数字农科院2.0

Generative adversarial network with double discrimination for heterogeneous hyperspectral reconstruction

文献类型： 外文期刊

作者： Haozhe Zhou;Yiyang Shen;Ziyi Yan;Yongjie Yang;Xiaoyue Yu;Yongliang Lu;Yanchao Zhang

作者机构：

关键词： Generation adversarial network (GAN);Hyperspectral reconstruction;Images registration;Spatial–spectral attention;UAV

期刊名称： Computers and Electronics in Agriculture

ISSN： 0168-1699

年卷期： 2025 年 237 卷

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Both spatial and spectral resolution play important roles in the identification of objects in hyperspectral remote sensing. However, the imaging characteristics of hyperspectral imagery lead to a mutually constraining relationship between spatial and spectral resolution. With the development of DL, the inverse transformation based on HS reconstruction of multispectral image (MSI) images has made great progress. Previous work mainly utilized HSI downsampling to obtain a few bands as inputs to the model for reconstruction, which is merely image processing rather than practical application. In order to improve the accuracy and application of HS reconstruction in field production activities, we propose a generative adversarial network (GAN) based on double discrimination. Specifically, the dataset is first formed through the preprocessing process of image alignment; then, based on the proposed network with double discrimination, adversarial learning is performed from the spatial dimension and the spectral dimension to ensure the spectral similarity of the HSI reconstruction; and finally, we propose a VI-based discrimination method to ensure the practical application capability. The results show that the proposed method not only achieves good results in all commonly used evaluation metrics, but also has good capabilities in VI-based production activities and generalization capabilities. In conclusion, the proposed method can help researchers in the field of remote sensing to better guide their production activities with less input.

分类号：

  • 相关文献

[1]Two-step ResUp&Down generative adversarial network to reconstruct multispectral image from aerial RGB image. Yanchao Zhang,Wen Yang,Wenbo Zhang,Jiya Yu,Jianxin Zhang,Yongjie Yang,Yongliang Lu,Wei Tang. 2022

[2]Numerical Simulation And Experimental Verification O.n Downwash Air Flow O f Six-Rotor Agricultural Unmanned Aerial Vehicle In Hover. Xue Xinyu,Yang Fengbo,Zhang Ling,Sun Zhu. 2017

[3]Development Of A Low-Cost Quadrotor U.av Based On Adrc F or Agricultural Remote Sensing. Xue, Xinyu,Zhang, Songchao,Zhang, Songchao,Sun, Tao,Chen, Chen,Sun, Zhu. 2019

[4]Drift and deposition of ultra-low altitude and low volume application in paddy field. Xue Xinyu,Tu Kang,Xue Xinyu,Qin Weicai,Lan, Yubin,Zhang, Huihui. 2014

[5]Estimating LAI for Cotton Using Multisource UAV Data and a Modified Universal Model. Yan, Puchen,Han, Qisheng,Feng, Yangming,Kang, Shaozhong. 2022

[6]A fast and robust method for plant count in sunflower and maize at different seedling stages using high-resolution UAV RGB imagery. Bai, Yi,Nie, Chenwei,Wang, Hongwu,Cheng, Minghan,Liu, Shuaibing,Yu, Xun,Shao, Mingchao,Wang, Zixu,Wang, Siyu,Tuohuti, Nuremanguli,Shi, Lei,Ming, Bo,Jin, Xiuliang. 2022

[7]Droplet distribution in cotton canopy using single-rotor and four-rotor unmanned aerial vehicles. Meng, Yanhua,Ma, Yan,Wang, Zhiguo,Hu, Hongyan. 2022

[8]Predicting equivalent water thickness in wheat using UAV mounted multispectral sensor through deep learning techniques. Adama Traore,Syed Tahir Ata-Ul-karim,Aiwang Duan,Mukesh Kumar Soothar,Seydou Traore,Ben Zhao. 2021

[9]Detection and Counting of Maize Leaves Based on Two-Stage Deep Learning with UAV-Based RGB Image. Xu, Xingmei,Wang, Lu,Shu, Meiyan,Liang, Xuewen,Ghafoor, Abu Zar,Liu, Yunling,Ma, Yuntao,Zhu, Jinyu. 2022

[10]Data on three-year flowering intensity monitoring in an apple orchard: A collection of RGB images acquired from unmanned aerial vehicles. Chenglong Zhang,João Valente,Wensheng Wang,Pieter van Dalfsen,Peter Frans de Jong,Bert Rijk,Lammert Kooistra. 2023

[11]Quantitative estimation of organ-scale phenotypic parameters of field crops through 3D modeling using extremely low altitude UAV images. Binglin Zhu,Yan Zhang,Yanguo Sun,Yi Shi,Yuntao Ma,Yan Guo. 2023

[12]Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery. Liang Ting,Duan Bo,Luo Xiaoyun,Ma Yi,Yuan Zhengqing,Zhu Renshan, Peng Yi,Gong Yan,Fang Shenghui,Wu Xianting. 2021

[13]Estimating leaf area index using unmanned aerial vehicle data: Shallow vs. 2 deep machine learning algorithms. Shuaibing Liu, Xiuliang Jin*, Chenwei Nie, Siyu Wang, Xun Yu, Minghan Cheng, Mingchao Shao, Zixu Wang, Nuremanguli Tuohuti, Yi Bai, Yadong Liu. 2021

[14]Improved estimation of canopy water status in maize using UAV-based digital and hyperspectral images. Shu Meiyan,Dong Qizhou,Fei ShuaiPeng,Yang Xiaohong,Zhu Jinyu,Meng Lei,Li Baoguo,Ma Yuntao. 2022

[15]Estimation of potato above-ground biomass based on unmanned aerial vehicle red-green-blue images with different texture features and crop height. Liu, Yang,Feng, Haikuan,Yue, Jibo,Jin, Xiuliang,Li, Zhenhai,Yang, Guijun. 2022

[16]Improving Wheat Yield Prediction Accuracy Using LSTM-RF Framework Based on UAV Thermal Infrared and Multispectral Imagery. Shen, Yulin,Mercatoris, Benoit,Cao, Zhen,Kwan, Paul,Guo, Leifeng,Yao, Hongxun,Cheng, Qian. 2022

[17]Entropy Weight Ensemble Framework for Yield Prediction of Winter Wheat Under Different Water Stress Treatments Using Unmanned Aerial Vehicle-Based Multispectral and Thermal Data. Shuaipeng Fei,Muhammad Adeel Hassan,Yuntao Ma,Meiyan Shu,Qian Cheng,Zongpeng Li,Zhen Chen,Yonggui Xiao. 2021

[18]Developing Novel Rice Yield Index Using UAV Remote Sensing Imagery Fusion Technology. Zhou, Jun,Lu, Xiangyu,Yang, Rui,Chen, Huizhe,Wang, Yaliang,Zhang, Yuping,Huang, Jing,Liu, Fei. 2022

[19]UAV multispectral images for accurate estimation of the maize LAI considering the effect of soil background. Shuaibing Liu,Xiuliang Jin,Yi Bai,Wenbin Wu,Ningbo Cui,Minghan Cheng,Yadong Liu,Lin Meng,Xiao Jia,Chenwei Nie,Dameng Yin. 2023

[20]Estimation of soybean yield parameters under lodging conditions using RGB information from unmanned aerial vehicles. Bai D.,Li D.,Zhao C.,Wang Z.,Shao M.,Guo B.,Liu Y.,Wang Q.,Li J.,Guo S.,Wang R.,Li Y.-H.,Qiu L.-J.,Jin X.. 2023

作者其他论文 更多>>