polwork Goto Github PK
Type: User
Location: The Laboratory of Multispectral and Polarimetric Intelligent Sensing
Type: User
Location: The Laboratory of Multispectral and Polarimetric Intelligent Sensing
It 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"
It is the code for paper "Yong-Qiang Zhao ; Lei Zhang ; Seong G. Kong. Band Subset Based Clustering Fusion for Hyperspectral Imagery Classification, IEEE Transactions on Geoscience and Remote Sensing ( Volume: 49, Issue: 2, Feb. 2011 )"
This 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, "Demosaicking DoFP images using Newton's polynomial interpolation and polarization difference model," Opt. Express 27, 1376-1391 (2019)
Histograms of oriented mosaic gradients for snapshot spectral image description
Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction
Zhao 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.
This is a LWIR DoFP Dataset of Road Scene (LDDRS)
code for paper "Learning and Transferring Deep Joint Spectral-Spatial Features for Hyperspectral Classification"
Mixed Norm Regularized Models for Low-Rank Tensor Completion
This repository is the official PyTorch implementation of "Mosaic Convolution-Attention Network for Demosaicing Multispectral Filter Array Images" (TCI 2021)
code for paper "Yang, J., Zhao, Y., Yi, C., & Chan, J. C. W. (2017). No-Reference Hyperspectral Image Quality Assessment via Quality-Sensitive Features Learning. Remote Sensing, 9(4), 305."
Code for "Polarization image demosaicking using polarization channel difference prior"
The code for Transductive Gradient Injection for Improved Hyperspectral Image Denoising
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