本科：1996.9 --- 2000.7, 武汉测绘科技大学 硕士：2000.9 --- 2002.7, 武汉大学 博士：2003.9 --- 2006.7, 中国科学院遥感应用研究所

[1] F. Chen, K. Wang, T. Van deVoorde, T. Tang, “Mapping urban land cover from high spatial resolution hyperspectral data: An approach based on simultaneously unmixing similar pixels with jointly sparse spectral mixture analysis”, Remote Sensing of Environment,vol. 196, no. 7, pp. 324-342, Jul. 2017. [2] F.Chen, P. Zhao, T. Tang, and Y. Zhou, “Fast low-rank decomposition model-based hyperspectral image classification method”, IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 2, pp. 169-173, Feb.2017. [3] F.Chen, K. Wang, and T. Tang, “Spectral unmixing using a sparse multiple-endmember spectral mixture model,” IEEE Transactions on Geoscience and Remote Sensing, vol.54, no. 10, pp. 5846-5861, Oct. 2016. [4] F.Chen, T. Tang, and K. Wang, “Low-rank decomposition model for adaptive identification of similar neighboring pixels in hyperspectral images,” IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 2, pp.172-176, Feb. 2016. [5] Fe.Chen, T. Tang, and K. Wang, “Sparse smoothing preprocessing of hyperspectral images for improved classification performance,” Remote Sensing Letters, vol.6, no. 4, pp. 276-285, Apr. 2015. [6] F.Chen, K. Wang, and T. Tang, “Hyperspectral image unmixing using a sparse Bayesian model,” Remote Sensing Letters, vol. 5, no. 7, pp. 642–651, Jul. 2014. [7] X.Liu, F. Chen*, “Automatic segmentation of 3-d brain mr images by using global tissue spatial structure,” IEEE Transactions on Applied Superconductivity, vol. 24, no.5, pp. 1-5, Oct. 2014. [8] F.Chen, Y. Zhang, “Sparse hyperspectral unmixing based on constrained ℓp−ℓ2 optimization”, IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 5, pp. 1142-1146,Sep. 2013. [9] F.Chen, J. Ma, J. C-W. Chan, and D. Yan, “Quantitative measurement for the homogeneity and contrast of the step edges in satellite image point spread function estimation,” International Journal of Remote Sensing, vol. 32, no. 22,pp. 7179-7201, Nov. 2011. [10] F.Chen, X. Huang, and W. Chen, “Texture-preserving image deblurring,” IEEE Signal Processing Letters, vol. 17, no. 12, pp. 1018-1021, Dec. 2010. [11] F.Chen, and J. Ma, “An empirical identification method of gaussian blur parameter for image deblurring,” IEEE Transactions on Signal Processing, vol. 57, no. 7,pp. 2467-2478, July 2009.