Exploring the Potential of Conditional Adversarial Networks for Optical and SAR Image Matching

Adam: A Method for Stochastic Optimization

Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946

Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography

Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893

Image-to-Image Translation with Conditional Adversarial Networks

Isola, P., Zhu, J.-Y., Zhou, T., & Efros, A. A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.632 · Cited by 22,930

Generative Adversarial Nets

Labaca-Castro, R. (2023) · Springer eBooks · doi:10.1007/978-3-658-40442-0_9 · Cited by 21,119

GAN（Generative Adversarial Nets）

淳司, 柴. (2017) · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · doi:10.3156/jsoft.29.5_177_2 · Cited by 20,507

Object recognition from local scale-invariant features

Lowe, D. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790410 · Cited by 16,472

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z., et al. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.19 · Cited by 12,696

Image registration methods: a survey

Zitová, B., & Flusser, J. (2003) · Image and Vision Computing · doi:10.1016/s0262-8856(03)00137-9 · Cited by 6,423

Untitled work

(2017) · International Conference on Machine Learning · Cited by 6,382

“Least squares generative adversarial networks,”

Mao, X., Li, Q., Xie, H., Lau, R. Y. K., Wang, Z., & Smolley, S. P. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.304 · Cited by 5,437

Deep learning in remote sensing applications: A meta-analysis and review

Ma, L., Liu, Y., Zhang, X., Ye, Y., Yin, G., & Johnson, B. A. (2019) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.04.015 · Cited by 2,456

How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions

Sun, A. Y., & Scanlon, B. R. (2019) · Environmental Research Letters · doi:10.1088/1748-9326/ab1b7d · Cited by 585

A review of multimodal image matching: Methods and applications

Jiang, X., Ma, J., Xiao, G., Shao, Z., & Guo, X. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.02.012 · Cited by 561

Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives

Zhu, X. X., Montazeri, S., Ali, M., Hua, Y., Wang, Y., Mou, L., Shi, Y., Xu, F., & Bamler, R. (2021) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2020.3046356 · Cited by 422

THE SEN1-2 DATASET FOR DEEP LEARNING IN SAR-OPTICAL DATA FUSION

Schmitt, M., Hughes, L. H., & Zhu, X. X. (2018) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-iv-1-141-2018 · Cited by 374

Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks

de Bem, P. P., Júnior, O. A. D. C., Guimarães, R. F., & Gomes, R. A. T. (2020) · Remote Sensing · doi:10.3390/rs12060901 · Cited by 299

Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection

Luppino, L. T., Kampffmeyer, M., Bianchi, F. M., Moser, G., Serpico, S. B., Jenssen, R., & Anfinsen, S. N. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3056196 · Cited by 211

SAR-to-Optical Image Translation Using Supervised Cycle-Consistent Adversarial Networks

Wang, L., Xu, X., Yu, Y., Yang, R. Q., Gui, R., Xu, Z., & Pu, F. (2019) · IEEE Access · doi:10.1109/access.2019.2939649 · Cited by 191

SAR-to-Optical Image Translation Based on Conditional Generative Adversarial Networks—Optimization, Opportunities and Limits

Reyes, M. F., Auer, S., Merkle, N., Henry, C., & Schmitt, M. (2019) · Remote Sensing · doi:10.3390/rs11172067 · Cited by 176

Automatic Registration of Optical and SAR Images Via Improved Phase Congruency Model

Xiang, Y., Tao, R., Wang, F., You, H., & Han, B. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3026162 · Cited by 150

Registration of Multimodal Remote Sensing Image Based on Deep Fully Convolutional Neural Network

Zhang, H., Ni, W., Yan, W., Xiang, D., Wu, J., Yang, X., & Hui, B. (2019) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2019.2916560 · Cited by 145

Survey of Deep-Learning Approaches for Remote Sensing Observation Enhancement

Tsagkatakis, G., Aidini, A., Fotiadou, K., Giannopoulos, M., Pentari, A., & Tsakalides, P. (2019) · Sensors · doi:10.3390/s19183929 · Cited by 144

Deep learning for processing and analysis of remote sensing big data: a technical review

Zhang, X., Zhou, Y., & Luo, J. (2021) · Big Earth Data · doi:10.1080/20964471.2021.1964879 · Cited by 122

Multi-Temporal Sentinel-1 and -2 Data Fusion for Optical Image Simulation

He, W. P., & Yokoya, N. (2018) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi7100389 · Cited by 109

Advances and Opportunities in Remote Sensing Image Geometric Registration: A systematic review of state-of-the-art approaches and future research directions

Feng, R., Shen, H., Bai, J., & Li, X. (2021) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2021.3081763 · Cited by 108

Multimodal Remote Sensing Image Registration Methods and Advancements: A Survey

Zhang, X., Leng, C., Hong, Y., Pei, Z., Cheng, I., & Basu, A. (2021) · Remote Sensing · doi:10.3390/rs13245128 · Cited by 115

Local feature matching using deep learning: A survey

Xu, S., Chen, S., Xu, R., Wang, C., Lu, P., & Guo, L. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102344 · Cited by 107

Reciprocal translation between SAR and optical remote sensing images with cascaded-residual adversarial networks

Fu, S., Xu, F., & Jin, Y. Q. (2021) · Science China Information Sciences · doi:10.1007/s11432-020-3077-5 · Cited by 106

A review and meta-analysis of Generative Adversarial Networks and their applications in remote sensing

Jozdani, S. E., Chen, D., Pouliot, D., & Johnson, B. A. (2022) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2022.102734 · Cited by 106

LDGAN: A Synthetic Aperture Radar Image Generation Method for Automatic Target Recognition

Cao, C., Cao, Z., & Cui, Z. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2957453 · Cited by 86

A comprehensive review on remote sensing image registration

Paul, S., & Pati, U. C. (2021) · International Journal of Remote Sensing · doi:10.1080/01431161.2021.1906985 · Cited by 85

Detection of geochemical anomalies related to mineralization using the GANomaly network

Luo, Z., Zuo, R., Xiong, Y., & Wang, X. (2021) · Applied Geochemistry · doi:10.1016/j.apgeochem.2021.105043 · Cited by 84

OS-PC: Combining Feature Representation and 3-D Phase Correlation for Subpixel Optical and SAR Image Registration

Xiang, Y., Tao, R., Wan, L., Wang, F., & You, H. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.2976865 · Cited by 82

Remote Sensing Data Fusion With Generative Adversarial Networks: State-of-the-art methods and future research directions

Liu, P., Li, J., Wang, L., & He, G. (2022) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2022.3165967 · Cited by 82

Advances and Challenges in Multimodal Remote Sensing Image Registration

Zhu, B., Zhou, L., Pu, S., Fan, J., & Ye, Y. (2023) · IEEE Journal on Miniaturization for Air and Space Systems · doi:10.1109/jmass.2023.3244848 · Cited by 80

A Survey on SAR and Optical Satellite Image Registration

Sommervold, O., Gazzea, M., & Arghandeh, R. (2023) · Remote Sensing · doi:10.3390/rs15030850 · Cited by 79

MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data

Hu, J., Hong, D., & Zhu, X. X. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2924113 · Cited by 78

Synthetic Aperture Radar for Geosciences

Meng, L., Yan, C., Lv, S., Sun, H., Xue, S., Li, Q., Zhou, L., Edwing, D., Edwing, K., Geng, X., et al. (2024) · Reviews of Geophysics · doi:10.1029/2023rg000821 · Cited by 89

A SAR-to-Optical Image Translation Method Based on Conditional Generation Adversarial Network (cGAN)

Li, Y., Fu, R., Meng, X., Jin, W., & Shao, F. (2020) · IEEE Access · doi:10.1109/access.2020.2977103 · Cited by 73

GAN-based SAR and optical image translation for wildfire impact assessment using multi-source remote sensing data

Hu, X., Zhang, P., Yifang Ban, A., & Rahnemoonfar, M. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113522 · Cited by 61

Mining Hard Negative Samples for SAR-Optical Image Matching Using Generative Adversarial Networks

Hughes, L. H., Schmitt, M., & Zhu, X. X. (2018) · Remote Sensing · doi:10.3390/rs10101552 · Cited by 59

A comprehensive review of spatial-temporal-spectral information reconstruction techniques

Wang, Q., Tang, Y., Ge, Y., Xie, H., Tong, X., & Atkinson, P. M. (2023) · Science of Remote Sensing · doi:10.1016/j.srs.2023.100102 · Cited by 54

Self-Similarity Features for Multimodal Remote Sensing Image Matching

Xiong, X., Jin, G., Xu, Q., & Zhang, H. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3131489 · Cited by 52

Dialectical GAN for SAR Image Translation: From Sentinel-1 to TerraSAR-X

Ao, D., Dumitru, C. O., Schwarz, G., & Datcu, M. P. (2018) · Remote Sensing · doi:10.3390/rs10101597 · Cited by 52

Edge-Preserving Convolutional Generative Adversarial Networks for SAR-to-Optical Image Translation

Guo, J., He, C., Zhang, M., Li, Y., Gao, X., & Song, B. (2021) · Remote Sensing · doi:10.3390/rs13183575 · Cited by 51

Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images

Fan, Z., Zhang, L., Liu, Y., Wang, Q., & Sisi Zlatanova, B. (2021) · Remote Sensing · doi:10.3390/rs13173535 · Cited by 48

Two-Stage Registration of SAR Images With Large Distortion Based on Superpixel Segmentation

Xiang, D., Pan, X., Ding, H., Cheng, J., & Sun, X. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3392971 · Cited by 48

Target Recognition of SAR Image Based on CN-GAN and CNN in Complex Environment

Mao, C., Huang, L., Xiao, Y., He, F., & Liu, Y. (2021) · IEEE Access · doi:10.1109/access.2021.3064362 · Cited by 49

A Distribution and Structure Match Generative Adversarial Network for SAR Image Classification

Ren, Z., Hou, B., Wu, Q., Wen, Z., & Jiao, L. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2959120 · Cited by 46

Explore Better Network Framework for High-Resolution Optical and SAR Image Matching

Zhang, H., Lei, L., Ni, W., Tang, T., Wu, J., Xiang, D., & Kuang, G. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3126939 · Cited by 45

OS-Flow: A Robust Algorithm for Dense Optical and SAR Image Registration

Xiang, Y., Wang, F., Wan, L., Jiao, N., & You, H. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2905585 · Cited by 44

Multiscale Generative Adversarial Network Based on Wavelet Feature Learning for SAR-to-Optical Image Translation

Li, H., Gu, C., Wu, D., Cheng, G., Guo, L., & Liu, H. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3211415 · Cited by 42

Deep Learning for SAR-Optical Image Matching

Hughes, L. H., Merkle, N., Bürgmann, T., Auer, S., & Schmitt, M. (2019) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2019.8898635 · Cited by 41

Shuffle GAN With Autoencoder: A Deep Learning Approach to Separate Moving and Stationary Targets in SAR Imagery

Pu, W. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3060747 · Cited by 41

Image Recognition of Crop Diseases and Insect Pests Based on Deep Learning

Xin, M., & Wang, Y. (2021) · Wireless Communications and Mobile Computing · doi:10.1155/2021/5511676 · Cited by 45

Comparative Analysis of Edge Information and Polarization on SAR-to-Optical Translation Based on Conditional Generative Adversarial Networks

Zhang, Q., Liu, X., Liu, M., Zou, X., Zhu, L., & Ruan, X. (2021) · Remote Sensing · doi:10.3390/rs13010128 · Cited by 37

Reconstruction of kiwifruit fruit geometry using a CGAN trained on a synthetic dataset

Olatunji, J. R., Redding, G. P., Rowe, C. L., & East, A. R. (2020) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2020.105699 · Cited by 37

A Comparative Review of Manifold Learning Techniques for Hyperspectral and Polarimetric SAR Image Fusion

Hu, J., Hong, D., Wang, Y., & Zhu, X. X. (2019) · Remote Sensing · doi:10.3390/rs11060681 · Cited by 34

Deceptive jamming template synthesis for SAR based on generative adversarial nets

Fan, W., Zhou, F., Zhang, Z., Bai, X., & Tian, T. (2020) · Signal Processing · doi:10.1016/j.sigpro.2020.107528 · Cited by 33

A Robust Two-Stage Registration Algorithm for Large Optical and SAR Images

Xiang, Y., Jiao, N., Wang, F., & You, H. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3133863 · Cited by 33

Target-Oriented SAR Imaging for SCR Improvement via Deep MF-ADMM-Net

Li, M., Wu, J., Huo, W., Jiang, R., Li, Z., Yang, J., & Li, H. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3145568 · Cited by 33

Multi-View HRRP Generation With Aspect-Directed Attention GAN

Song, Y., Zhou, Q., Yang, W., Wang, Y., Hu, C., & Hu, X. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3204439 · Cited by 32

Optical and SAR Image Dense Registration Using a Robust Deep Optical Flow Framework

Zhang, H., Lei, L., Ni, W., Yang, X., Tang, T., Cheng, K., Xiang, D., & Kuang, G. (2023) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2023.3235535 · Cited by 32

A Global-to-Local Algorithm for High-Resolution Optical and SAR Image Registration

Xiang, Y., Wang, X., Wang, F., You, H., Qiu, X., & Fu, K. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3309855 · Cited by 32

Conditional Diffusion Model With Spatial-Frequency Refinement for SAR-to-Optical Image Translation

Qin, J., Wang, K. W., Zou, B., Zhang, L., & van de Weijer, J. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3491826 · Cited by 36

Modality-Free Feature Detector and Descriptor for Multimodal Remote Sensing Image Registration

Cui, S., Xu, M., Ma, A., & Zhong, Y. (2020) · Remote Sensing · doi:10.3390/rs12182937 · Cited by 32

MS-GAN: Learn to Memorize Scene for Unpaired SAR-to-Optical Image Translation

Guo, Z., Zhang, Z., Cai, Q., Liu, J., Fan, Y., & Mei, S. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3411691 · Cited by 29

K-Means Clustering Guided Generative Adversarial Networks for SAR-Optical Image Matching

Du, W.-L., Zhou, Y. Z., Zhao, J., & Tian, X. (2020) · IEEE Access · doi:10.1109/access.2020.3042213 · Cited by 29

Selective Adversarial Adaptation-Based Cross-Scene Change Detection Framework in Remote Sensing Images

Yang, M., Jiao, L., Hou, B., Liu, F., & Yang, S. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3001584 · Cited by 28

Sar2color: Learning Imaging Characteristics of SAR Images for SAR-to-Optical Transformation

Guo, Z., Guo, H., Liu, X., Zhou, W., Wang, Y., & Fan, Y. (2022) · Remote Sensing · doi:10.3390/rs14153740 · Cited by 28

Unsupervised Multistep Deformable Registration of Remote Sensing Imagery Based on Deep Learning

Papadomanolaki, M., Christodoulidis, S., Karantzalos, K. G., & Vakalopoulou, M. (2021) · Remote Sensing · doi:10.3390/rs13071294 · Cited by 27

An Overview on the Generation and Detection of Synthetic and Manipulated Satellite Images

Abady, L., Cannas, E. D., Bestagini, P., Tondi, B., Tubaro, S., & Barni, M. (2022) · APSIPA Transactions on Signal and Information Processing · doi:10.1561/116.00000142 · Cited by 28

SAR-to-Optical Image Translation via an Interpretable Network

Zhang, M., Zhang, P., Zhang, Y., Yang, M., Li, X., Dong, X., & Yang, L. (2024) · Remote Sensing · doi:10.3390/rs16020242 · Cited by 26

Deep Learning Meets SAR

Zhu, X. X., Montazeri, S., Ali, M., Hua, Y., Wang, Y., Mou, L., Shi, Y., Xu, F., & Bamler, R. (2020) · elib (German Aerospace Center) · doi:10.48550/arxiv.2006.10027 · Cited by 26

Cost-Sensitive Awareness-Based SAR Automatic Target Recognition for Imbalanced Data

Cao, C., Cui, Z., Wang, L., Wang, J., Cao, Z., & Yang, J. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3068447 · Cited by 24

A SAR-to-Optical Image Translation Method Based on PIX2PIX

Zuo, Z., & Li, Y. (2021) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss47720.2021.9555111 · Cited by 24

A Rotation-Invariant Optical and SAR Image Registration Algorithm Based on Deep and Gaussian Features

Li, Z., Zhang, H., & Huang, Y. (2021) · Remote Sensing · doi:10.3390/rs13132628 · Cited by 23

A Semi-Supervised Image-to-Image Translation Framework for SAR–Optical Image Matching

Du, W.-L., Zhou, Y. Z., Zhu, H., Zhao, J., Shao, Z., & Tian, X. (2022) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2022.3223353 · Cited by 23

Multi-Scale translation method from SAR to optical remote sensing images based on conditional generative adversarial network

Kong, Y., Liu, S., & Peng, X. (2022) · International Journal of Remote Sensing · doi:10.1080/01431161.2022.2072179 · Cited by 22

A Demand-Driven SAR Target Sample Generation Method for Imbalanced Data Learning

Cao, C., Cui, Z., Wang, L., Wang, J., Cao, Z., & Yang, J. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3134674 · Cited by 20

MOTIF: MULTI-ORIENTATION TENSOR INDEX FEATURE DESCRIPTOR FOR SAR-OPTICAL IMAGE REGISTRATION

Yao, Y., Zhang, B., Wan, Y., & zhang, Y. (2022) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xliii-b2-2022-99-2022 · Cited by 18

LabelRS: An Automated Toolbox to Make Deep Learning Samples from Remote Sensing Images

Li, J., Meng, L., Yang, B., Tao, C., Li, L., & Zhang, W. (2021) · Remote Sensing · doi:10.3390/rs13112064 · Cited by 18

Learning SAR-to-Optical Image Translation via Diffusion Models With Color Memory

Guo, Z., Liu, J., Cai, Q., Zhang, Z., & Mei, S. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3439516 · Cited by 24

A Dual-Generator Translation Network Fusing Texture and Structure Features for SAR and Optical Image Matching

Nie, H., Fu, Z., Tang, B., Li, Z., Chen, S., & Wang, L. (2022) · Remote Sensing · doi:10.3390/rs14122946 · Cited by 17

Transfer Learning for Optical and SAR Data Correspondence Identification With Limited Training Labels

Zhang, M., Li, W., Tao, R., & Wang, S. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3044643 · Cited by 16

Image Template Matching via Dense and Consistent Contrastive Learning

Li, B., Wu, L. Y., Liu, D., Chen, H., Ye, Y., & Xie, X. (2023) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme55011.2023.00229 · Cited by 15

A SEMI-SUPERVISED APPROACH TO SAR-OPTICAL IMAGE MATCHING

Hughes, L. H., & Schmitt, M. (2019) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-iv-2-w7-71-2019 · Cited by 15

Exploring the Potential of Unsupervised Image Synthesis for SAR-Optical Image Matching

Du, W.-L., Zhou, Y. Z., Zhao, J., Tian, X., Yang, Z. H., & Bian, F. (2021) · IEEE Access · doi:10.1109/access.2021.3079327 · Cited by 15

SAR-to-optical image translation for quality enhancement

Luo, Y. P., & Pi, D. (2022) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-021-03665-0 · Cited by 14

ADD-UNet: An Adjacent Dual-Decoder UNet for SAR-to-Optical Translation

Luo, Q., Li, H., Chen, Z., & Li, J. (2023) · Remote Sensing · doi:10.3390/rs15123125 · Cited by 14

RTV-SIFT: Harnessing Structure Information for Robust Optical and SAR Image Registration

Pang, S., Ge, J., Hu, L., Guo, K., Zheng, Y., Zheng, C., Zhang, W., & Liang, J. (2023) · Remote Sensing · doi:10.3390/rs15184476 · Cited by 13

Multimodal remote sensing image registration： a survey

Bai, Z., & Ye, Y. (2024) · Journal of Image and Graphics · doi:10.11834/jig.230737 · Cited by 13

Parallel Connected Generative Adversarial Network with Quadratic Operation for SAR Image Generation and Application for Classification

He, C., Xiong, D., Zhang, Q., & Liao, M. (2019) · Sensors · doi:10.3390/s19040871 · Cited by 13

Body Orientation and Vital Sign Measurement With IR-UWB Radar Network

Yang, X., Yu, Y., Qian, H., Zhang, X., & Zhang, L. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9176528 · Cited by 13

Generating planar distributions of soot particles from luminosity images in turbulent flames using deep learning

Zhang, W., Dong, X. Y., Liu, C., Nathan, G. J., Dally, B. B., Rowhani, A., & Sun, Z. (2021) · Applied Physics B · doi:10.1007/s00340-020-07571-9 · Cited by 13

Registration of Multisensor Images through a Conditional Generative Adversarial Network and a Correlation-Type Similarity Measure

Maggiolo, L., Solarna, D., Moser, G., & Serpico, S. B. (2022) · Remote Sensing · doi:10.3390/rs14122811 · Cited by 13

Spatial and Spectral Translation of Landsat 8 to Sentinel-2 Using Conditional Generative Adversarial Networks

Mukherjee, R., & Liu, D. (2023) · Remote Sensing · doi:10.3390/rs15235502 · Cited by 12

Data Augmentation Method of SAR Image Dataset Based on Wasserstein Generative Adversarial Networks

Lu, Q., Jiang, H., Li, G., & Ye, W. (2019) · International Conference on Electronic Engineering and Informatics (EEI) · doi:10.1109/eei48997.2019.00111 · Cited by 12

Energy-Based Models in Earth Observation: From Generation to Semisupervised Learning

Castillo-Navarro, J., Saux, B. L., Boulch, A., & Lefèvre, S. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3126428 · Cited by 12

Siamese Detail Difference and Self-Inverse Network for Forest Cover Change Extraction Based on Landsat 8 OLI Satellite Images

Guo, Y., Long, T., Jiao, W., Zhang, X. M., He, G., Wang, W., Peng, Y., & Xiao, H. (2022) · Remote Sensing · doi:10.3390/rs14030627 · Cited by 13

Multimodal Image Registration for GPS-denied UAV Navigation Based on Disentangled Representations

Li, H., Liu, Z., Lyu, Y., & Wu, F. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10161567 · Cited by 11

Deep Image Prior Amplitude SAR Image Anonymization

Cannas, E. D., Mandelli, S., Bestagini, P., Tubaro, S., & Delp, E. J. (2023) · Remote Sensing · doi:10.3390/rs15153750 · Cited by 11

Shared contents alignment across multiple granularities for robust SAR-optical image matching

Zhang, H. R., Yue, Y., Li, H., Liu, P., Jia, Y., He, W. P., & Wang, Z. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102298 · Cited by 11

SAR Image Classification with Knowledge Distillation and Class Balancing for Long-Tailed Distributions

Jahan, C. S., Savakis, A. E., & Blasch, E. (2022) · Multidimensional Signal Processing Workshop · doi:10.1109/ivmsp54334.2022.9816201 · Cited by 10

GAN with ASPP for SAR Image to Optical Image Conversion

Shao, Z., Zhang, X., & Zhang, T. (2022) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss46834.2022.9883157 · Cited by 10

Building Instance Classification using Social Media Images

Hoffmann, E. J., Werner, M., & Zhu, X. X. (2019) · Joint Urban Remote Sensing Event (JURSE) · doi:10.1109/jurse.2019.8809056 · Cited by 10

Deriving Non-Cloud Contaminated Sentinel-2 Images with RGB and Near-Infrared Bands from Sentinel-1 Images Based on a Conditional Generative Adversarial Network

Xiong, Q., Di, L., Feng, Q., Liu, D., Liu, W., Zan, X., Zhang, L., Zhu, D., Liu, Z., Yao, X., et al. (2021) · Remote Sensing · doi:10.3390/rs13081512 · Cited by 9

High-Precision Pixelwise SAR–Optical Image Registration via Flow Fusion Estimation Based on an Attention Mechanism

Yu, Q., Jiang, Y., Zhao, W., & Sun, T. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3172449 · Cited by 9

A Review on Remote Sensing Data Fusion with Generative Adversarial Networks (GAN)Preprint

Liu, P. (2021) · doi:10.36227/techrxiv.16607261 · Cited by 9

MSG: Robust Multimodal Remote Sensing Image Matching Using Side Window Gaussian Space

Zheng, C., Li, S., Wang, C., & Zhang, B. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3591504 · Cited by 8

On the Possibility of Conditional Adversarial Networks for SAR Template Generation

Merkle, N., Fischer, P., Auer, S., & Müller, R. (2017) · elib (German Aerospace Center) · Cited by 1

On the possibility of conditional adversarial networks for multi-sensor image matching

Merkle, N., Fischer, P., Auer, S., & Müller, R. (2017) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2017.8127535 · Cited by 32

A Novel Approach for SAR to Optical Image Registration using Deep Learning

James, L., Nidamanuri, ‪. R., Krishnan, S. M., Anjaneyulu, R. V. G., & Srinivas, C. V. (2023) · International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS) · doi:10.1109/migars57353.2023.10064578 · Cited by 4

OS-CycleGAN: Modified CycleGAN-Based Descriptors for Optical and SAR Image Matching

Liaghat, A., Helfroush, M. S., Norouzi, J., Danyali, H., & Guerrero, J. M. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3575193 · Cited by 5

Structure similarity virtual map generation network for optical and SAR image matching

Chen, S., & Mei, L. (2024) · Frontiers in Physics · doi:10.3389/fphy.2024.1287050