Background dictionary construction-based sparse representation hyperspectral target detection
Aiming at the existing target detection algorithms based on sparse representation, in the process of building the background dictionary with concentric double windows, the target pixels will interfere with the background dictionary. A sparse representation hyperspectral target detection algorithm ba...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
National Computer System Engineering Research Institute of China
2022-01-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000145094 |
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| Summary: | Aiming at the existing target detection algorithms based on sparse representation, in the process of building the background dictionary with concentric double windows, the target pixels will interfere with the background dictionary. A sparse representation hyperspectral target detection algorithm based on background dictionary is proposed. The algorithm decomposes the hyperspectral image into low rank background and sparse target, and introduces the target dictionary as the prior information of sparse target, which can separate the target and background better and construct a pure background dictionary. Simulation results on four public hyperspectral image datasets show that the proposed algorithm has excellent detection performance. |
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| ISSN: | 0258-7998 |