A comparison of common factor-based methods for hyperspectral image exploration: principal components analysis, maximum autocorrelation factors (MAF), minimum noise factors (MNF) and maximum difference factors (MDF)
Principal components analysis (PCA), maximum autocorrelation factors (MAF), minimum noise factors (MNF) and maximum difference factors (MDF) models are common factor-based models used for analysis of hyperspectral images. The models can be posed as maximisation problems that result in a symmetric ei...
保存先:
| 第一著者: | |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
IM Publications Open
2022-08-01
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| シリーズ: | Journal of Spectral Imaging |
| 主題: | |
| オンライン･アクセス: | https://www.impopen.com/download.php?code=I11_a6 |
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