Spectrum Extension of a Real-Aperture Microwave Radiometer Using a Spectrum Extension Convolutional Neural Network for Spatial Resolution Enhancement

被引:0
|
作者
Zhao, Guanghui [1 ]
Huang, Yuhang [1 ]
Xiao, Chengwang [1 ]
Chen, Zhiwei [1 ]
Wang, Wenjing [1 ]
Gultepe, Ismail
Wang, Zhenzhan
机构
[1] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Sci & Technol Multispectral Informat Proc Lab, Wuhan 430074, Peoples R China
关键词
real-aperture microwave radiometer; spectrum extension; spatial resolution enhancement; land-to-sea contamination; neural network; CNN;
D O I
10.3390/rs15245775
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Enhancing the spatial resolution of real-aperture microwave radiometers is an essential research topic. The accuracy of the numerical values of brightness temperatures (BTs) observed using microwave radiometers directly affects the precision of the retrieval of marine environmental parameters. Hence, ensuring the accuracy of the enhanced brightness temperature values is of paramount importance when striving to enhance spatial resolution. A spectrum extension (SE) method is proposed in this paper, which restores the suppressed high-frequency components in the scene BT spectrum through frequency domain transformation and calculations, specifically, dividing the observed BT spectrum by the conjugate of the antenna pattern spectrum and applying a Taylor approximation to suppress error amplification, thereby extending the observed BT spectrum. By using a convolutional neural network to correct errors in the calculated spectrum and then reconstructing the BT through inverse fast Fourier transform (IFFT), the enhanced BTs are obtained. Since the extended BT spectrum contains more high-frequency components, namely, the spectrum is closer to that of the original scene BT, the reconstructed BT not only achieves an enhancement in spatial resolution, but also an improvement in the accuracy of BT values. Both the results from simulated data and satellite-measured data processing illustrate that the SE method is able to enhance the spatial resolution of real-aperture microwave radiometers and concurrently improve the accuracy of BT values.
引用
收藏
页数:26
相关论文
共 50 条
  • [1] Spatial Resolution Enhancement of Satellite Microwave Radiometer Data with Deep Residual Convolutional Neural Network
    Hu, Weidong
    Li, Yade
    Zhang, Wenlong
    Chen, Shi
    Lv, Xin
    Ligthart, Leo
    REMOTE SENSING, 2019, 11 (07)
  • [2] Spatial Resolution Matching of Microwave Radiometer Data with Convolutional Neural Network
    Li, Yade
    Hu, Weidong
    Chen, Shi
    Zhang, Wenlong
    Guo, Rui
    He, Jingwen
    Ligthart, Leo
    REMOTE SENSING, 2019, 11 (20)
  • [3] Visibility Extension of 1-D Aperture Synthesis by a Residual CNN for Spatial Resolution Enhancement
    Zhao, Guanghui
    Li, Qingxia
    Chen, Zhiwei
    Lei, Zhenyu
    Xiao, Chengwang
    Huang, Yuhang
    REMOTE SENSING, 2023, 15 (04)
  • [4] Bandwidth Extension of Telephone Speech Using a Neural Network and a Filter Bank Implementation for Highband Mel Spectrum
    Pulakka, Hannu
    Alku, Paavo
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2011, 19 (07): : 2170 - 2183
  • [5] Cosine Visibility Extension of 1-D Mirrored Aperture Synthesis by a CNN for Spatial Resolution Enhancement
    Zhao, Guanghui
    Li, Qingxia
    Lei, Zhenyu
    Xiao, Chengwang
    Chen, Zhiwei
    Huang, Yuhang
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [6] Cosine Visibility Extension of 1-D Mirrored Aperture Synthesis by a CNN for Spatial Resolution Enhancement
    Zhao, Guanghui
    Li, Qingxia
    Lei, Zhenyu
    Xiao, Chengwang
    Chen, Zhiwei
    Huang, Yuhang
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [7] Robust Source Counting and DOA Estimation Using Spatial Pseudo-Spectrum and Convolutional Neural Network
    Nguyen, Thi Ngoc Tho
    Gan, Woon-Seng
    Ranjan, Rishabh
    Jones, Douglas L.
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2020, 28 : 2626 - 2637
  • [8] Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network
    Sherkatghanad, Zeinab
    Akhondzadeh, Mohammadsadegh
    Salari, Soorena
    Zomorodi-Moghadam, Mariam
    Abdar, Moloud
    Acharya, U. Rajendra
    Khosrowabadi, Reza
    Solari, Vahid
    FRONTIERS IN NEUROSCIENCE, 2020, 13
  • [9] Enhancing Physical Spatial Resolution of Synthetic Aperture Sonar Images Based on Convolutional Neural Network
    Xu, Pan
    Gao, Dongbao
    Yu, Shui
    Li, Guangming
    Zhao, Yun
    Xu, Guojun
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2025, 13 (01)
  • [10] Spatial-Cue Based Audio Channel Extension Using Convolutional Neural Networks
    Beack, Seungkwon
    Lim, Wootaek
    Lee, Taejin
    2019 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB), 2019,