Texture segmentation for remote sensing image based on texture-topic model
- Resource Type
- Conference
- Authors
- Feng, Hao; Jiang, Zhiguo; Han, Xingmin
- Source
- 2011 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International. :2669-2672 Jul, 2011
- Subject
- Fields, Waves and Electromagnetics
Geoscience
Power, Energy and Industry Applications
Signal Processing and Analysis
Image segmentation
Remote sensing
Zinc
Visualization
Accuracy
Image color analysis
Computer vision
remote sensing
LDA
topic model
segmentation
Bayesian model
- Language
- ISSN
- 2153-6996
2153-7003
Textures of land covers provide significant evidences for segmentation and classification. Inspired by resent researches on topic model, we work on a novel texture segmentation method for very high resolution (VHR) remote sensing images based on Latent Dirichlet Allocation (LDA). In order to model spatial relationship between words in LDA, a constraint random variable which is used to control the selection of neighboring features of each specific texture is introduced to the model. The proposed method is evaluated on segmenting remote sensing images by finding the homogeneous regions in texture-topic map. The experimental results show our method has great potential for remote sensing image segmentation.