Hyperspectral Data Compression Tradeoff

摘要: Hyperspectral data are a challenge for compression. Several factors make the constraints particularly stringent and exciting. First is size of data: as third dimension added, amount increases dramatically making compression necessary at different steps processing chain. Also properties required stages chain with variable tradeoff. Second, differences in spatial spectral relation between values more traditional 3D algorithms obsolete. And finally, high expectations from scientists using hyperspectral require assurance that will not degrade quality. All these aspects investigated present chapter possible tradeoffs explored. In conclusion, we see number challenges remain, which most important to find an easier way qualify algorithm proposals.