写真測量とリモートセンシング
Online ISSN : 1883-9061
Print ISSN : 0285-5844
ISSN-L : 0285-5844
スケーリングを目的とするミクセル推定におけるカテゴリ分解法と回帰推定法の比較
竹内 章司稲永 麻子
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ジャーナル フリー

1998 年 37 巻 1 号 p. 29-34

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抄録
The authors tested the applicability of category decomposition method based on the linear mixture model for the fusion of multipleresolution satellite data such as Landsat-TM and NOAA-AVHRR. The goal of the application of this method is to estimate the mixing ratio of different categories within one pixel of the lower-resolution data using the classification result of the higher-resolution data, which is considered to be useful for the extrapolation of the information from the higher-resolution data over the wider coverage of the lower-resolution data. The authors tested the estimation accuracy by two kinds of decomposition methods, the maximum likelihood estimation and the minimum distance estimation and also by the multiple regression method. The experimental results showed that the most adequate estimation was obtained by the category decomposition based on the minimum distance estimation.
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© 社団法人 日本写真測量学会
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