Discover @polwork Open Source projects

@polwork

polwork

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131
Global Rank 170,475 (Top 6 %)
Followers 84
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Registered over 7 years ago
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MATLAB
84.6 %

Python
7.7 %

Batchfile 7.7 %
Location 🇺🇸 United States
Country Total Rank 43,573
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MATLAB
202

Batchfile 466

Hyperspectral-Image-Denoising-via-Sparse-Representation-and-Low-Rank-Constraint

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.

An-Iterative-Image-Dehazing-Method-with-Polarization

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"

Learning-and-Transferring-Deep-Joint-Spectral-Spatial-Features-for-Hyperspectral-Classification

code for paper "Learning and Transferring Deep Joint Spectral-Spatial Features for Hyperspectral Classification"

LDDRS

This is a LWIR DoFP Dataset of Road Scene (LDDRS)

Demosaicking-DoFP-images-using-Newton-polynomial-interpolation-and-polarization-difference-model

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)

U-2Pnet

PCDP

Code for "Polarization image demosaicking using polarization channel difference prior"

Mosaic-Convolution-Attention-Network-for-Demosaicing-Multispectral-Filter-Array-Images

This repository is the official PyTorch implementation of "Mosaic Convolution-Attention Network for Demosaicing Multispectral Filter Array Images" (TCI 2021)

PDS

No-Reference-Hyperspectral-Image-Quality-Assessment-via-Quality-Sensitive-Features-Learning

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."

LRTC-DM

Mixed Norm Regularized Models for Low-Rank Tensor Completion

Hyperspectral-and-Multispectral-fusion-via-Two-branch-CNN

TMSL

Band-Subset-Based-Clustering-Fusion-for-Hyperspectral-Imagery-Classification

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 )"

Unsupervised-Spectral-Demosaicing

TGI

The code for Transductive Gradient Injection for Improved Hyperspectral Image Denoising

APMR

HSI-CSR

Nonlocal Tensor Sparse Representation and Low-Rank Regularization for Hyperspectral Image Compressive Sensing Reconstruction

HOMG

Histograms of oriented mosaic gradients for snapshot spectral image description