Hyperspectral Unmixing with Bandwise Generalized Bilinear Model
Generalized bilinear model (GBM) has received extensive attention in the field of hyperspectral nonlinear unmixing. Traditional GBM unmixing methods are usually assumed to be degraded only by additive white Gaussian noise (AWGN), and the intensity of AWGN in each band of hyperspectral image (HSI) is...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/10/10/1600 |
| _version_ | 1818958148621303808 |
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| author | Chang Li Yu Liu Juan Cheng Rencheng Song Hu Peng Qiang Chen Xun Chen |
| author_facet | Chang Li Yu Liu Juan Cheng Rencheng Song Hu Peng Qiang Chen Xun Chen |
| author_sort | Chang Li |
| collection | DOAJ |
| description | Generalized bilinear model (GBM) has received extensive attention in the field of hyperspectral nonlinear unmixing. Traditional GBM unmixing methods are usually assumed to be degraded only by additive white Gaussian noise (AWGN), and the intensity of AWGN in each band of hyperspectral image (HSI) is assumed to be the same. However, the real HSIs are usually degraded by mixture of various kinds of noise, which include Gaussian noise, impulse noise, dead pixels or lines, stripes, and so on. Besides, the intensity of AWGN is usually different for each band of HSI. To address the above mentioned issues, we propose a novel nonlinear unmixing method based on the bandwise generalized bilinear model (NU-BGBM), which can be adapted to the presence of complex mixed noise in real HSI. Besides, the alternative direction method of multipliers (ADMM) is adopted to solve the proposed NU-BGBM. Finally, extensive experiments are conducted to demonstrate the effectiveness of the proposed NU-BGBM compared with some other state-of-the-art unmixing methods. |
| first_indexed | 2024-12-20T11:21:08Z |
| format | Article |
| id | doaj.art-12e0bf3cdb8d478092abbcfdb60cd72b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T11:21:08Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-12e0bf3cdb8d478092abbcfdb60cd72b2022-12-21T19:42:30ZengMDPI AGRemote Sensing2072-42922018-10-011010160010.3390/rs10101600rs10101600Hyperspectral Unmixing with Bandwise Generalized Bilinear ModelChang Li0Yu Liu1Juan Cheng2Rencheng Song3Hu Peng4Qiang Chen5Xun Chen6Department of Biomedical Engineering, Hefei University of Technology, Hefei 230009, ChinaDepartment of Biomedical Engineering, Hefei University of Technology, Hefei 230009, ChinaDepartment of Biomedical Engineering, Hefei University of Technology, Hefei 230009, ChinaDepartment of Biomedical Engineering, Hefei University of Technology, Hefei 230009, ChinaDepartment of Biomedical Engineering, Hefei University of Technology, Hefei 230009, ChinaDepartment of Biomedical Engineering, Hefei University of Technology, Hefei 230009, ChinaDepartment of Electronic Science and Technology, University of Science and Technology of China, Hefei 230027, ChinaGeneralized bilinear model (GBM) has received extensive attention in the field of hyperspectral nonlinear unmixing. Traditional GBM unmixing methods are usually assumed to be degraded only by additive white Gaussian noise (AWGN), and the intensity of AWGN in each band of hyperspectral image (HSI) is assumed to be the same. However, the real HSIs are usually degraded by mixture of various kinds of noise, which include Gaussian noise, impulse noise, dead pixels or lines, stripes, and so on. Besides, the intensity of AWGN is usually different for each band of HSI. To address the above mentioned issues, we propose a novel nonlinear unmixing method based on the bandwise generalized bilinear model (NU-BGBM), which can be adapted to the presence of complex mixed noise in real HSI. Besides, the alternative direction method of multipliers (ADMM) is adopted to solve the proposed NU-BGBM. Finally, extensive experiments are conducted to demonstrate the effectiveness of the proposed NU-BGBM compared with some other state-of-the-art unmixing methods.http://www.mdpi.com/2072-4292/10/10/1600additive white Gaussian noise (AWGN)hyperspectral images (HSIs)mixed noisebandwise generalized bilinear model (BGBM)alternative direction method of multipliers (ADMM) |
| spellingShingle | Chang Li Yu Liu Juan Cheng Rencheng Song Hu Peng Qiang Chen Xun Chen Hyperspectral Unmixing with Bandwise Generalized Bilinear Model Remote Sensing additive white Gaussian noise (AWGN) hyperspectral images (HSIs) mixed noise bandwise generalized bilinear model (BGBM) alternative direction method of multipliers (ADMM) |
| title | Hyperspectral Unmixing with Bandwise Generalized Bilinear Model |
| title_full | Hyperspectral Unmixing with Bandwise Generalized Bilinear Model |
| title_fullStr | Hyperspectral Unmixing with Bandwise Generalized Bilinear Model |
| title_full_unstemmed | Hyperspectral Unmixing with Bandwise Generalized Bilinear Model |
| title_short | Hyperspectral Unmixing with Bandwise Generalized Bilinear Model |
| title_sort | hyperspectral unmixing with bandwise generalized bilinear model |
| topic | additive white Gaussian noise (AWGN) hyperspectral images (HSIs) mixed noise bandwise generalized bilinear model (BGBM) alternative direction method of multipliers (ADMM) |
| url | http://www.mdpi.com/2072-4292/10/10/1600 |
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