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Weighted Low-rank Tensor Recovery for Hyperspectral Image Restoration
[article]
2017
arXiv
pre-print
Hyperspectral imaging, providing abundant spatial and spectral information simultaneously, has attracted a lot of interest in recent years. Unfortunately, due to the hardware limitations, the hyperspectral image (HSI) is vulnerable to various degradations, such noises (random noise, HSI denoising), blurs (Gaussian and uniform blur, HSI deblurring), and down-sampled (both spectral and spatial downsample, HSI super-resolution). Previous HSI restoration methods are designed for one specific task
arXiv:1709.00192v1
fatcat:ueremc3lzvhlna42pgngpgb3ka