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Volume 7 Issue 4

Oct.  1990

Article Contents

Delineation of Mesoscale Features of Ocean on Satellite IR Image


doi: 10.1007/BF03008872

  • An ICSED (Improved Cluster Shade Edge-Detection) algorithm and a series of post-processing technique are discussed for automatic delineation of mesoscale structure of the ocean on digital IR images. The popular derivative-based edge operators are shown to be too sensitive to edge fine-structure and to weak gradients. The new edge-detection algorithm is ICSED (Improved Cluster Shade Edge-detection) method and it is found to he an excel-lent edge detector that exhibits the characteristic of fine-structure rejection while retaining edge sharpness. This characteristic is highly desirable for analyzing oceanographic satellite images. A sorting technique for separating clouds or land well from ocean at both day and night is described in order to obtain high quality mesoscale features on the IR image. This procedure is evaluated on an AVHRR (Advanced Very High Resolution Radiometer) image with Kuroshio. Results and analyses show that the mesoscale features can be well identified by using ICSED algorithm.
  • [1] Li Jun, Zhou Fengxian, 1992: On Accurate Detection of Oceanic Features from Satellite IR Data Using ICSED Method, ADVANCES IN ATMOSPHERIC SCIENCES, 9, 373-382.  doi: 10.1007/BF02656948
    [2] Li Jun, Zhou Fengxian, Gao Qinghuai, 1991: Satellite Data Reduction Using Entropy-preserved Image Compression Technique, ADVANCES IN ATMOSPHERIC SCIENCES, 8, 237-242.  doi: 10.1007/BF02658097
    [3] Jiang Shangcheng, Ye Qian, Yang Xifeng, An Gang, Xiangqiang Wu, 2000: Climatological Features of the Global Tropical Subsidence Region Based on Satellite Observations, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 391-402.  doi: 10.1007/s00376-000-0031-8
    [4] LIU Chuanxi, LIU Yi, Xiong LIU, Kelly CHANCE, 2013: Dynamical and Chemical Features of a Cutoff Low over Northeast China in July 2007: Results from Satellite Measurements and Reanalysis, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 525-540.  doi: 10.1007/s00376-012-2086-8
    [5] Yi-Xuan SHOU, Feng LU, Hui LIU, Peng CUI, Shaowen SHOU, Jian LIU, 2019: Satellite-based Observational Study of the Tibetan Plateau Vortex: Features of Deep Convective Cloud Tops, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 189-205.  doi: 10.1007/s00376-018-8049-y
    [6] Haoya LIU, Weibiao LI, Shumin CHEN, Rong FANG, Zhuo LI, 2018: Atmospheric Response to Mesoscale Ocean Eddies over the South China Sea, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 1189-1204.  doi: 10.1007/s00376-018-7175-x
    [7] Shaowu BAO, Lian XIE, Sethu RAMAN, 2004: A Numerical Study of a TOGA-COARE Squall-Line Using a Coupled Mesoscale Atmosphere-Ocean Model, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 708-716.  doi: 10.1007/BF02916368
    [8] Jincheng WANG, Xingwei JIANG, Xueshun SHEN, Youguang ZHANG, Xiaomin WAN, Wei HAN, Dan WANG, 2023: Assimilation of Ocean Surface Wind Data by the HY-2B Satellite in GRAPES: Impacts on Analyses and Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 44-61.  doi: 10.1007/s00376-022-1349-2
    [9] Jun LI, Wei HAN, 2017: A Step Forward toward Effectively Using Hyperspectral IR Sounding Information in NWP, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 1263-1264.  doi: 10.1007/s00376-017-7167-2
    [10] LIU Liping, Qin XU, Pengfei ZHANG, Shun LIU, 2008: Automated Detection of Contaminated Radar Image Pixels in Mountain Areas, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 778-790.  doi: 10.1007/s00376-008-0778-x
    [11] Myoung-Hwan AHN, Eun-Ha SOHN, Byong-Jun HWANG, 2003: A New Algorithm for Sea Fog/Stratus Detection Using GMS-5 IR Data, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 899-913.  doi: 10.1007/BF02915513
    [12] LI Pingyang, JIANG Weimei, SUN Jianning, YUAN Renmin, 2003: A Laboratory Modeling of the Velocity Field in the Convective Boundary Layer with the Particle Image Velocimetry Technique, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 631-637.  doi: 10.1007/BF02915506
    [13] Chao LIU, Shu YANG, Di DI, Yuanjian YANG, Chen ZHOU, Xiuqing HU, Byung-Ju SOHN, 2022: A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1994-2007.  doi: 10.1007/s00376-021-0366-x
    [14] CHEN Lianshou, LUO Zhexian, 2004: Interaction of Typhoon and Mesoscale Vortex, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 515-528.  doi: 10.1007/BF02915719
    [15] PENG Jiayi, FANG Juan, WU Rongsheng, 2004: Interaction of Mesoscale Convection and Frontogenesis, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 814-823.  doi: 10.1007/BF02916377
    [16] MA Leiming, DUAN Yihong, ZHU Yongti, 2004: The Structure and Rainfall Features of Tropical Cyclone Rammasun (2002), ADVANCES IN ATMOSPHERIC SCIENCES, 21, 951-963.  doi: 10.1007/BF02915597
    [17] Ge Ling, Liang Jiaxing, Chen Yiliang, 1996: Spatial / Temporal Features of Antarctic Climate Change, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 375-382.  doi: 10.1007/BF02656854
    [18] Jo-Han LEE, Dong-Kyou LEE, Hyun-Ha LEE, Yonghan CHOI, Hyung-Woo KIM, 2010: Radar Data Assimilation for the Simulation of Mesoscale Convective Systems, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1025-1042.  doi: 10.1007/s00376-010-9162-8
    [19] LIU Jianyong, TAN Zhe-Min, 2009: Mesoscale Predictability of Mei-yu Heavy Rainfall, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 438-450.  doi: 10.1007/s00376-009-0438-9
    [20] Jing YANG, Gaopeng LU, Ningyu LIU, Haihua CUI, Yu WANG, Morris COHEN, 2017: Analysis of a Mesoscale Convective System that Produced a Single Sprite, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 258-271.  doi: 10.1007/s00376-016-6092-0

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Manuscript History

Manuscript received: 10 October 1990
Manuscript revised: 10 October 1990
通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Delineation of Mesoscale Features of Ocean on Satellite IR Image

  • 1. Institute of Atmospheric Physics, Academia Sinica, Beijing 100029,Institute of Atmospheric Physics, Academia Sinica, Beijing 100029,Information Science Center, Peking University, Beijing 100871

Abstract: An ICSED (Improved Cluster Shade Edge-Detection) algorithm and a series of post-processing technique are discussed for automatic delineation of mesoscale structure of the ocean on digital IR images. The popular derivative-based edge operators are shown to be too sensitive to edge fine-structure and to weak gradients. The new edge-detection algorithm is ICSED (Improved Cluster Shade Edge-detection) method and it is found to he an excel-lent edge detector that exhibits the characteristic of fine-structure rejection while retaining edge sharpness. This characteristic is highly desirable for analyzing oceanographic satellite images. A sorting technique for separating clouds or land well from ocean at both day and night is described in order to obtain high quality mesoscale features on the IR image. This procedure is evaluated on an AVHRR (Advanced Very High Resolution Radiometer) image with Kuroshio. Results and analyses show that the mesoscale features can be well identified by using ICSED algorithm.

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