Xiaoguang Mei (梅晓光)

Short Bio:

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. (中文主页) (Google Scholar)

Research Interests:
hyperspectral imagery, information fusion, machine learning, and pattern recognition.

Contact information:
Email:  image.png

Publications:

Journal papers:

  1. Y. Zhang, Y. Ma, X. Dai, H. Li, X. Mei*, and J. Ma, “Locality-constrained sparse representation for hyperspectral image classification,” Information Sciences, vol. 546, pp. 850–870, 2021.[code]
  2. J. Chen, X. Li, L. Luo, X. Mei*, and J. Ma, “Infrared and visible image fusion based on target-enhanced multiscale transform decomposition,” Information Sciences, vol. 508, pp. 64–78, 2020.[code]
  3. 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.
  4. 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 Transactions on Image Processing, vol. 29, pp. 4980–4995, 2020.[code]
  5. 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 \& APPLICATIONS, 2020. [code]
  6. Y. Wang, X. Mei, Y. Ma, J. Huang, F. Fan, and J. Ma, “Learning to find reliable correspondences with local neighborhood consensus,” Neurocomputing, 2020.
  7. 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, pp. 1105–1115, 2020.
  8. Y. Zhang, Z. Wan, X. Jiang, and X. Mei*, “Automatic Stitching for Hyperspectral Images Using Robust Feature Matching and Elastic Warp,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3145–3154, 2020. [code]
  9. 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 Geoscience and Remote Sensing Letters, 2020. [code]
  10. J. Wang, J. Chen, H. Xu, S. Zhang, X. Mei*, J. Huang, and J. Ma, “Gaussian field estimator with manifold regularization for retinal image registration,” Signal Processing, vol. 157, pp. 225–235, 2019.[code]
  11. Y. Ma, Y. Wang, X. Mei, C. Liu, X. Dai, F. Fan, and 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.
  12. Y. Ma, Q. Jin, X. Mei*, X. Dai, F. Fan, H. Li, and J. Huang, “Hyperspectral unmixing with Gaussian mixture model and low-rank representation,” Remote Sensing, vol. 11, p. 911, 2019. [code]
  13. X. Mei, E. Pan, Y. Ma, X. Dai, J. Huang, F. Fan, Q. Du, H. Zheng, and J. Ma, “Spectral-spatial attention networks for hyperspectral image classification,” Remote Sensing, vol. 11, p. 963, 2019. [code]
  14. Q. Jin, Y. Ma, E. Pan, F. Fan, J. Huang, H. Li, C. Sui, and X. Mei*, “Hyperspectral Unmixing with Gaussian Mixture Model and Spatial Group Sparsity,” Remote Sensing, vol. 11, p. 2434, 2019. [code]
  15. C. Sui, C. Li, J. Feng, and X. Mei, “Unsupervised manifold-preserving and weakly redundant band selection method for hyperspectral imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 1156–1170, 2019.
  16. Y. Ma, Y. Zhang, X. Mei*, X. Dai, and J. Ma, “Multifeature-Based Discriminative Label Consistent K-SVD for Hyperspectral Image Classification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, pp. 4995–5008, 2019.
  17. 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.
  18. 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. [code]
  19. Y. Ma, C. Li, H. Li, X. Mei, and J. Ma, “Hyperspectral image classification with discriminative kernel collaborative representation and Tikhonov regularization,” IEEE Geoscience and Remote Sensing Letters, vol. 15, pp. 587–591, 2018.
  20. 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.
  21. F. Fan, Y. Ma, C. Li, X. Mei, J. Huang, and J. Ma, “Hyperspectral image denoising with superpixel segmentation and low-rank representation,” Information Sciences, vol. 397, pp. 48–68, 2017.
  22. 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, pp. 1961–1968, 2017.
  23. 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.
  24. C. Li, Y. Ma, X. Mei*, F. Fan, J. Huang, and J. Ma, “Sparse unmixing of hyperspectral data with noise level estimation,” Remote Sensing, vol. 9, p. 1166, 2017. [code]
  25. Y. Ma, C. Li, X. Mei*, C. Liu, and J. Ma, “Robust Sparse Hyperspectral Unmixing With $$\backslash$ell\_ $\{$2, 1$\}$ $ Norm,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, pp. 1227–1239, 2017. [code]
  26. 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 Geoscience and Remote Sensing Letters, vol. 13, pp. 952–956, 2016.
  27. C. Li, Y. Ma, X. Mei, C. Liu, and J. Ma, “Hyperspectral image classification with robust sparse representation,” IEEE Geoscience and Remote Sensing Letters, vol. 13, pp. 641–645, 2016.
  28. J. Han, Y. Ma, J. Huang, X. Mei, and J. Ma, “An infrared small target detecting algorithm based on human visual system,” IEEE Geoscience and Remote Sensing Letters, vol. 13, pp. 452–456, 2016.
  29. C. Li, Y. Ma, X. Mei, C. Liu, and J. Ma, “Hyperspectral unmixing with robust collaborative sparse regression,” Remote Sensing, vol. 8, p. 588,
  30. Y. M. X. M. J Huang, “A Hybrid Spatial-Spectral Denoising Method for Infrared Hyperspectral Images Using 2DPCA,” Infrared Physics \& Technology, 2016.
  31. 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 Physics \& Technology, vol. 69, pp. 145–154, 2015.
  32. 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, vol. 15, pp. 15868–15887, 2015.
  33. 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, pp. 1604–1612, 2015.
  34. J. Huang, Y. Ma, F. Fan, X. Mei, and Z. Liu, “A scene-based nonuniformity correction algorithm based on fuzzy logic,” Optical Review, vol. 22, pp. 614–622, 2015. 32.
  35. X. Mei, Y. Ma, F. Fan, C. Li, C. Liu, J. Huang, and J. Ma, “Infrared ultraspectral signature classification based on a restricted Boltzmann machine with sparse and prior constraints,” International Journal of Remote Sensing, vol. 36, pp. 4724–4747, 2015.
  36. B. Zhou, S. Wang, Y. Ma, X. Mei, B. Li, H. Li, and F. Fan, “An infrared image impulse noise suppression algorithm based on fuzzy logic,” Infrared Physics \& Technology, vol. 60, pp. 346–358, 2013.

Conference papers:

  1. L. Luo, Q. Wan, J. Chen, Y. Wang and X. Mei, “Drone Image Stitching Guided by Robust Elastic Warping and Locality Preserving Matching,” IGARSS 2019 – 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 9212-9215 (Oral)
  2. E. Pan, Y. Ma, X. Dai, F. Fan, J. Huang, X. Mei, and J. Ma, “GRU with Spatial Prior for Hyperspectral Image Classification,” IGARSS 2019 – 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 967-970 (Oral)
  3. 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,” IGARSS 2019 – 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 294-297 (Oral)
  4. 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,” IGARSS 2019 – 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 413-416 (Oral)
  5. F Fan, Y. Ma, X Dai, and X. Mei, “An optimization model for infrared image enhancement method based on p-q norm constrained by saliency value”, Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106152P (10 April 2018) (Oral)
  6. H. Xia, G. Zhang, M. Chen and X. Mei, “Two-Round Cooperation Based Spectrum Sensing in Cognitive Radio Networks,” 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM), Chengdu, 2010, pp. 1-5