Interactive analysis of large scale multi-spectral images using a Hilbert curve

Michiharu Niimi, Sei ichiro Kamata, Eiji Kawaguchi

研究成果: Paper査読

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
ページ1017-1019
ページ数3
出版ステータスPublished - 1995 1 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 101995 7 14

Other

OtherProceedings of the 1995 International Geoscience and Remote Sensing Symposium. Part 3 (of 3)
CityFirenze, Italy
Period95/7/1095/7/14

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)

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