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Jingjing Ren

Publications
6
Citations
21
Publications by Year
20222024
Co-Authors:
Show All Co-Authors (29)
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Jingjing Ren

Affiliation

Institute of Remote Sensing Satellites
China Academy of Space Technology
Beijing, China

Publication Topics

Biography

Jingjing Ren received the Ph.D. degree from the University of Science and Technology of China, Hefei, China, in 2012.,Her research interests include spaceborne microwave system design.(Based on document published on 17 October 2024).
Publications
6
Citations
21
Publications by Year
20222024
Co-Authors:
Show All Co-Authors (29)
Author's Published Works

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A Novel Sinusoid Correction Method of Direct Sun Contamination for Interferometric Microwave Radiometer

Xiaobin Yin;Dunchao Du;Yan Li;Wu Zhou;Chaofei Ma;Huan Zhang;Yinan Li;Jingjing Ren

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Correction for the impact of direct Sun contamination is a crucial task in the data processing of interferometric microwave radiometer (IMR). The evident presence of solar radiation is observed in the brightness temperature images derived from the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) payload onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, significantly impact...Show More

A Novel Sinusoid Correction Method of Direct Sun Contamination for Interferometric Microwave Radiometer

Xiaobin Yin;Dunchao Du;Yan Li;Wu Zhou;Chaofei Ma;Huan Zhang;Yinan Li;Jingjing Ren

Year: 2024 | Volume: 62 | Journal Article |

Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning

Haoyu Chen;Wenbo Li;Jinjin Gu;Jingjing Ren;Haoze Sun;Xueyi Zou;Zhensong Zhang;Youliang Yan;Lei Zhu

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2024 | Conference Paper |
Cited by: Papers (2)
For image super-resolution (SR), bridging the gap between the performance on synthetic datasets and real-world degradation scenarios remains a challenge. This work introduces a novel “Low-Res Leads the Way” (LWay) training framework, merging Supervised Pre-training with Self-supervised Learning to enhance the adaptability of SR models to real-world images. Our approach utilizes a low-resolution (L...Show More

Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning

Haoyu Chen;Wenbo Li;Jinjin Gu;Jingjing Ren;Haoze Sun;Xueyi Zou;Zhensong Zhang;Youliang Yan;Lei Zhu

Year: 2024 | Conference Paper |

An Improved Method of Multiple RFI Intensity Estimation for Synthetic Aperture Interferometric Radiometer

Tingyu Shi;Rong Jin;Jingjing Ren;Ke Chen;Quanliang Huang;Qingxia Li

IEEE Transactions on Geoscience and Remote Sensing
Year: 2024 | Volume: 62 | Journal Article |
Cited by: Papers (1)
L-band radio frequency interferences (RFIs) seriously contaminate remote sensing data. This poses a major challenge in processing microwave radiometric data and can substantially degrade the quality of the data. There is an urgent need to estimate RFI intensity to mitigate Gibbs errors caused by RFIs along the sidelobes. The traditional CLEAN algorithm is limited in its ability to account for the ...Show More

An Improved Method of Multiple RFI Intensity Estimation for Synthetic Aperture Interferometric Radiometer

Tingyu Shi;Rong Jin;Jingjing Ren;Ke Chen;Quanliang Huang;Qingxia Li

Year: 2024 | Volume: 62 | Journal Article |

Improved Generalized Cross Correlation Communication Radiation Source Time Difference Estimation Method

Gaohui Liu;Jingjing Ren

2023 IEEE 6th International Conference on Electronics and Communication Engineering (ICECE)
Year: 2023 | Conference Paper |
The aim is to address the issue of low accuracy in traditional cross correlation estimation methods of time difference of arrival (TDOA) under low signal-to-noise ratio (SNR) conditions, this paper proposes a generalized cross correlation (GCC) method for estimating arrival time difference estimation method based on variational modal decomposition (VMD) and wavelet denoising. Firstly, VMD is used ...Show More

Improved Generalized Cross Correlation Communication Radiation Source Time Difference Estimation Method

Gaohui Liu;Jingjing Ren

Year: 2023 | Conference Paper |

Snow Removal in Video: A New Dataset and A Novel Method

Haoyu Chen;Jingjing Ren;Jinjin Gu;Hongtao Wu;Xuequan Lu;Haoming Cai;Lei Zhu

2023 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2023 | Conference Paper |
Cited by: Papers (10)
Snowfall is a common weather phenomenon that can severely affect computer vision tasks by obscuring objects and scenes. However, existing deep learning-based snow removal methods are designed for single images only. In this paper, we target a more complex task - video snow removal, which aims to restore the clear video from the snowy video. To facilitate this task, we propose the first high-qualit...Show More

Snow Removal in Video: A New Dataset and A Novel Method

Haoyu Chen;Jingjing Ren;Jinjin Gu;Hongtao Wu;Xuequan Lu;Haoming Cai;Lei Zhu

Year: 2023 | Conference Paper |

Retrieval of Atmospheric Aerosol Optical Depth From AVHRR Over Land With Global Coverage Using Machine Learning Method

Xiaoqing Tian;Ling Gao;Jun Li;Lin Chen;Jingjing Ren;Chengcai Li

IEEE Transactions on Geoscience and Remote Sensing
Year: 2022 | Volume: 60 | Journal Article |
Cited by: Papers (8)
Aerosols play an important role in global climate change, which requires long-term data records. Advanced very high-resolution radiometer (AVHRR) provides continuous observations for up to 40 years since 1979, which makes it worthwhile to retrieve aerosol optical depth (AOD) from AVHRR over land. A novel algorithm for retrieving AOD from AVHRR is developed based on the machine learning (ML) method...Show More

Retrieval of Atmospheric Aerosol Optical Depth From AVHRR Over Land With Global Coverage Using Machine Learning Method

Xiaoqing Tian;Ling Gao;Jun Li;Lin Chen;Jingjing Ren;Chengcai Li

Year: 2022 | Volume: 60 | Journal Article |

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