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- W2079088971 abstract "In this paper, hyperspectral data cubes that are denoised using a wavelet transform based hybrid spatial–spectral noise-reduction (HSSNR) algorithm are evaluated based on two approaches. The first approach relies on narrow-band vegetation indices and red-edge positions, and the second approach adopts a number of spectral similarity measures. The evaluation shows that the results from the HSSNR denoising algorithm are comparable to those from existing denoising algorithms for vegetation indices and red-edge positions and superior to those from existing denoising algorithms for spectral similarity measures." @default.
- W2079088971 created "2016-06-24" @default.
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- W2079088971 date "2008-01-01" @default.
- W2079088971 modified "2023-09-22" @default.
- W2079088971 title "An evaluation of wavelet-denoised hyperspectral data for remote sensing" @default.
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- W2079088971 doi "https://doi.org/10.5589/m07-061" @default.
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