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Discovering Diverse Subset for Unsupervised Hyperspectral Band Selection
IEEE Transactions on Image Processing, 2017Band selection, as a special case of the feature selection problem, tries to remove redundant bands and select a few important bands to represent the whole image cube. This has attracted much attention, since the selected bands provide discriminative information for further applications and reduce the computational burden.
Yuan, Yuan +3 more
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Band Selection for Hyperspectral Imagery with PCA-MIG
2012Although hyperspectral imagery provides abundant information about bands, their high dimensionality also substantially increases the computational burden. An interesting task in hyperspectral data processing is to reduce the redundancy of the spectral and spatial information without loss of any valuable details.
Kitti Koonsanit +2 more
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Hyperspectral Band Selection With Iterative Graph Autoencoder
IEEE Transactions on Geoscience and Remote Sensing, 2023Yuan Zhou 0006 +3 more
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Hyperspectral Band Selection by Virtual Dimensionality
2018Hyperspectral images are generally acquired by hundreds of contiguous spectral bands and provide a wealth of useful and crucial information for data analysis. However, on many occasions too many bands cause undesired effects, called curse of dimensionality.
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Hyperspectral imagery visualization using band selection
2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS), 2012Hongjun Su, Qian Du 0001, Peijun Du
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Band selection for hyperspectral remote sensing
2005de Backer, Steve +3 more
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