MULTISPECTRAL REMOTE SENSING IMAGE CLASSIFICATION BASED ON QUANTUM ENTANGLEMENT

Yang, F.; Zhou, G. Q.; Xiao, J. R.; Li, Q.; Jia, B.; Wang, H. Y.; Gao, J.

Aiming at the problems of low accuracy and slow speed in the current remote sensing image classification algorithm,In order to improve remote sensing image classification, a quantum entanglement algorithm is proposed.The model transforms the classification process of remote sensing image into a random self-organization process of quantum particles in the state configuration space. The state configuration formed by entanglement of quantum particles evolves with time and finally converges to an average probability distribution.Taking Kunming city of Yunnan province as the research area, this paper compares the classification method in this paper with the traditional remote sensing classification method by using the 02C image data of yuanyuan1.Compared with other classification methods, the classification accuracy of this paper meets the requirements.

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Yang, F. / Zhou, G. Q. / Xiao, J. R. / et al: MULTISPECTRAL REMOTE SENSING IMAGE CLASSIFICATION BASED ON QUANTUM ENTANGLEMENT. 2020. Copernicus Publications.

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