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- W2766820552 abstract "Abstract In hyperspectral images, spectral mixing occurs when objects lying beside each cannot be distinguished as different entities due to its low spatial resolution. Other hurdles in hyperspectral imaging are its huge dimension and noisy bands. In this paper, a new approach for spectral unmixing is presented where, the data is reduced dimensionally and, the bands eliminated during this are denoised using the existing denoising methods. Then, dataset with these bands is dimensionally reduced and their presence after reduction is validated using spectral unmixing methods. The effectiveness of this method is evaluated using parametric measures such as RMSE and classification accuracy." @default.
- W2766820552 created "2017-11-10" @default.
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- W2766820552 date "2017-01-01" @default.
- W2766820552 modified "2023-10-17" @default.
- W2766820552 title "Effect of Denoising on Dimensionally Reduced Sparse Hyperspectral Unmixing" @default.
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- W2766820552 doi "https://doi.org/10.1016/j.procs.2017.09.096" @default.
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