On the Impact of Lossy Compression on Hyperspectral Image Classification and Unmixing

  title={On the Impact of Lossy Compression on Hyperspectral Image Classification and Unmixing},
  author={Fernando Garc{\'i}a-V{\'i}lchez and Jordi Mu{\~n}oz-Mar{\'i} and Maciel Zortea and Ian Blanes and Vicente Gonz{\'a}lez Ruiz and Gustavo Camps-Valls and Antonio J. Plaza and Joan Serra-Sagrist{\`a}},
  journal={IEEE Geoscience and Remote Sensing Letters},
Hyperspectral data lossy compression has not yet achieved global acceptance in the remote sensing community, mainly because it is generally perceived that using compressed images may affect the results of posterior processing stages. This possible negative effect, however, has not been accurately characterized so far. In this letter, we quantify the impact of lossy compression on two standard approaches for hyperspectral data exploitation: spectral unmixing, and supervised classification using… CONTINUE READING
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