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Non-Negative and Non-Local Tensor Dictionary Learning Based Hyperspectral Image Super-Resolution
发布时间: 2018-06-24     22:11   【返回上一页】 发布人:郭卫红


 

北京师范大学数学科学学院

 

周五公众报告

 

 

报告题目:Non-Negative and Non-Local Tensor Dictionary Learning Based Hyperspectral Image Super-Resolution

 

报告人:Weihong Guo (郭卫红), Case Western Reserve University, USA

 

时间地点:6月29日下午15:00-16:00后主楼1124 

 

邀请人: 刘君

 

报告摘要:Hyperspectral images provide rich spectral information that could be used in industry, airborne and remote sensing etc. Hyperspectral sensors achieve high resolution along spectral direction with the price of very low spatial resolution.  We provide a hypersepctral image (HIS) super resolution algorithm to increase its spatial resolution by fusing it with a multispectral image (MSI) which is usually available simultaneously during the data collection. Multispectral images have less spectral bands but higher spatial resolution compared with the hyperspectral counter part.  We aim at obtaining a high spatial resolution hyperspectral image. We propose a novel non-negative tensor dictionary learning based HSI super-resolution model using non-local spatial similarity and group-block-sparsity. The computation is done on clusters obtained by tensor cube classification. Numerical experiments demonstrate that the proposed model outperforms many state-of-the-art HSI super-resolution methods. The results are based on collaboration with graduate student Wei Wan and Professors Jun Liu and Haiyang Huang from Beijing Normal University, China.

 

报告人简介:Weihong Guo is an  Associate Professor in Applied Mathematics at Case Western Reserve University, USA. She received the Ph.D. degree in Applied Math from University of Florida (USA) in 2007.  She also received a Master’s degree in Statistics from the same university the same year. Her research interests include image reconstruction and image processing such as image super-resolution, image segmentation, image registration and their applications in medicine, biology, remote sensing, satellite imaging etc. Prof. Guo is an associate editor of the international journal Inverse Problems and Imaging since 2012. She also served as an editor for International Journal of Biomedical Imaging. She has published more than 30 papers in various well-known international journals including SIAM J. Imaging Sciences, Inverse Problems and Imaging, Information Sciences, Journal of Computational and Applied Mathematics, IEEE Transactions on Image Processing, EEE Transactions on Circuits and Systems for Video Technology, Magnetic Resonance Imaging and Magnetic Resonance in Medicine. Prof. Guo has also referred papers for more than 20 international journals and conferences. 

 

 

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