梅晓光 (Xiaoguang Mei)

梅晓光 (Xiaoguang Mei)

博士，武汉大学电子信息学院副教授，博士生导师 (Ph.D., Associated Professor, Electronic Information School, Wuhan University)

👨‍🎓 Biosketch

Xiaoguang Mei received the B.S. degree in communication engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2007, the M.S. degree in communications and information systems from Central China Normal University, Wuhan, in 2011, and the Ph.D. degree in circuits and systems from the HUST, in 2016. From 2010 to 2012, he was a Software Engineer with the 722 Research Institute, China Shipbuilding Industry Corporation, Wuhan. From May 2016 to April 2019, he was a Post-Doctoral Fellow with the Electronic Information School, Wuhan University (WHU), Wuhan. From May 2019 to February 2020, he was an Assistant Professor with WHU. He is currently an Associate Professor with WHU. His research interests include hyperspectral image processing and computer vision.

📝 Publications

2024

  1. Yantao Chen, Yong Ma, Xiaoguang Mei, Lin Zhang, Zhigang Fu, and Jiayi Ma. “Triple-Task Mutual Consistency for Semi-Supervised 3D Medical Image Segmentation.” Computers in Biology and Medicine, 2024.
  2. Yingsong Cheng, Xinya Wang, Yong Ma, Xiaoguang Mei*, Minghui Wu, and Jiayi Ma. “General Hyperspectral Image Super-Resolution via Meta-Transfer Learning.” IEEE Transactions on Neural Networks and Learning Systems, 2024.
  3. Wendi Liu, Yong Ma, Xiaozhu Wang, Jun Huang, Qihai Chen, Hao Li, Xiaoguang Mei*, “UADNet: A Joint Unmixing and Anomaly Detection Network Based on Deep Clustering for Hyperspectral Image,” in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.33759341.
  4. Yifan Lu, Jiayi Ma, Xiaoguang Mei, Jun Huang, Xiao-Ping (Steven) Zhang, Feature Matching via Topology-Aware Graph Interaction Model. IEEE CAA J. Autom. Sinica 11(1): 113-130 (2024)
  5. Yang Yu, Erting Pan, Xinya Wang, Yuheng Wu, Xiaoguang Mei*, Jiayi Ma, Unmixing before Fusion: A Generalized Paradigm for Multi-modality-based Hyperspectral Image Synthesis, The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024, Seattle, USA, 2024
  6. Hebaixu Wang, Meiqi Gong, Xiaoguang Mei, Hao Zhang, and Jiayi Ma. “Deep Unfolded Network with Intrinsic Supervision for Pan-Sharpening”, Proceedings of the AAAI Conference on Artificial Intelligence 38.6 (AAAI 2024): 5419-5426.

2023

  1. Pan, E., Ma, Y., Mei, X., Huang, J., Chen, Q., & Ma, J. (2023). Hyperspectral image destriping and denoising from a task decomposition view. Pattern Recognition, 109832.
  2. Liu, W., Mei, X., Ma, Y., Huang, J., Chen, Q., & Li, H. (2023). Graph L1-Laplacians Regularized GMM for Hyperspectral Unmixing. IEEE Geoscience and Remote Sensing Letters.
  3. Pan, E., Ma, Y., Mei, X.*, Fan, F., Huang, J., & Ma, J. (2023). Progressive Hyperspectral Image Destriping with an Adaptive Frequencial Focus. IEEE Transactions on Geoscience and Remote Sensing.
  4. Chu, M., Ma, Y., Mei, X., Huang, J., & Fan, F. (2023). Learning-based correspondence classifier with self-attention hierarchical network. Applied Intelligence, 1-17.
  5. W. Dong, Y. Chen, A. Li, X. Mei & Y. Yang, “Automatic detection of adenoid hypertrophy on cone-beam computed tomography based on deep learning,” American Journal of Orthodontics and Dentofacial Orthopedics, 163(4), 553-560, 2023 (On the cover)
  6. Pan, E., Ma, Y., Mei, X., Fan, F., & Ma, J. (2023). Hyperspectral image denoising via spectral noise distribution bootstrap. Pattern Recognition, 142, 109699.
  7. Li, Z., Ma, Y., Mei, X., & Ma, J. (2023). Two-view correspondence learning using graph neural network with reciprocal neighbor attention. ISPRS Journal of Photogrammetry and Remote Sensing, 2023, 114-124.
  8. Peng, Z., Ma, Y., Zhang, Y., Li, H., Fan, F., & Mei, X. (2023). Seamless UAV hyperspectral image stitching using optimal seamline detection via graph cuts. IEEE Transactions on Geoscience and Remote Sensing.
  9. Cai, Z., Ma, Y., Huang, J., Mei, X., & Fan, F. (2023). Correlation-Guided Discriminative Cross-Modality Features Network for Infrared and Visible Image Fusion. IEEE Transactions on Instrumentation and Measurement.
  10. Sun, Y., Xu, H., Ma, Y., Wu, M., Mei, X., Huang, J., & Ma, J. (2023). Dual Spatial-spectral Pyramid Network with Transformer for Hyperspectral Image Fusion. IEEE Transactions on Geoscience and Remote Sensing.
  11. 靳淇文, 马泳, 樊凡, 黄珺, 李皞, & 梅晓光*. (2023). 生成对抗网络的无监督高光谱解混. Journal of Remote Sensing, 27(8).

2022

  1. A. Fan, J. Ma, X. Tian, X. Mei, W. Liu,”Coherent Point Drift Revisited for Non-Rigid Shape Matching and Registration,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
  2. 徐涵, 梅晓光*, 樊凡, 马泳, & 马佳义, 信息分离和质量引导的红外与可见光图像融合, 中国图象图形学报, 27(11), 3316-3330, 2022
  3. X. Wang, Y. Cheng, X. Mei, J. Jiang and J. Ma, “Group Shuffle and Spectral-Spatial Fusion for Hyperspectral Image Super-Resolution,” in IEEE Transactions on Computational Imaging, vol. 8, pp. 1223-1236, 2022
  4. E. Pan, Y. Ma, X. Mei*, J. Huang, F. Fan and J. Ma, “Letter: D2Net: Deep denoising network in frequency domain for hyperspectral image,” in IEEE/CAA Journal of Automatica Sinica
  5. H. Xu, Y. Sun, X. Mei, X. Tian and J. Ma, “Attention-Guided Polarization Image Fusion Using Salient Information Distribution,” in IEEE Transactions on Computational Imaging, vol. 8, pp. 1117-1130, 2022
  6. Y. Yao, M. Wang, G. Fan, W. Liu, Y. Ma, X. Mei, “Dictionary Learning-Cooperated Matrix Decomposition for Hyperspectral Target Detection. Remote Sensing,” 14(17), 4369, 2022
  7. Y. Yu, Y. Ma, X. Mei*, F. Fan, J. Huang, H. Li, “Multi-stage convolutional autoencoder network for hyperspectral unmixing. International Journal of Applied Earth Observation and Geoinformation,” 113, 102981, 2022
  8. S. Mei, Y. Ma, X. Mei, J. Huang, F. Fan, “S2-Net: Self-Supervision Guided Feature Representation Learning for Cross-Modality Images. IEEE/CAA Journal of Automatica Sinica,” 9(10), 1883-1885, 2022
  9. Y. Zhang, X. Mei, Y. Ma, X. Jiang, Z. Peng, J. Huang, “Hyperspectral Panoramic Image Stitching Using Robust Matching and Adaptive Bundle Adjustment,” Remote Sensing, 4(16): 4038, 2022
  10. Z. Le, J. Huang, H. Xu, F. Fan, Y. Ma, X. Mei, J. Ma, “UIFGAN: An unsupervised continual-learning generative adversarial network for unified image fusion,” Information Fusion, 2022
  11. Z. Li, Y. Ma, X. Mei, J. Huang and J. Ma, “Guided neighborhood affine subspace embedding for feature matching,” Pattern Recogn., vol. 124, pp. 108489, 2022
  12. Q. Jin, Y. Ma, X. Mei* and J. Ma, “TANet: An Unsupervised Two-Stream Autoencoder Network for Hyperspectral Unmixing,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.
  13. E. Pan, Y. Ma, X. Mei*, F. Fan, J. Huang and J. Ma, “SQAD: Spatial-Spectral Quasi-Attention Recurrent Network for Hyperspectral Image Denoising,” IEEE T. Geosci. Remote, vol. 60, pp. 1-14, 2022
  14. J. Ma, L. Tang, F. Fan, J. Huang, X. Mei, Y. Ma, “SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer,” IEEE/CAA Journal of Automatica Sinica, 9(7), 1200-1217, 2022. Hsue-shen Tsien Paper Award（钱学森论文奖，IEEE/CAA JAS唯一最佳论文奖） 🔥🔥
  15. Zhao-bing Qiu, Yong Ma, Fan Fan, Jun Huang, Ming-hui Wu, Xiao-guang Mei, A pixel-level local contrast measure for infrared small target detection, Defence Technology, Volume 18, Issue 9, 2022, Pages 1589-1601,
  16. 樊港辉, 马泳, 梅晓光*, 黄珺, 樊凡, & 李皞. 空域协同自编码器的高光谱异常检测. 中国图象图形学报, 27(10): 3116-3126, 2022
  17. C. Ma, J. Jiang, H. Li, X. Mei & C. Bai, “Hyperspectral Image Classification via Spectral Pooling and Hybrid Transformer. Remote Sensing,” 14(19), 4732, 2022

2021

  1. 徐涵, 梅晓光*, 樊凡, 马泳 and 马佳义, “分离表征和指标驱动的红外可见光图像融合,” 中国图象图形学报, 2021.
  2. Y. Zhang, Y. Ma, X. Dai, H. Li, X. Mei* and J. Ma, “Locality-constrained sparse representation for hyperspectral image classification,” Inform. Sciences, vol. 546, pp. 858-870, 2021.
  3. C. Sui, J. Zhou, C. Li, Q. Zhang, J. Feng, X. Mei, J. Wang, “Unsupervised hyperspectral band selection with multigraph integrated embedding and robust self-contained regression,” IEEE T. Geosci. Remote, vol. 60, pp. 1-15, 2021.
  4. E. Pan, Y. Ma, F. Fan, X. Mei and J. Huang, “Hyperspectral Image Classification across Different Datasets: A Generalization to Unseen Categories,” Remote Sens.-Basel, vol. 13, no. 9, pp. 1672, 2021.
  5. J. Ma, X. Ye, H. Zhou, X. Mei and F. Fan, “Loop-closure detection using local relative orientation matching,” IEEE T. Intell. Transp., 2021.
  6. Z. Qiu, Y. Ma, F. Fan, J. Huang, M. Wu and X. Mei, “A pixel-level local contrast measure for infrared small target detection,” Defence Technology, 2021.
  7. G. Fan, Y. Ma, X. Mei*, F. Fan, J. Huang and J. Ma, “Hyperspectral anomaly detection with robust graph autoencoders,” IEEE T. Geosci. Remote, 2021.
  8. H. Li, Y. Zhang, Y. Ma, X. Mei, S. Zeng and Y. Li, “Pairwise Elastic Net Representation-Based Classification for Hyperspectral Image Classification,” Entropy-Switz., vol. 23, no. 8, pp. 956, 2021.
  9. Z. Peng, Y. Ma, X. Mei*, J. Huang and F. Fan, “Hyperspectral Image Stitching via Optimal Seamline Detection,” IEEE Geosci. Remote S., vol. 19, pp. 1-5, 2021.
  10. Q. Jin, Y. Ma, F. Fan, J. Huang, X. Mei* and J. Ma, “Adversarial Autoencoder Network for Hyperspectral Unmixing,” IEEE T. Neur. Net. Lear., 2021.
  11. J. Ma, S. Wang, K. Zhang, Z. He, J. Huang and X. Mei, “Fast and Robust Loop-closure Detection via Convolutional Auto-encoder and Motion Consensus,” IEEE T. Ind. Inform., 2021.
  12. A. Fan, X. Jiang, Y. Ma, X. Mei and J. Ma, “Smoothness-Driven Consensus Based on Compact Representation for Robust Feature Matching,” IEEE T. Neur. Net. Lear., 2021.
  13. Y. Yu, Y. Ma, X. Mei, F. Fan, J. Huang and J. Ma, “A Spatial-Spectral Feature Descriptor for Hyperspectral Image Matching,” Remote Sens.-Basel, vol. 13, no. 23, pp. 4912, 2021.
  14. G. Fan, Y. Ma, J. Huang, X. Mei, and J. Ma, “Robust graph autoencoder for hyperspectral anomaly detection,” in ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021, pp. 1830–1834.
  15. Q. Jin, Y. Ma, X. Mei, H. Li, and J. Ma, “Utdn: An unsupervised two-stream dirichlet-net for hyperspectral unmixing,” in ICASSP 2021- 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021, pp. 1885–1889.
  16. E. Pan, Y. Ma, X. Mei, F. Fan, and J. Ma, “Unsupervised stacked capsule autoencoder for hyperspectral image classification,” in ICASSP 2021- 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021, pp. 1825–1829.
  17. K. Zhang, X. Jiang, X. Mei, H. Zhou, and J. Ma, “Motion field consensus with locality preservation: A geometric confirmation strategy for loop closure detection,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, pp. 445–451.

2020

  1. J. Chen, X. Li, L. Luo, X. Mei* and J. Ma, “Infrared and visible image fusion based on target-enhanced multiscale transform decomposition,” Inform. Sciences, vol. 508, pp. 64-78, 2020. (ESI Highly Cited Paper) 🔥🔥
  2. E. Pan, X. Mei, Q. Wang, Y. Ma and J. Ma, “Spectral-spatial classification for hyperspectral image based on a single GRU,” Neurocomputing, vol. 387, pp. 150-160, 2020.
  3. J. Ma, H. Xu, J. Jiang, X. Mei* and X. Zhang, “DDcGAN: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion,” IEEE T. Image Process., vol. 29, pp. 4980-4995, 2020. (ESI Highly Cited Paper) 🔥🔥
  4. J. Huang, Z. Le, Y. Ma, X. Mei and F. Fan, “A generative adversarial network with adaptive constraints for multi-focus image fusion,” Neural Computing and Applications, vol. 32, no. 18, pp. 15119-15129, 2020.
  5. Y. Wang, X. Mei, Y. Ma, J. Huang, F. Fan and J. Ma, “Learning to find reliable correspondences with local neighborhood consensus,” Neurocomputing, vol. 406, pp. 150-158, 2020.
  6. M. Wu, Y. Ma, F. Fan, X. Mei and J. Huang, “Infrared and visible image fusion via joint convolutional sparse representation,” JOSA A, vol. 37, no. 7, pp. 1105-1115, 2020.
  7. Y. Zhang, Z. Wan, X. Jiang and X. Mei*, “Automatic stitching for hyperspectral images using robust feature matching and elastic warp,” Ieee J.-Stars, vol. 13, pp. 3145-3154, 2020.
  8. Y. Ma, G. Fan, Q. Jin, J. Huang, X. Mei and J. Ma, “Hyperspectral anomaly detection via integration of feature extraction and background purification,” IEEE Geosci. Remote S., vol. 18, no. 8, pp. 1436-1440, 2020.

2019

  1. J. Wang, J. Chen, H. Xu, S. Zhang, X. Mei*, J. Huang, J. Ma, “Gaussian field estimator with manifold regularization for retinal image registration,” Signal Process., vol. 157, pp. 225-235, 2019.
  2. Y. Ma, Y. Wang, X. Mei, C. Liu, X. Dai, F. Fan, J. Huang, “Visible/infrared combined 3D reconstruction scheme based on nonrigid registration of multi-modality images with mixed features,” IEEE Access, vol. 7, pp. 19199-19211, 2019.
  3. Y. Ma, Q. Jin, X. Mei*, X. Dai, F. Fan, H. Li, J. Huang, “Hyperspectral unmixing with Gaussian mixture model and low-rank representation,” Remote Sens.-Basel, vol. 11, no. 8, pp. 911, 2019.
  4. X. Mei, E. Pan, Y. Ma, X. Dai, J. Huang, F. Fan, Q. Du, H. Zheng, J. Ma, “Spectral-spatial attention networks for hyperspectral image classification,” Remote Sens.-Basel, vol. 11, no. 8, pp. 963, 2019. (ESI Highly Cited Paper) 🔥🔥
  5. Q. Jin, Y. Ma, E. Pan, F. Fan, J. Huang, H. Li, C. Sui, X. Mei*, “Hyperspectral unmixing with Gaussian mixture model and spatial group sparsity,” Remote Sens.-Basel, vol. 11, no. 20, pp. 2434, 2019.
  6. C. Sui, C. Li, J. Feng and X. Mei, “Unsupervised manifold-preserving and weakly redundant band selection method for hyperspectral imagery,” IEEE T. Geosci. Remote, vol. 58, no. 2, pp. 1156-1170, 2019.
  7. Y. Ma, Y. Zhang, X. Mei*, X. Dai and J. Ma, “Multifeature-based discriminative label consistent k-svd for hyperspectral image classification,” Ieee J.-Stars, vol. 12, no. 12, pp. 4995-5008, 2019.
  8. J. Ma, X. Wang, Y. He, X. Mei and J. Zhao, “Line-based stereo slam by junction matching and vanishing point alignment,” IEEE Access, vol. 7, pp. 181800-181811, 2019.
  9. L. Luo, Q. Wan, J. Chen, Y. Wang, and X. Mei, “Drone image stitching guided by robust elastic warping and locality preserving matching,” in IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019, pp. 9212–9215.
  10. E. Pan, Y. Ma, X. Dai, F. Fan, J. Huang, X. Mei, and J. Ma, “GRU with spatial prior for hyperspectral image classification,” in IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019, pp. 967–970.
  11. Q. Jin, Y. Ma, X. Mei, X. Dai, H. Li, F. Fan, and J. Huang, “Gaussian mixture model for hyperspectral unmixing with low-rank representation,” in IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019, pp. 294–297.
  12. E. Pan, Y. Ma, X. Mei, X. Dai, F. Fan, X. Tian, and J. Ma, “Spectral-spatial classification of hyperspectral image based on a joint attention network,” in IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019, pp. 413–416.

2018

  1. X. Mei, Y. Ma, C. Li, F. Fan, J. Huang and J. Ma, “Robust GBM hyperspectral image unmixing with superpixel segmentation based low rank and sparse representation,” Neurocomputing, vol. 275, pp. 2783-2797, 2018.
  2. Y. Ma, C. Li, H. Li, X. Mei and J. Ma, “Hyperspectral image classification with discriminative kernel collaborative representation and Tikhonov regularization,” IEEE Geosci. Remote S., vol. 15, no. 4, pp. 587-591, 2018.
  3. Q. Du, A. Fan, Y. Ma, F. Fan, J. Huang and X. Mei*, “Infrared and visible image registration based on scale-invariant piifd feature and locality preserving matching,” IEEE Access, vol. 6, pp. 64107-64121, 2018.

2017

  1. F. Fan, Y. Ma, C. Li, X. Mei, J. Huang and J. Ma, “Hyperspectral image denoising with superpixel segmentation and low-rank representation,” Inform. Sciences, vol. 397, pp. 48-68, 2017.
  2. H. Guo, Y. Ma, X. Mei* and J. Ma, “Infrared and visible image fusion based on total variation and augmented Lagrangian,” JOSA A, vol. 34, no. 11, pp. 1961-1968, 2017. (Editors' Pick) 🔥🔥
  3. Y. Ma, J. Wang, H. Xu, S. Zhang, X. Mei and J. Ma, “Robust image feature matching via progressive sparse spatial consensus,” IEEE Access, vol. 5, pp. 24568-24579, 2017.
  4. C. Li, Y. Ma, X. Mei*, F. Fan, J. Huang and J. Ma, “Sparse unmixing of hyperspectral data with noise level estimation,” Remote Sens.-Basel, vol. 9, no. 11, pp. 1166, 2017. (code)
  5. Y. Ma, C. Li, X. Mei*, C. Liu and J. Ma, “Robust Sparse Hyperspectral Unmixing With $\ell_ {2, 1} $ Norm,” IEEE T. Geosci. Remote, vol. 55, no. 3, pp. 1227-1239, 2017. (code)

2016

  1. C. Li, Y. Ma, J. Huang, X. Mei, C. Liu and J. Ma, “GBM-based unmixing of hyperspectral data using bound projected optimal gradient method,” IEEE Geosci. Remote S., vol. 13, no. 7, pp. 952-956, 2016.
  2. C. Li, Y. Ma, X. Mei, C. Liu and J. Ma, “Hyperspectral image classification with robust sparse representation,” IEEE Geosci. Remote S., vol. 13, no. 5, pp. 641-645, 2016.
  3. J. Han, Y. Ma, J. Huang, X. Mei and J. Ma, “An infrared small target detecting algorithm based on human visual system,” IEEE Geosci. Remote S., vol. 13, no. 3, pp. 452-456, 2016.
  4. C. Li, Y. Ma, X. Mei, C. Liu and J. Ma, “Hyperspectral unmixing with robust collaborative sparse regression,” Remote Sens.-Basel, vol. 8, no. 7, pp. 588, 2016.
  5. J. Huang, Y. Ma, X. Mei, F. Fan, “A Hybrid Spatial-Spectral Denoising Method for Infrared Hyperspectral Images Using 2DPCA,” Infrared Phys. Techn., 2016.

2015

  1. T. Tian, X. Mei, Y. Yu, C. Zhang and X. Zhang, “Automatic visible and infrared face registration based on silhouette matching and robust transformation estimation,” Infrared Phys. Techn., vol. 69, pp. 145-154, 2015.
  2. X. Mei, Y. Ma, C. Li, F. Fan, J. Huang and J. Ma, “A real-time infrared ultra-spectral signature classification method via spatial pyramid matching,” Sensors-Basel, vol. 15, no. 7, pp. 15868-15887, 2015.
  3. C. Li, Y. Ma, J. Huang, X. Mei and J. Ma, “Hyperspectral image denoising using the robust low-rank tensor recovery,” JOSA A, vol. 32, no. 9, pp. 1604-1612, 2015.
  4. J. Huang, Y. Ma, F. Fan, X. Mei and Z. Liu, “A scene-based nonuniformity correction algorithm based on fuzzy logic,” Opt. Rev., vol. 22, no. 4, pp. 614-622, 2015.
  5. X. Mei, Y. Ma, F. Fan, C. Li, C. Liu, J. Huang, J. Ma, “Infrared ultraspectral signature classification based on a restricted Boltzmann machine with sparse and prior constraints,” Int. J. Remote Sens., vol. 36, no. 18, pp. 4724-4747, 2015.

2013

  1. B. Zhou, S. Wang, Y. Ma, X. Mei, B. Li, H. Li, F. Fan, “An infrared image impulse noise suppression algorithm based on fuzzy logic,” Infrared Phys. Techn., vol. 60, pp. 346-358, 2013.

📧 Contacts

照片 照片