Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage

@article{Othman2006NoiseRO,
  title={Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage},
  author={Hisham Othman and Shen-En Qian},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2006},
  volume={44},
  pages={397-408}
}
In this paper, a new noise reduction algorithm is introduced and applied to the problem of denoising hyperspectral imagery. This algorithm resorts to the spectral derivative domain, where the noise level is elevated, and benefits from the dissimilarity of the signal regularity in the spatial and the spectral dimensions of hyperspectral images. The performance of the new algorithm is tested on two different hyperspectral datacubes: an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS… CONTINUE READING
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