Journal of Guangxi Normal University(Natural Science Edition) ›› 2018, Vol. 36 ›› Issue (2): 33-41.doi: 10.16088/j.issn.1001-6600.2018.02.005

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Remote Sensing Image Fusion Based on Convolutional Neural Network Super-resolution Reconstruction

XUE Yang,ZENG Qingke,XIA Haiying*,WANG Wentao   

  1. College of Electronic Engineering, Guangxi Normal University,Guilin Guangxi 541004, China
  • Received:2017-07-20 Online:2018-05-10 Published:2018-07-18

Abstract: A remote sensing image fusion method based on super-resolution reconstruction with convolutional neural network (CNN) is proposed to make full use of spatial information of multispectral image and obtain better fusion quality. Firstly,the mulispectral image is transformed with IHS transform,the gotten I component is reconstructed by Super-Resolution Convolutional Neural Network(SRCNN), which enhances the spatial information while expanding its size. Then the panchromatic image and the reconstructed I component of mulispectral image are fused with the fusion method based on wavelet transform,the fusion rule is the absolute value and the changed high frequency components of the fusion image are all derived from the panchromatic image in the traditional algorithms. Finally, the fused multispectral image is obtained via inverse IHS transform.The experiment results show that the algorithm outperforms other algorithms, and reduces the loss of spatial information and spectral information in the process of image fusion effectively.

Key words: remote sensing, image fusion, super-resolution reconstruction, convolutional neural network

CLC Number: 

  • TP751
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