Cloud classification of satellite image performed in two stages

Hiroshi Ikeda*, Mitsuharu Matsumoto, Shuji Hashimoto


    研究成果: Conference contribution

    1 被引用数 (Scopus)


    To understand a comprehensive atmospheric state, it is important to classify clouds in satellite images into appropriate classes. Many researches utilizing various features concerning the cloud texture have been reported in cloud classification. However, some clouds can not be classified uniquely only with the texture features. According to the knowledge of the experts, they classify the clouds in two stages. They firstly categorize the clouds into the provisional classes according to the brightnesses of the satellite images. They then classify each provisional class into the objective class based on the texture, shape and velocity of the cloud employing the meteorological knowledge about the time and location of the image. In this paper, we propose a novel method for the cloud classification that consists of two stages and utilizes cloud movement as human experts adopt. We firstly classify the clouds into 20 classes based on their brightnesses of the two-band spectral images. We then closely analyze the classes according to five features such as the brightnesses, deviations of brightness and cloud velocity estimated by varying window size adaptively. The experimental results are shown to verify the proposed method.

    ホスト出版物のタイトルProceedings of SPIE - The International Society for Optical Engineering
    出版ステータスPublished - 2007
    イベントImage Processing: Algorithms and Systems V - San Jose, CA
    継続期間: 2007 1月 292007 1月 30


    OtherImage Processing: Algorithms and Systems V
    CitySan Jose, CA

    ASJC Scopus subject areas

    • 電子工学および電気工学
    • 凝縮系物理学


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