明该方法在边缘保持和分割精度上具有明显优势,并且降低了计算时间。
  • YESOU H, HUBER C, HAOUET S, et al. Exploiting sentinel 1 time series to monitor the largest fresh water bodies in PR China, the Poyang lake[C]. IEEE International Geoscience and Remote Sensing Symposium, Beijing, China, 2016: 3882-3885. doi: 10.1109/IGARSS.2016.7730008.
    ZHANG P, FENG L, LU J Z, et al. Hydrodynamic and inundation modeling of Chinas largest freshwater lake aided by remote sensing data[J]. Remote Sensing, 2015, 7(4): 4858-4879. doi: 10.3390/rs70404858.
    LAI X J, SHANKMAN D, HUBER C, et al. Sand mining and increasing Poyang Lakes discharge ability: A reassessment of causes for lake decline in China[J]. Journal of Hydrology, 2014, 519(1): 1698-1706. doi: 10.1016/j.jhydrol.2014.09.058.
    YE X C, ZHANG Q, LIU J, et al. Distinguishing the relative impacts of climate change and human activities on variation of streamflow in the Poyang Lake catchment, China[J]. Journal of Hydrology, 2013, 494(12): 83-95. doi: 10.1016 /j.jhydrol.2013.04.036.
    FENG L, HU C, CHEN X, et al. Dramatic inundation changes of Chinas two largest freshwater lakes linked to the Three Gorges Dam[J]. Environmental Science and Technology, 2013, 47(17): 9628-9634. doi: 10.1021/es4009618.
    FENG L, HU C M, HAN X X, et al. Long-term distribution patterns of Chlorophyll-a concentration in Chinas largest freshwater lake: MERIS full-resolution observations with a practical approach[J]. Remote Sensing, 2015, 7(1): 275-299. doi: 10.3390/rs70100275.
    LI L, XIA H, LI Z, et al. Temporal-spatial evolution analysis of lake size-distribution in the middle and lower Yangtze river basin using Landsat imagery data[J]. Remote Sensing, 2015, 7(8): 10364-10384. doi: 10.3390/rs70810364.
    安成锦, 牛照东, 李志军, 等. 典型 Otsu 算法阈值比较及其SAR 图像水域分割性能分析[J]. 电子与信息学报, 2010, 32(9): 2215-2219. doi: 10.3724/SP.J.1146.2009.01426.
    AN Chengjin, NIU Zhaodong, LI Zhijun, et al. Otsu threshold comparison and SAR water segmentation result analysis[J]. Journal of Electronics Information Technology, 2010, 32(9): 2215-2219. doi: 10.3724/SP.J.1146.2009.01426.
    SHENG G F, YANG W, DENG X P, et al. Coastline detection in synthetic aperture radar (SAR) Images by integrating watershed transformation and controllable gradient vector flow (GVF) snake model[J]. IEEE Journal of Oceanic Engineering, 2012, 37(3): 375-383. doi: 10.1109/JOE. 2012.2191998.
    颜学颖, 焦李成, 王凌霞, 等. 一种提高SAR 图像分割性能的新方法[J]. 电子与信息学报, 2011, 33(7): 1700-1705. doi: 10.3724/SP.J.1146.2010.01190.
    YAN Xueying, JIAO Licheng, WANG Lingxia, et al. New method for improving the performance of SAR image segmentation[J]. Journal of Electronics Information Technology, 2011, 33(7): 1700-1705. doi: 10.3724/SP.J.1146. 2010.01190.
    CASELLES V, KIMMEL R, and SAPIRO G. Geodesic active contours[J]. International Journal of Computer Vision, 1997, 22(1): 61-79. doi: 10.1023/A:1007979827043.
    ADALSTEINSSON D and SETHIAN J A. A fast level set method for propagating interfaces[J]. Journal of Computational Physics, 1995, 118(2): 269-277. doi: 10.1006/ jcph.1995.1098.
    ZHANG K, ZHANG L, SONG H, et al. Active contours with selective local or global segmentation: A new formulation and level set method[J]. Image Vision Computing, 2010, 28(4): 668-676. doi: 10.1016/j.imavis.2009.10.009.
    XU C, YEZZI A, and PRINCE J L. On the relationship between parametric and geometric active contours[C]. IEEE Signals, Systems and Computers, Asilomar, USA, 2000: 483-489. doi: 10.1109/ACSSC.2000.911003.
    LIU Z L, LI N, WANG R, et al. A novel region-merging approach for coastline extraction from Sentinel-1A IW mode SAR imagery[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(3): 324-328. doi: 10.1109/LGRS.2015. 2510745.
    BASELICE F and FERRAIOLI G. Unsupervised coastal line extraction from SAR images[J]. IEEE Geoscience Remote Sensing Letters, 2013, 10(6): 1350-1354. doi: 10.1109/LGRS. 2013.2241013.
    SHU Y M, LI J, and YOUSIF H. Dark-spot detection from SAR intensity imagery with spatial density thresholding for oil-spill monitoring[J]. Remote Sensing of Environment, 2010, 114(9): 2026-2035. doi: 10.1016/j.rse.2010.04.009.
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出版历程
  • 收稿日期:  2016-08-24
  • 修回日期:  2017-01-20
  • 刊出日期:  2017-05-19

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