Hyperspectral imaging is a significant remote sensing technology for deep space exploration to understand the planetary geological evolution. However, hyperspectral images (HSIs) usually suffer from various noises because of the complicated environment and equipment limitations, which leads to inconvenience to subsequent applications. In this work, a comprehensive and systematic investigation on planetary noise categories is summarized initially, and an intercomparison among state-of-the-art

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... restrial joint spatial-spectral restoration models is performed to test their capability on planetary datasets. The Compact Reconnaissance Imaging Spectrometer for Mars and Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité are adopted as examples. An improved nonreference quantitative evaluation method based on the high-resolution imaging science experiment imagery is proposed. The processed high-resolution classification result of Russell Dune can be used as the reference of unmixing after denoising. Then, spectral and spatial fidelity can be assessed indirectly. Experimental results emphasize that denoising approaches with modeling for non-independently and identically (non i.i.d.) noise characteristics are more suitable for planetary HSIs because of the diversity and complexity of their noises. This kind of method is flexible under practical circumstances and maintains the intrinsic information of HSIs better. Index Terms-Compact reconnaissance imaging spectrometer for mars (CRISM), denoising, high resolution imaging science experiment (HiRISE) imagery, hyperspectral imagery (HSI), l'Eau, les glaces et l'activité (OMEGA), observatoire pour la minéralogie, remote sensing of planetary surface, spatial-spectral, spectral analysis.