Spatio-temporal contextual image classification based on spatial AdaBoost

Ryuei Nishii, Shinto Eguchi

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 引用 (Scopus)

抜粋

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.

元の言語英語
ホスト出版物のタイトル25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium
ページ172-175
ページ数4
1
DOI
出版物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, 大韓民国
継続期間: 7 25 20057 29 2005

その他

その他2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005
大韓民国
Seoul
期間7/25/057/29/05

All Science Journal Classification (ASJC) codes

  • Geology
  • Software

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  • これを引用

    Nishii, R., & Eguchi, S. (2005). Spatio-temporal contextual image classification based on spatial AdaBoost. : 25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium (巻 1, pp. 172-175). [1526132] https://doi.org/10.1109/IGARSS.2005.1526132