H
Hongjian You
Researcher at Chinese Academy of Sciences
Publications - 64
Citations - 1297
Hongjian You is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Synthetic aperture radar & Computer science. The author has an hindex of 14, co-authored 52 publications receiving 680 citations.
Papers
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Journal ArticleDOI
BFSIFT: A Novel Method to Find Feature Matches for SAR Image Registration
Shanhu Wang,Hongjian You,Kun Fu +2 more
TL;DR: A novel method based on bilateral filter (BF) scale-invariant feature transform (SIFT) (BFSIFT) to find feature matches for synthetic aperture radar (SAR) image registration, where more accurately located matches can be found in the anisotropic scale space.
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OS-SIFT: A Robust SIFT-Like Algorithm for High-Resolution Optical-to-SAR Image Registration in Suburban Areas
TL;DR: The experimental results show that the proposed OS-SIFT algorithm gives a robust registration result for optical-to-SAR images and outperforms other state-of-the-art algorithms in terms of registration accuracy.
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DRBox-v2: An Improved Detector With Rotatable Boxes for Target Detection in SAR Images
TL;DR: An improved RBox-based target detection framework is proposed to boost precision and recall rates of detection, and this method is referred to as DRBox-v2 and applied to target detection in SAR images.
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Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network
TL;DR: This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme using a fully convolutional network to separate the sea from the land.
Journal ArticleDOI
Adapted Anisotropic Gaussian SIFT Matching Strategy for SAR Registration
Feng Wang,Hongjian You,Xingyu Fu +2 more
TL;DR: An adapted anisotropic Gaussian scale-invariant feature transform (AAG-SIFT) method to find feature matches for synthetic aperture radar (SAR) image registration is proposed and the correct matching rate is significantly increased by DOC matching.