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[An algorithm for highlightling structure in multispectral remote sensing].
Wang, Qin-Jun; Lin, Qi-Zhong; Li, Ming-Xiao; Wei, Yong-Ming; Wang, Li-Ming.
Afiliação
  • Wang QJ; Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China. wangqin08262002@yahoo.com.cn
Guang Pu Xue Yu Guang Pu Fen Xi ; 29(7): 1950-3, 2009 Jul.
Article em Zh | MEDLINE | ID: mdl-19798979
Based on the principle of mineral generation, structures could provide not only passage ways for ore-forming fluid, but also space for them to aggregate. So, it was very important to study the feature of structures in study area before mineral exploration. In order to highlight structures using multispectral remote sensing data, an algorithm integrating principle component analysis (PCA), maximum noise fraction transformation (MNF) and original image data was proposed here. In the algorithm, the original image was firstly transformed by PCA and MNF; then all bands were normalized to reduce errors caused by different band dimensions, and three bands containing detailed structure information were selected to form the false color image in which structures in study area were highlighted. Results of transformation on enhanced thematic mapper (ETM) data acquired on June 27th 2000 in Hatu area, Xinjiang province, China showed that (1) the transformed image was not only more colorful than the original data, but also more gradational than the original data. (2) The color difference among objects was enhanced by the algorithm. (3) Structrues were highlighted by the algorithm. Therefore, the algorithm's effect of highlighting structures in study area was noticeable.
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Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Guang Pu Xue Yu Guang Pu Fen Xi Ano de publicação: 2009 Tipo de documento: Article País de afiliação: China País de publicação: China
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Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Guang Pu Xue Yu Guang Pu Fen Xi Ano de publicação: 2009 Tipo de documento: Article País de afiliação: China País de publicação: China