An Adaptive Mean-Shift Analysis Approach for Object Extraction and Classification From Urban Hyperspectral Imagery

@article{Huang2008AnAM,
  title={An Adaptive Mean-Shift Analysis Approach for Object Extraction and Classification From Urban Hyperspectral Imagery},
  author={Xin Huang and Liangpei Zhang},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2008},
  volume={46},
  pages={4173-4185}
}
In this paper, an adaptive mean-shift (MS) analysis framework is proposed for object extraction and classification of hyperspectral imagery over urban areas. The basic idea is to apply an MS to obtain an object-oriented representation of hyperspectral data and then use support vector machine to interpret the feature set. In order to employ MS for hyperspectral data effectively, a feature-extraction algorithm, nonnegative matrix factorization, is utilized to reduce the high-dimensional feature… CONTINUE READING