Remote sensing image classification based on geostatistics and ANN
2006
Texture is the key character of remote sensing image classification and a lot of studies on this have been done. This
article analyzes the current study situation of remote sensing image classification methods and extracting textural
information. Moreover, it analyzes the theory of geostatistics. Based on the geostatistics theory, the variogram is applied
to extracting textural information of remote sensing image in this article. It has been proven that the textural information
can be used to classification by means of test. At the same time, this article discusses the size of computation window,
computation direction and step according to the practical application and puts forward to an auto-adaptive method to
determine the size of computation window. In addition, it advances a new method to compute textural information,
weighted variogram. Considering that the neural network classification has no limitation to data, this study adopts the
back propagation neural network method to classify and recognize the matter combining the textural information
extracted by variogram and spectral information. Then the classification results are compared with those gained by
maximum likelihood method. The analysis result shows that this method can improve the classification precision.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
0
References
1
Citations
NaN
KQI