Knowledge - Based Enhancement of Low Spatial Resolution Images

• LI Xiao-Zheng

  the Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University

• KUDO Mineichi

  the Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University

• TOYAMA Jun

  the Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University

• SHIMBO Masaru

  the Division of Systems and Information Engineering, Graduate School of Engineering, Hokkaido University

抄録

Many image-processing techniques are based on texture features or gradation features of the image. However, Landsat images are complex; they also include physical features of reflection radiation and heat radiation from land cover. In this paper, we describe a method of constructing a super-resolution image of Band 6 of the Landsat TM sensor, oriented to analysis of an agricultural area, by combining information(texture features, gradation features, physical features)from other bands. In this method, a knowledge-based hierarchical classifier is first used to identify land cover in each pixel and then the least-squares approach is applied to estimate the mean temperature of each type of land cover. By reassigning the mean temperature to each pixel, a finer spatial resolution is obtained in Band 6. Computational results show the efficiency of this method.

収録刊行物

• IEICE transactions on information and systems

  IEICE transactions on information and systems 81 (5), 457-463, 1998-05-25

  一般社団法人電子情報通信学会

キーワード

• remote-sensing image
• super-resolution method
• image processing
• knowledge-based classifier

詳細情報

• CRID: 1572824502217611008
• NII論文ID: 110003209985
• NII書誌ID: AA10826272
• ISSN: 09168532
• 本文言語コード: en
• データソース種別:
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