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    Automated Processing of Sea Surface Images for the Determination of Whitecap Coverage

    Source: Journal of Atmospheric and Oceanic Technology:;2009:;volume( 026 ):;issue: 002::page 383
    Author:
    Callaghan, Adrian H.
    ,
    White, Martin
    DOI: 10.1175/2008JTECHO634.1
    Publisher: American Meteorological Society
    Abstract: Sea surface images have been collected to determine the percentage whitecap coverage (W) since the late 1960s. Image processing methods have changed dramatically since the beginning of whitecap studies. An automated whitecap extraction (AWE) technique has been developed at the National University of Ireland, Galway, that allows images to be analyzed for percentage whitecap coverage without the need of a human analyst. AWE analyzes digital images and determines a suitable threshold with which whitecaps can be separated from unbroken background water. By determining a threshold for each individual image, AWE is suitable for images obtained in conditions of changing ambient illumination. AWE is also suitable to process images that have been taken from both stable and nonstable platforms (such as towers and research vessels, respectively). Using techniques based on derivative analysis, AWE provides an objective method to determine an appropriate threshold for the identification of whitecaps in sea surface images without the need for a human analyst. The automated method allows large numbers of images to be analyzed in a relatively short amount of time. AWE can be used to analyze hundreds of images per individual W data point, which produces more convergent values of W.
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      Automated Processing of Sea Surface Images for the Determination of Whitecap Coverage

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4209245
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    • Journal of Atmospheric and Oceanic Technology

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    contributor authorCallaghan, Adrian H.
    contributor authorWhite, Martin
    date accessioned2017-06-09T16:25:54Z
    date available2017-06-09T16:25:54Z
    date copyright2009/02/01
    date issued2009
    identifier issn0739-0572
    identifier otherams-67762.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4209245
    description abstractSea surface images have been collected to determine the percentage whitecap coverage (W) since the late 1960s. Image processing methods have changed dramatically since the beginning of whitecap studies. An automated whitecap extraction (AWE) technique has been developed at the National University of Ireland, Galway, that allows images to be analyzed for percentage whitecap coverage without the need of a human analyst. AWE analyzes digital images and determines a suitable threshold with which whitecaps can be separated from unbroken background water. By determining a threshold for each individual image, AWE is suitable for images obtained in conditions of changing ambient illumination. AWE is also suitable to process images that have been taken from both stable and nonstable platforms (such as towers and research vessels, respectively). Using techniques based on derivative analysis, AWE provides an objective method to determine an appropriate threshold for the identification of whitecaps in sea surface images without the need for a human analyst. The automated method allows large numbers of images to be analyzed in a relatively short amount of time. AWE can be used to analyze hundreds of images per individual W data point, which produces more convergent values of W.
    publisherAmerican Meteorological Society
    titleAutomated Processing of Sea Surface Images for the Determination of Whitecap Coverage
    typeJournal Paper
    journal volume26
    journal issue2
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/2008JTECHO634.1
    journal fristpage383
    journal lastpage394
    treeJournal of Atmospheric and Oceanic Technology:;2009:;volume( 026 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian