Imperial College London

DrPingfanSong

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Research Associate
 
 
 
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Contact

 

p.song

 
 
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Location

 

805Electrical EngineeringSouth Kensington Campus

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Summary

 

Summary

Pingfan Song is a postdoctoral research associate in the Department of Electrical and Electronic Engineering at Imperial College Londonwhere he works with Prof. Pier Luigi Dragotti in the Communications and Signal Processing group since July 2018. He received the Ph.D. degree at University College London (UCL) in 2018 in UK, the Master and Bachelor degree both at Harbin Institute of Technology in 2014 and 2012, respectively, in China. His research interests include signal/image processing, machine learning, sparse modeling, sampling theory with applications to light-field microscopy, MRI imaging, multi-modal image super-resolution, denoising, etc.


Email, Google Scholar, Research Gate .

Selected Publications

Journal Articles

Song P, Verinaz Jadan H, Howe C, et al., 2020, 3D localization for light-field microscopy via convolutional sparse coding on epipolar images, Ieee Transactions on Computational Imaging, Vol:6, ISSN:2333-9403, Pages:1017-1032

Song P, Deng X, Mota JFC, et al., 2020, Multimodal image super-resolution via joint sparse representations induced by coupled dictionaries, Ieee Transactions on Computational Imaging, Vol:6, ISSN:2333-9403, Pages:57-72

Song P, Eldar YC, Mazor G, et al., 2019, HYDRA: Hybrid deep magnetic resonance fingerprinting., Med Phys, Vol:46, Pages:4951-4969

Song P, Weizman L, Mota JFC, et al., 2019, Coupled dictionary learning for multi-contrast MRI reconstruction, IEEE Transactions on Medical Imaging, Vol:39, ISSN:0278-0062, Pages:621-633

Deng X, Song P, Rodrigues MRD, et al., 2019, RADAR: robust algorithm for depth image super resolution based on FRI theory and multimodal dictionary learning, IEEE Transactions on Circuits and Systems for Video Technology, ISSN:1051-8215, Pages:1-1

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