- The Laboratory of Multispectral and Polarimetric Intelligent Sensing
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Hyperspectral-Image-Denoising-via-Sparse-Representation-and-Low-Rank-Constraint
Hyperspectral-Image-Denoising-via-Sparse-Representation-and-Low-Rank-Constraint PublicZhao Y Q, Yang J. Hyperspectral image denoising via sparse representation and low-rank constraint[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(1): 296-308.
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An-Iterative-Image-Dehazing-Method-with-Polarization
An-Iterative-Image-Dehazing-Method-with-Polarization PublicIt is the code for paper "Yongqiang Zhao, Linghao Shen, Qunnie Peng, Jonathan Cheung-Wai Chan, Seong G. Kong. An Iterative Image Dehazing Method with Polarization, IEEE Transactions on Multimedia"
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Learning-and-Transferring-Deep-Joint-Spectral-Spatial-Features-for-Hyperspectral-Classification
Learning-and-Transferring-Deep-Joint-Spectral-Spatial-Features-for-Hyperspectral-Classification Publiccode for paper "Learning and Transferring Deep Joint Spectral-Spatial Features for Hyperspectral Classification"
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Demosaicking-DoFP-images-using-Newton-polynomial-interpolation-and-polarization-difference-model
Demosaicking-DoFP-images-using-Newton-polynomial-interpolation-and-polarization-difference-model PublicThis is the MATLAB implementation of the Newton's polynomial interpolation of the DoFP images demosaicking described in the following paper: Ning Li, Yongqiang Zhao, Quan Pan, and Seong G. Kong, "D…
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