Gaussian Mixture Model of Texture for Extracting Residential Area from High-resolution Remotely Sensed Imagery

@inproceedings{Gu2007GaussianMM,
  title={Gaussian Mixture Model of Texture for Extracting Residential Area from High-resolution Remotely Sensed Imagery},
  author={Juan Gu and Jun Chen and Qingfeng Zhou and Hongwei Zhang},
  year={2007}
}
Using high-resolution remotely sensed imagery to timely detect distribution and expansion of residential area is one of most important jobs of national 1:5 spatial database updating. In view of complicated spatial characters of residential area and working disable of current automatic interpretation methods based on spectral features on high-resolution remotely sensed imagery, a classifier based on Gaussian Mixture Model (GMM) of texture is proposed. The combination of co-occurrence texture… CONTINUE READING
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Urban built - up land change detection with road density and spectral information from multi - temporal Landsat TM data

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