Enhancing Spectral Classification Using Adaboost
Spectral classification for hyperspectral image is a challenging job because of the number of spectral in a hyperspectral image and high dimensional spectral. In this paper, we proposed a method to enhance the spectral classification using the Adaboost for hyperspectral image analysis. By applying...
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| Language: | en |
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2012
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| Online Access: | http://eprints.utem.edu.my/id/eprint/8553/1/06457623.pdf http://eprints.utem.edu.my/id/eprint/8553/ http://ieeexplore.ieee.org.libproxy.utem.edu.my/xpl/articleDetails.jsp?tp=&arnumber=6457623&queryText%3DEnhancing+spectral+classification+using+Adaboost |
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| author | Saipullah, Khairul Muzzammil |
| author_facet | Saipullah, Khairul Muzzammil |
| author_sort | Saipullah, Khairul Muzzammil |
| building | UTEM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknikal Malaysia Melaka |
| content_source | UTEM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Spectral classification for hyperspectral image is a challenging job because of the number of spectral in a
hyperspectral image and high dimensional spectral. In this paper, we proposed a method to enhance the spectral classification using the Adaboost for hyperspectral image analysis. By applying the Adaboost algorithm to the classifier, the classification can be executed iteratively by giving weight to the spectral data, thus will reduce the classification error rate. The Adaboost is implemented to spectral angle mapper (SAM),Euclidean distance (ED), and city block distance (CD). From the experimental results, the Adaboost increases the average classification accuracy of 2000 spectral up to 99.63% using the CD. Overall, Adaboost increases the average classification accuracy of ED, CD, and SAM by 2.54%, 1.95%, and 1.67%. |
| format | Conference or Workshop Item |
| id | my.utem.eprints-8553 |
| institution | Universiti Teknikal Malaysia Melaka |
| language | en |
| publishDate | 2012 |
| record_format | eprints |
| spelling | my.utem.eprints-85532015-05-28T03:57:29Z http://eprints.utem.edu.my/id/eprint/8553/ Enhancing Spectral Classification Using Adaboost Saipullah, Khairul Muzzammil TA Engineering (General). Civil engineering (General) Spectral classification for hyperspectral image is a challenging job because of the number of spectral in a hyperspectral image and high dimensional spectral. In this paper, we proposed a method to enhance the spectral classification using the Adaboost for hyperspectral image analysis. By applying the Adaboost algorithm to the classifier, the classification can be executed iteratively by giving weight to the spectral data, thus will reduce the classification error rate. The Adaboost is implemented to spectral angle mapper (SAM),Euclidean distance (ED), and city block distance (CD). From the experimental results, the Adaboost increases the average classification accuracy of 2000 spectral up to 99.63% using the CD. Overall, Adaboost increases the average classification accuracy of ED, CD, and SAM by 2.54%, 1.95%, and 1.67%. 2012-12-11 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/8553/1/06457623.pdf Saipullah, Khairul Muzzammil (2012) Enhancing Spectral Classification Using Adaboost. In: 2012 IEEE Asia-Pacific Conference on Applied Electromagnetics (APACE) 2012, 11 - 13 Dec 2012, Melaka. http://ieeexplore.ieee.org.libproxy.utem.edu.my/xpl/articleDetails.jsp?tp=&arnumber=6457623&queryText%3DEnhancing+spectral+classification+using+Adaboost |
| spellingShingle | TA Engineering (General). Civil engineering (General) Saipullah, Khairul Muzzammil Enhancing Spectral Classification Using Adaboost |
| title | Enhancing Spectral Classification Using Adaboost
|
| title_full | Enhancing Spectral Classification Using Adaboost
|
| title_fullStr | Enhancing Spectral Classification Using Adaboost
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| title_full_unstemmed | Enhancing Spectral Classification Using Adaboost
|
| title_short | Enhancing Spectral Classification Using Adaboost
|
| title_sort | enhancing spectral classification using adaboost |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://eprints.utem.edu.my/id/eprint/8553/1/06457623.pdf http://eprints.utem.edu.my/id/eprint/8553/ http://ieeexplore.ieee.org.libproxy.utem.edu.my/xpl/articleDetails.jsp?tp=&arnumber=6457623&queryText%3DEnhancing+spectral+classification+using+Adaboost |
| url_provider | http://eprints.utem.edu.my/ |