Development of Remote Sensing Software Based on Hyperspectral Imaging Framework
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- Okamoto Hiroshi
- Graduate School of Agriculture, Hokkaido University
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- Sakai Kenshi
- Institute of Symbiotic Science and Technology, Tokyo University of Agriculture and Technology
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- Murata Tetsuro
- Graduate School of Agriculture, Hokkaido University
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- Kataoka Takashi
- Graduate School of Agriculture, Hokkaido University
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- Hata Shun-ich
- Graduate School of Agriculture, Hokkaido University
Bibliographic Information
- Other Title
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- ハイパースペクトル画像解析フレームワークを利用したリモートセンシングソフトウェアの開発
- ハイパースペクトル ガゾウ カイセキ フレームワーク オ リヨウ シタ リモートセンシングソフトウェア ノ カイハツ
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Abstract
The purpose of this study is to develop application software for various hyperspectral imaging analyses in agricultural sensing and ecosystem observation. As previously reported, we constructed a software framework for hyperspectral imaging. A number of common hyperspectral image processing algorithms are available in this framework. Custom analytical software for specialized sensing tasks can be efficiently developed using the framework. Spectral processing algorithms can be switched through polymorphism, a standard object-oriented programming mechanism. Analytical software developers need only write the specialized portion of the program code that implements their spectral processing algorithm; the framework handles the common tasks. In this study, six spectral processors (for waveband extraction, false color generation, data normalization, segmentation between plant and soil, SPAD estimation, and for plant classification) were experimentally developed as examples of spectral processor development. In addition, data sampling software that can be used to obtain waveband images and pixel spectral data was developed.
Journal
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- Agricultural Information Research
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Agricultural Information Research 15 (3), 219-229, 2006
Japanese Society of Agricultural Informatics
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Keywords
Details 詳細情報について
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- CRID
- 1390282679437554816
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- NII Article ID
- 130000115756
- 30027761119
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- NII Book ID
- AN10481161
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- ISSN
- 18815219
- 09169482
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- NDL BIB ID
- 8599393
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed