抄録
There have been some new developments of an interactive analysis for the multi-spectral images. Recently the authors have proposed an interactive analysis method for classification using a Hilbert curve which is a one-to-one mapping and takes a neighborhood between N-dimensional space and one-dimensional space into consideration. In order to analyze large scale multi-spectral images, we divide a large scale image into subimages which can be analyzed using our proposed method. A problem is that after classifying one of the subimages, how we classify the rest of the subimages using this result effectively. We present a solution of this problem using a tree structure expression. We assign a reliability measure to each pixels on the rest. The reliability measure is based on a distance from a center of a cluster, and the center is considered occurrence information. For the low reliable data, we apply our interactive analysis method for classification again. In the experiment using a LANDSAT image data, We confirmed the effectiveness of the reliability measure because category boundaries on the rest have lower reliability.
本文言語 | English |
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ページ | 1017-1019 |
ページ数 | 3 |
出版ステータス | Published - 1995 1月 1 |
外部発表 | はい |
イベント | Proceedings of the 1995 International Geoscience and Remote Sensing Symposium. Part 3 (of 3) - Firenze, Italy 継続期間: 1995 7月 10 → 1995 7月 14 |
Other
Other | Proceedings of the 1995 International Geoscience and Remote Sensing Symposium. Part 3 (of 3) |
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City | Firenze, Italy |
Period | 95/7/10 → 95/7/14 |
ASJC Scopus subject areas
- コンピュータ サイエンスの応用
- 地球惑星科学(全般)