A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data
Multispectral and hyperspectral images are well established in various fields of application like remote sensing, astronomy, and microscopic spectroscopy. In recent years, the availability of new sensor designs, more powerful processors, and high-capacity storage further opened this imaging modality...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/2635124 |
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| author | Johannes Jordan Elli Angelopoulou Andreas Maier |
| author_facet | Johannes Jordan Elli Angelopoulou Andreas Maier |
| author_sort | Johannes Jordan |
| collection | DOAJ |
| description | Multispectral and hyperspectral images are well established in various fields of application like remote sensing, astronomy, and microscopic spectroscopy. In recent years, the availability of new sensor designs, more powerful processors, and high-capacity storage further opened this imaging modality to a wider array of applications like medical diagnosis, agriculture, and cultural heritage. This necessitates new tools that allow general analysis of the image data and are intuitive to users who are new to hyperspectral imaging. We introduce a novel framework that bundles new interactive visualization techniques with powerful algorithms and is accessible through an efficient and intuitive graphical user interface. We visualize the spectral distribution of an image via parallel coordinates with a strong link to traditional visualization techniques, enabling new paradigms in hyperspectral image analysis that focus on interactive raw data exploration. We combine novel methods for supervised segmentation, global clustering, and nonlinear false-color coding to assist in the visual inspection. Our framework coined Gerbil is open source and highly modular, building on established methods and being easily extensible for application-specific needs. It satisfies the need for a general, consistent software framework that tightly integrates analysis algorithms with an intuitive, modern interface to the raw image data and algorithmic results. Gerbil finds its worldwide use in academia and industry alike with several thousand downloads originating from 45 countries. |
| format | Article |
| id | doaj-art-9376044cf0934632847ab6d7e719cef5 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-9376044cf0934632847ab6d7e719cef52025-02-03T01:04:35ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552016-01-01201610.1155/2016/26351242635124A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image DataJohannes Jordan0Elli Angelopoulou1Andreas Maier2Pattern Recognition Lab, University of Erlangen-Nuremberg, Erlangen, GermanyPattern Recognition Lab, University of Erlangen-Nuremberg, Erlangen, GermanyPattern Recognition Lab, University of Erlangen-Nuremberg, Erlangen, GermanyMultispectral and hyperspectral images are well established in various fields of application like remote sensing, astronomy, and microscopic spectroscopy. In recent years, the availability of new sensor designs, more powerful processors, and high-capacity storage further opened this imaging modality to a wider array of applications like medical diagnosis, agriculture, and cultural heritage. This necessitates new tools that allow general analysis of the image data and are intuitive to users who are new to hyperspectral imaging. We introduce a novel framework that bundles new interactive visualization techniques with powerful algorithms and is accessible through an efficient and intuitive graphical user interface. We visualize the spectral distribution of an image via parallel coordinates with a strong link to traditional visualization techniques, enabling new paradigms in hyperspectral image analysis that focus on interactive raw data exploration. We combine novel methods for supervised segmentation, global clustering, and nonlinear false-color coding to assist in the visual inspection. Our framework coined Gerbil is open source and highly modular, building on established methods and being easily extensible for application-specific needs. It satisfies the need for a general, consistent software framework that tightly integrates analysis algorithms with an intuitive, modern interface to the raw image data and algorithmic results. Gerbil finds its worldwide use in academia and industry alike with several thousand downloads originating from 45 countries.http://dx.doi.org/10.1155/2016/2635124 |
| spellingShingle | Johannes Jordan Elli Angelopoulou Andreas Maier A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data Journal of Electrical and Computer Engineering |
| title | A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data |
| title_full | A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data |
| title_fullStr | A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data |
| title_full_unstemmed | A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data |
| title_short | A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data |
| title_sort | novel framework for interactive visualization and analysis of hyperspectral image data |
| url | http://dx.doi.org/10.1155/2016/2635124 |
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