zhao yong qiang



The basic information

zhao yong qiang

School of Automation




Admission Information

Scientific Research

Research Directions:

Image processing, Computer vision, Polarization Imaging,  Hyperspectral Remote Sensing, 

Pattern Recognition, Photoelectric Detection and so on.

(1) Bionic polarization vision

Polarization vision, which could accurately obtain all kinds of information of the interested targets in scattering medium, is a new research direction in the field of machine vision. The research work is mainly on carrying out high-speed and high-resolution micro-nano grating array polarization imaging, multiband polarization joint encoding and decoding, bionic multiband polarization visual model, multiband polarization visual information analysis, bionic polarization light integrated navigation and so on.

(2) High-dimensional image reconstruction

Obtaining images with high-spatial, spectrum, and polarization resolution through post-processing is one of the important development directions of spectropolarimetric remote sensing, which also brings new challenges to the theory of traditional image reconstruction. And in this field, researches on compressed spectropolarimetric imaging combined with sparse sampling, multi-band image super-resolution reconstructions, computing spectral imaging, multi-objective joint optimization and so on have been carried out.

(3) Multi-band photoelectric detection system

Carrying out research work mainly on different directions such as target detection, tracking, recognition of visible light, infrared, multispectral and polarized image, and designing different imaging system combined with engineering practice.

Research projects


National Natural Science Foundation of China  (NSFC:61771391), “Spectropolarimetric Imaging Based on Gratting Array and Deep Learning”. 1/2018 —12/2021(principal investigator)

(2)Joint research project between National Natural Science Foundation of China and Korea National Research Foundation (NSFC-NRF: 61511140292), “The theoretical research on multi-band polarization imaging based on micro-nano filter cascaded array ”. 7 2015—6/2017 (principal investigator)

(3) National Natural Science Foundation of China (NSFC: 61371152), “The theoretical research on joint sparse sampling applied to compressed spectropolarimetric imaging”. 1/2014—12/2017 (principal investigator)

(4) National Natural Science Foundation of China (NSFC: 61071172), “Research on multi-band bionic polarized visual sensing model”. 1/2011—12/2013 (principal investigator)  

(5) National Natural Science Foundation of China (NSFC: 60602056), “Synthesis and application of imaging spectropolarimetric detected information using multi-scale analysis”. 1/2007—12/2009 (principal investigator)

Academic Achievements


[2] Yongqiang Zhao, Quan Pan,S.G.Kong, Chen Yi, Yongmei Cheng. Multi-band Optical Polarization Imaging and Application. Springer-NDIP.2015.

[1] Yongqiang Zhao, Quan Pan,Yongmei Cheng. Imaging Spectropolarimetric Remote Sensing and Application. NDIP. 2011.


[37]Jize Xue,Yongqiang Zhao and Wenzhi Liao et al. Nonlocal Low-rank Regularized Tensor Decomposition for Hyperspectral Image Denoising. Submitted.(paper,code)

[36]Jize Xue,Yongqiang Zhao and Wenzhi Liao et al. Nonconvex Tensor Rank Minimization and Its Application for Tensor Data.Submitted.(paper,code)

[35] Mohamed Reda, Yongqiang Zhao and Jonathan C-W Chan. Matching enhancement using polarization and depth information.Submitted.(paper,code)

[34] Jingxiang Yang, Yongqiang Zhao,Jonathan Cheung-Wai Chan. Hyperspectral and Multispectral Image Fusion via Deep Two-Branches Convolutional Neural Network.Submitted.(paper,code)

[33] Chen Yi,Yongqiang Zhao,J.W. Chan. Hyperspectral image super-resolution based on spatial and spectral correlation fusion. Submitted.(paper,code)

[32] Yongqiang Zhao,Shen Lin Hao, Qunnie Peng. Robust Image Dehazing With Polarization and Noise Suppression. Submitted.(paper,code)

[31]Yongqiang Zhao,Hao Jinglei, Qunnie Peng. Straylights Suppression of High-reflective Objects Based on Multiband Polarization Imaging. Submitted. (paper,code)

[30] Yongqiang Zhao,Miaomiao Wang, J.W. Chan. FOV Expansion of Bio-Inspired Multiband Polarimetric Imagers with Convolutional Neural Networks. IEEE Photonics Journal.2018. (paper,code)

[29] Xixi Ping, Yong Liu, Yongqiang Zhao et al. 3-D reconstruction of textureless and high-reflective target by polarization and binocular stereo vision. Journal of Infrared and Millimeter Waves. 2017,36(4):432-438(paper,code)

[28]Jize Xue, Yongqiang Zhao, Wenzhi Liao, and Seong G. Kong.Joint Spatial and Spectral Low-Rank Regularization for Hyperspectral Image Denoising. IEEE Trans. Geoscience and Remote Sensing.2017.(paper,code)

[27] Lin Li, Yongqiang Zhao, Jinjun Sun, et. Al. Deformable Dictionary Learning for SAR Image Change Detection. IEEE Trans. Geoscience and Remote Sensing.2017. (paper,code)

[26]Mohamed Reda, Yongqiang Zhao and Jonathan C-W Chan. Polarization guided auto-regressive model for depth recovery. IEEE Photonics Journal.2017.(paper,code)

[25] Jingxiang Yang, Yongqiang Zhao,Jonathan Cheung-Wai Chan. Learning and Transferring Deep Joint Spectral-Spatial Feature for Hyperspectral Classification.IEEE Trans. Geoscience and Remote Sensing.2017. (paper,code)

[24]Jingxiang Yang, Yongqiang Zhao, Chen Yi and Jonathan Cheung-Wai Chan. No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning. Remote Sensing.2017(paper,code)

[23] Chen Yi, Yongqiang Zhao, Jingxiang Yang, Jonathan Cheung-Wai Chan, and Seong G. Kong, Joint Hyperspectral Super-Resolution and Unmixing with Interactive Feedback. IEEE Trans. Geoscience and Remote Sensing.2017. (paper,code)

[22] Jingxiang Yang, Yongqiang Zhao, JCW Chan, SG Kong. Coupled Sparse Denoising and Unmixing with Low Rank Constraint for Hyper-spectral Image. IEEE Trans. Geoscience and Remote Sensing. 2016.(paper,code)

[21] Jinhuan Wen, James E. Fowler, Mingyi He, Yongqiang Zhao, Chengzhi Deng, and Vineetha Menon. Orthogonal Nonnegative Matrix Factorization Combining Multiple Features for Hyerspectral Image Spectral-Spatial Dimension Reduction.IEEE Trans. Geoscience and Remote Sensing. 2016.(paper,code)

[20] Yongqiang Zhao, Qunnie Peng, Chen Yi and Seong G. Kong. Multi-band Polarization Imaging. Journal of Sensors. 2016.(paper,code)

[19] Yongqiang Zhao, Jingxiang Yang. Hyperspectral Image Denoising via Sparse Representation and Low-Rank Constraint. IEEE Trans. on Geoscience and Remote Sensing, 53(1):2015.296-308.(PDF,Code)

[18] Yongqiang Zhao, Jingxiang Yang, JCW Chan. Hyperspectral Imagery Super-Resolution by Spatial–Spectral Joint Nonlocal Similarity. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-13, 2014.(PDF)

[17] S.B.Gao, Y.M. Cheng, Y.Q. Zhao et al. Data-driven quadratic correlation filter using sparse coding for infrared targets detection. Journal of Infrared and Millimeter Waves. ,2014,33(5):498-506

[16] S Gao, Y Cheng, Yongqiang Zhao. Method of visual and infrared fusion for moving object detection. Optics letters 38 (11), 1981-1983, 2013.(PDF)

[15] Yongqiang Zhao, SG Kong. Automated classification of touching or overlapping M-FISH chromosomes by region fusion and homolog pairing. Pattern Analysis and Applications 16 (1), 31-39, 2013.(PDF)

[14] S Gao, Y Cheng, Yongqiang Zhao. Unsupervised change detection of satellite images using low rank matrix completion. Optics Letters 38 (23), 5146-5149,2013. (paper)

[13] Jinhuan Wen, Yongqiang Zhao, Xingfu Zhang, Weidong Yan, Wei Lin, Local discriminant nonnegative matrix factorization feature extraction for hyperspectral image classification, International Journal of Remote Sensing, 2014, 35(13): 5073–5093.(paper)

[12] Yongqiang Zhao, Q Zhang, J Yang. High-resolution multiband polarization epithelial tissue imaging method by sparse representation and fusion. Applied Optics 51 (4), 2012:A27-A35. (paper)

[11] Yongqiang Zhao, L Zhang, SG Kong. Band-subset-based clustering and fusion for hyperspectral imagery classification. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49 (2), 747-756. (paper)

[10] Yongqiang Zhao, G Zhang, F Jie, S Gao, C Chen, Q Pan. Unsupervised Classification of Spectropolarimetric Data by Region-Based Evidence Fusion. IEEE Geoscience and Remote Sensing Letters, 2011, 755-759.(paper)

[8] Yongqiang Zhao, J Yang, Q Zhang, L Song, Y Cheng, Q Pan. Hyperspectral imagery super-resolution by sparse representation and spectral regularization. EURASIP Journal on Advances in Signal Processing, 2011 (1), 87. (paper)

[8] Yongqiang Zhao, X Wu, SG Kong, L Zhang. Joint segmentation and pairing of multispectral chromosome images. Pattern Analysis & Applications, 2011:1-10.(Data, paper)

[7 ] Y. Wu, Y.M. Cheng, Y.Q. Zhao et al. Infrared target detection using kernel Rayleigh quotient quadratic correlation filter. Journal of Infrared and Millimeter Waves. ,2011,30(2):142-148

[6] C. Chen, Y.Q. Zhao, L. Luo et al. Model and Analysis of Spectropolarimetric BRDF of Painted Target Based on GA-LM Method. Spectroscopy and Spectral Analysis. 2010: 729-734.

[5] Yongqiang Zhao, Peng Gong, Quan Pan. Object Detection by Spectropolarieteric Imagery Fusion, IEEE Transactions on Geoscience and Remote Sensing, 46(9), 2008.(paper)

[4] Yongqiang Zhao, Lei Zhang, Quan Pan. Spectropolarimetric imaging for pathological analysis of skin, Applied Optics, 48(10), 2009: D236-D246.(paper)

[3] Yongqiang Zhao, Lei Zhang, Quan Pan. Object Separation by Polarimetric and Spectral Imagery Fusion, Computer Vision and Image Understanding, 2009.(paper)

[2] S.B.Gao, Y.M. Cheng, Y.Q. Zhao et al. Detection of Buried Target Based on Multitemporal Infrared Image. Journal of Infrared and Millimeter Waves. 2009,28(1):142-148

[1] Yongqiang Zhao, Quan Pan, Hong-Cai Zhang. New Polarization Imaging Method based on Spatially Adaptive Wavelet Image Fusion, Optical Engineering,45(12), 2006: 123202 -1-6.(paper)

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