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Data Driven Camera for Snap Shot Hyperspectral Imaging Reconstruction
时间:2018-08-13 23:02    点击:   所属单位:物理与光电工程学院
讲座名称 Data Driven Camera for Snap Shot Hyperspectral Imaging Reconstruction
讲座时间 2018-08-16 14:00:00
讲座地点 北校区图书馆西裙楼三楼报告厅
讲座人 Dr. Lin Gu
讲座人介绍

Dr. Gu received the bachelor degree from Shanghai University in 2009 and his PhD degree in 2014 from the Australian National University (ANU). From 2014 to 2016, he was working in A*STAR, Singapore as a postdoctoral research fellow. He joined National Institute of Informatics in 2016 as project researcher. He is also a visiting researcher in Kyoto University, Japan. He was awarded the best student paper at International Conference on Pattern Recognition (ICPR) 2012, International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2013.

Dr Gu’s research field includes hyperspectral imaging, computational photography and medical imaging. He has published over 10 papers in top conference and journals including CVPR, ICCV, MICCAI, IEEE TIP and IEEE TMI.

讲座内容

Hyperspectral reconstruction from RGB imaging has recently achieved significant progress via sparse coding and deep learning. However, a largely ignored fact is that existing RGB cameras are tuned to mimic human trichromatic perception, thus their spectral responses are not necessarily optimal for hyperspectral reconstruction. In this paper, rather than use RGB spectral responses, we simultaneously learn optimized camera spectral response functions (to be implemented in hardware) and a mapping for spectral reconstruction by using an end-to-end network. Our core idea is that since camera spectral filters act in effect like the convolution layer, their response functions could be optimized by training standard neural networks. We propose two types of designed filters: a three-chip setup without spatial mosaicing and a single-chip setup with a Bayer-style 2x2 filter array. Numerical simulations verify the advantages of deeply learned spectral responses compared to existing RGB cameras. More interestingly, by considering physical restrictions in the design process, we are able to realize the deeply learned spectral response functions by using modern film filter production technologies, and thus construct data-inspired multispectral cameras for snapshot hyperspectral imaging.

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