基于空间与光谱注意力的光学图像和SAR图像特征融合分类方法

Translated title of the contribution: Feature Fusion Classification for Optical Image and SAR Image Based on Spatial-spectral Attention

Wen Jiang, Jie Pan, Jinbiao Zhu, Xijuan Yue

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Considering the issue of difference and complementarity of multi-source remote sensing images, this paper proposes a feature fusion classification method for optical image and SAR image based on spatial-spectral attention. Firstly, features of optical image and SAR image are extracted by the convolutional neural network, and an attention module composed of spatial attention and spectral attention is designed to analyze the importance of features. Features can be enhanced by the weights of the attention module, which can reduce the attention to irrelevant information, and thus improve the accuracy of fusion classification for optical and SAR images. Experimental results on two datasets of optical image and SAR image demonstrate that the proposed method is able to yield higher fusion classification accuracy.

Translated title of the contributionFeature Fusion Classification for Optical Image and SAR Image Based on Spatial-spectral Attention
Original languageChinese (Traditional)
Pages (from-to)987-995
Number of pages9
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Volume45
Issue number3
DOIs
StatePublished - Mar 2023
Externally publishedYes

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