Robust support vector regression for biophysical variable estimation from remotely sensed images

@article{CampsValls2006RobustSV,
  title={Robust support vector regression for biophysical variable estimation from remotely sensed images},
  author={Gustavo Camps-Valls and Lorenzo Bruzzone and Jos{\'e} Luis Rojo-{\'A}lvarez and Farid Melgani},
  journal={IEEE Geoscience and Remote Sensing Letters},
  year={2006},
  volume={3},
  pages={339-343}
}
This letter introduces the epsiv-Huber loss function in the support vector regression (SVR) formulation for the estimation of biophysical parameters extracted from remotely sensed data. This cost function can handle the different types of noise contained in the dataset. The method is successfully compared to other cost functions in the SVR framework, neural networks and classical bio-optical models for the particular case of the estimation of ocean chlorophyll concentration from satellite… CONTINUE READING
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