Article
Environmental Sciences
Jingxing Zhu, Feng Wang, Hongjian You
Summary: The existence of multiplicative noise in synthetic aperture radar (SAR) images makes SAR segmentation by fuzzy c-means (FCM) a challenging task. To tackle this problem, we propose two unsupervised FCM segmentation frameworks: LBNL_FCM and GLR_FCM. Both frameworks achieve high segmentation accuracy on simulated and real SAR images.
Article
Environmental Sciences
Jinjin Li, Jiacheng Zhang, Chao Yang, Huiyu Liu, Yangang Zhao, Yuanxin Ye
Summary: Synthetic aperture radar (SAR) and optical image fusion can effectively integrate complementary information and improve the performance of remote sensing applications. This paper conducts a systematic review and comparative analysis of pixel-level fusion algorithms for SAR and optical image fusion. Eleven representative fusion methods are evaluated using high-resolution datasets based on visual evaluation, objective image quality metrics, and classification accuracy. The results show that multiscale decomposition methods (MSD) can effectively avoid the negative effects of SAR image shadows, and the non-subsampled contourlet transform method (NSCT) presents the best fusion results. In terms of image classification, the gradient transfer fusion method (GTF) yields the best results.
Article
Engineering, Electrical & Electronic
Takuma Watanabe, Hiroyoshi Yamada
Summary: This study proposes a synthetic aperture imaging technique for near-field scatterers mutually coupled with an antenna array, aiming to reduce unwanted scattered and reradiated waves, and validate the antenna design using bistatic synthetic aperture radar measurement. A direct wave filter is applied as a preprocessing method to suppress artifacts caused by direct waves in image reconstruction.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Remote Sensing
Xin Niu, Di Yang, Ke Yang, Hengyue Pan, Yong Dou, Fei Xia
Summary: This study introduces a novel approach for remote-sensing image translation between high-resolution optical and SAR data through machine learning methods. The efficiency of the proposed methods has been validated with different SAR parameters in three regions, showing that the translated images effectively preserve land cover types and exhibit excellent performance in classification accuracy and similarity indicators.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Yijiang Nan, Xiaojing Huang, Y. Jay Guo
Summary: This article proposes a new panoramic SAR which combines linear and rotational SARs to reconstruct a large 360 degrees panoramic view of the observed scene. It introduces the system geometry, imaging process, resolution analysis, sampling criteria, and a novel dynamic piecewise compensation algorithm. A prototype of panoramic SAR is built based on an FMCW radar and a moving platform, and simulation and experimental results are provided to validate the proposed principle and algorithm.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Qihan Xu, Yunfan Xiang, Zhixiong Di, Yibo Fan, Quanyuan Feng, Qiang Wu, Jiangyi Shi
Summary: An end-to-end SAR image compression convolutional neural network (CNN) model based on a variational autoencoder is proposed in this study, leveraging joint transforms and residual blocks to enhance feature learning efficiency and improve reconstructed image quality, while optimizing compression quality with a conditioned entropy model and hyperprior network.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Runzhi Jiao, Qingsong Wang, Tao Lai, Haifeng Huang
Summary: This study introduces a multi-hypothesis topological isomorphism matching method for SAR images with large geometric distortions, which achieves keypoint matching by utilizing ridge-line keypoint detection and multi-hypothesis topological isomorphism matching. The method improves matching performance by considering both local and global geometric relationships between keypoints.
Article
Computer Science, Artificial Intelligence
Seyed Emadedin Hashemi, Fatemeh Gholian-Jouybari, Mostafa Hajiaghaei-Keshteli
Summary: Big data is increasingly important in various research fields. Cluster analysis is recognized as an effective process, especially for big data. The whale optimization algorithm is applied to solve the convergence problem in fuzzy C-means clustering and find more suitable cluster centers. The algorithm is validated on large data sets and proves to be more powerful and efficient compared to other algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Geochemistry & Geophysics
Shen Tan, Xin Zhang, Han Wang, Le Yu, Yanlei Du, Junjun Yin, Bingfang Wu
Summary: A novel self-supervised SAR denoising model is proposed, which can be trained without a noise-free image and restore spatial details through a hybrid loss function. Experiments show that the method outperforms traditional approaches in terms of noise reduction and feature preservation.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Maxwell Nogueira Peixoto, Michelangelo Villano
Summary: Synthetic aperture radar (SAR) is a high-resolution imaging radar used in satellite remote sensing, with staggered SAR being a novel mode of operation under consideration for future SAR missions. Proposed processing techniques aim to mitigate the impact of nadir echoes in staggered SAR images and recover useful signals through interpolation, leading to improved image quality at a reasonable additional computational cost.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Shasha Mao, Jinyuan Yang, Shuiping Gou, Licheng Jiao, Tao Xiong, Lin Xiong
Summary: SAR image registration is a crucial problem, where high precision is beneficial for quality improvement; utilizing multiple scales and deep forest method effectively enhances registration performance.
Article
Engineering, Aerospace
Michael Inggs
Summary: This document summarizes the achievements in synthetic aperture radar (SAR) technology during the 50-year existence of the Aerospace and Electronic Systems Society. Advances in radar technology, driven by the digital revolution, have led to the widespread application of SAR in various fields. The development of coherent radar during World War II enabled the formation of large synthetic apertures, resulting in microwave images with high resolution that are unaffected by time and weather. The article traces the history of SAR technology from airborne platforms to satellites and discusses its achievements. SAR technology has now entered the phase of commercial exploitation, with a significant increase in available systems.
IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE
(2023)
Article
Geochemistry & Geophysics
Hongyang An, Junjie Wu, Kah Chan Teh, Zhichao Sun, Zhongyu Li, Jianyu Yang
Summary: This article proposes an efficient video formation method for video SAR systems with reduced data, modeling the observed scene as a sum of low-rank and sparse tensors and using a tensor alternating direction method of multiplier. Compared to traditional imaging methods, the proposed approach greatly reduces the amount of data samples.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Kang Ni, Mingliang Zhai, Qianqian Wu, Minrui Zou, Peng Wang
Summary: This article presents a wavelet-driven subspace basis learning network for high-resolution synthetic aperture radar (SAR) image classification. The network utilizes wavelet feature denoising and reconstruction to learn deep feature statistics effectively, and maintains image structure and acquires robust feature statistics in the subspace basis learning module.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Engineering, Electrical & Electronic
Kaixin Zhao, Yaping Dai, Zhiyang Jia, Ye Ji
Summary: The paper proposes a general FCM clustering algorithm based on contraction mapping (cGFCM) for more general cases using Minkowski metric, providing an analytical method for calculating the parameters. The algorithm's core is the construction of a contraction mapping to update prototypes, guided by the Banach contraction mapping principle, with proven correctness and feasibility. Furthermore, experimental studies show that the proposed cGFCM algorithm extends FCM to more general cases with improved performance and reduced running time compared to other clustering methods.
Article
Engineering, Electrical & Electronic
Cheolkon Jung, L. C. Jiao, Maoguo Gong
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
(2012)
Article
Computer Science, Artificial Intelligence
Yutao Qi, Fang Liu, Meiyun Liu, Maoguo Gong, Licheng Jiao
APPLIED SOFT COMPUTING
(2012)
Article
Computer Science, Artificial Intelligence
Maoguo Gong, Xiaowei Chen, Lijia Ma, Qingfu Zhang, Licheng Jiao
APPLIED SOFT COMPUTING
(2013)
Article
Geochemistry & Geophysics
Jingjing Ma, Maoguo Gong, Zhiqiang Zhou
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2012)
Article
Geochemistry & Geophysics
Maoguo Gong, Yu Cao, Qiaodi Wu
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2012)
Article
Geochemistry & Geophysics
Shuang Wang, Kun Liu, Jingjing Pei, Maoguo Gong, Yachao Liu
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2013)
Article
Computer Science, Artificial Intelligence
Maoguo Gong, Yan Liang, Jiao Shi, Wenping Ma, Jingjing Ma
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2013)
Article
Computer Science, Hardware & Architecture
Huming Zhu, Yu Cao, Zhiqiang Zhou, Maoguo Gong, Licheng Jiao
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
(2013)
Article
Physics, Fluids & Plasmas
Jianshe Wu, Licheng Jiao, Chao Jin, Fang Liu, Maoguo Gong, Ronghua Shang, Weisheng Chen
Article
Physics, Fluids & Plasmas
Lijia Ma, Maoguo Gong, Qing Cai, Licheng Jiao
Article
Engineering, Electrical & Electronic
Jie Feng, L. C. Jiao, Xiangrong Zhang, Maoguo Gong, Tao Sun
Article
Environmental Sciences
Na Li, Deyun Zhou, Jiao Shi, Mingyang Zhang, Tao Wu, Maoguo Gong
Summary: Due to the superior spatial-spectral extraction capability of CNN, it has great potential in DR of HSIs. However, most CNN-based methods are supervised, while unsupervised methods often focus on data reconstruction rather than discriminability. Therefore, a deep fully convolutional embedding network (DFCEN) is proposed in this study to address these issues and improve the effectiveness of unsupervised learning.
Article
Environmental Sciences
Hongyu Zhao, Kaiyuan Feng, Yue Wu, Maoguo Gong
Summary: This paper proposes a novel feature extraction network that combines Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) for hyperspectral change detection tasks. The experimental results demonstrate that the proposed method yields reliable detection results and has fewer noise regions.
Article
Environmental Sciences
Junyu Gao, Maoguo Gong, Xuelong Li
Summary: In this paper, we propose a method named SwinCounter for object counting in remote sensing. The method addresses the issue of imbalanced object labels by introducing a Balanced MSE Loss and captures multi-scale information accurately using the attention mechanism. Experiments on the RSOC dataset demonstrate the competitiveness and superiority of the proposed method.
