Computer Science ›› 2017, Vol. 44 ›› Issue (9): 23-27.doi: 10.11896/j.issn.1002-137X.2017.09.004

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Multi-granularity Clustering of Remote Sensing Image Based on Gaussian Cloud Transformation

LIU Xuan, WANG Guo-yin and LUO Xiao-bo   

  • Online:2018-11-13 Published:2018-11-13

Abstract: With the development of remote sensing image technology,the limitation of the traditional image analysis methods have become increasingly prominent.From the perspective of multi-granularity and multi-level,we can solve the adaptive clustering problem of remote sensing images better,with large amount of information and complex structures.Gaussian cloud transformation which is based on cloud model and Gaussian mixture model is a new model of multi-granularity method.It can extract multiple concepts from different granularities in a problem domain.However,due to its time complexity and noise sensitivity,the clustering result of remote sensing images is not ideal.An improved Gaussian cloud transformation method was proposed in this thesis.First,K-Means is used to optimize the selection of initial grain size and amplitude cloud comprehensive is used to modify the adaptive concept abstraction strategy.Then,the granularity division is gotten by using a membership distance.Finally,the method is applied to remote sensing images.The experimental results show the correctness and effectiveness of the proposed method.

Key words: Remote sensing image,Gaussian cloud transformation,Multi-granularity,Image clustering

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