クラスタリングのための固有空間上での多重画像からの部分画像の選択 Subimage Selection from Multiple Image on Eigenspace for Clustering

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抄録

Clustering of multiple image such as multispectral and hyperspectral image has some challenges. First, the computational complexity increases in proportion to the number of multiple image. Second, the performance is decreased by mixed improper images. Therefore, dimensionality compression and dimensionality reduction of multiple image are needed for the computational complexity decrease and the accuracy improvement of clustering. Then, this technical report marks on dimensionality reduction of the multiple image, and proposes a method to select subimage from multiple image on the eigenspace. To validate the effectiveness of the proposed method, selection of subimage is performed using Landsat TM multispectral image. A landcover classification map which is created as the result of clustering is compared with aerial photo.

収録刊行物

  • 写真測量とリモートセンシング

    写真測量とリモートセンシング 50(5), 284-289, 2011-11-09

    一般社団法人 日本写真測量学会

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各種コード

  • NII論文ID(NAID)
    10030287112
  • NII書誌ID(NCID)
    AN00111450
  • 本文言語コード
    JPN
  • 資料種別
    NOT
  • ISSN
    02855844
  • NDL 記事登録ID
    023432649
  • NDL 請求記号
    Z16-147
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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