Infrared and Laser Engineering, Volume. 48, Issue 10, 1026002(2019)
Multi-objective hyperspectral unmixing algorithm based on high-order nonlinear mixing model
Based on high-order nonlinear mixing model, a multi-objective hyperspectral unmixing algorithm was proposed, which solved the problem that the traditional method cannot obtain higher unmixing accuracy due to the outliers of hyperspectral image data. The proposed algorithm took the reconstruction error and spectral angle mapper as the objective functions and optimized them in order to reduce the outliers influence of hyperspectral data on the solution of optimization model and improve the two evaluation indicators. Then, the difference search algorithm was used to solve the multi-objective optimization model and overcame the tendency of the traditional gradient-based optimization method to fall into the local extremum problem and further improved the unmixing accuracy. The experiment results show that the proposed algorithm has more accurate endmembers abundance estimation and higher unmixing accuracy.
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Gan Shizhong, Xiao Zhitao, Chen Lei, Nan Ruijie. Multi-objective hyperspectral unmixing algorithm based on high-order nonlinear mixing model[J]. Infrared and Laser Engineering, 2019, 48(10): 1026002
Category: 图像处理
Received: Jun. 11, 2019
Accepted: Jul. 21, 2019
Published Online: Nov. 19, 2019
The Author Email: Shizhong Gan (gan_shizhong@163.com)