Spatio-temporal contextual image classification based on spatial AdaBoost

Ryuei Nishii, Shinto Eguchi

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

Spatial AdaBoost proposed by Nishii and Eguchi (TGRS 2005) is a contextual supervised classifier of land-cover categories of geostatistical data. It shows an excellent performance similar to that of the MRF-based classifier with much less computational cost. In this paper, we extend the method to the setup with multi spatio-temporal images. We take classification functions by the averages of log posterior probabilities derived by respective training data sets. The functions are sequentially combined by minimizing the empirical exponential risk calculated over samples in all the training data sets. Thus, we obtain a classifier based on a convex combination of the functions. The proposed method is applied to artificial data, and it shows performance similar to that of Spatial AdaBoost based on much larger training data.

本文言語英語
ホスト出版物のタイトル25th Anniversary IGARSS 2005
ホスト出版物のサブタイトルIEEE International Geoscience and Remote Sensing Symposium
ページ172-175
ページ数4
DOI
出版ステータス出版済み - 2005
イベント2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005 - Seoul, 韓国
継続期間: 7月 25 20057月 29 2005

出版物シリーズ

名前International Geoscience and Remote Sensing Symposium (IGARSS)
1

その他

その他2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005
国/地域韓国
CitySeoul
Period7/25/057/29/05

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンスの応用
  • 地球惑星科学一般

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