396-a-novel-band-selection-and-spatial-noise-reduction-method-for-hyperspectral-image-classification

https://github.com/szu-advtech-2023/396-a-novel-band-selection-and-spatial-noise-reduction-method-for-hyperspectral-image-classification

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  • Host: GitHub
  • Owner: SZU-AdvTech-2023
  • Language: MATLAB
  • Default Branch: main
  • Size: 2.33 MB
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Citation

https://github.com/SZU-AdvTech-2023/396-A-Novel-Band-Selection-and-Spatial-Noise-Reduction-Method-for-Hyperspectral-Image-Classification/blob/main/

# Readme 
This repository contains code developed for the Computer Frontiers Technology course assignment at Shenzhen University. The assignment was completed by student Zhang Yuze, with student ID 2350278003. The code is a reproduction of the research paper titled "A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification."

## Description

The main file for executing the code is `main.m`. The code is specifically designed for execution in the MATLAB environment.

## Reproduction of Research Paper

This code serves as a reproduction of the methods presented in the research paper "A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification."

## Usage

1. **MATLAB Environment:**
   - Ensure that you have MATLAB installed (version R2019a or later).

2. **Execution:**
   - Run the `main.m` script in the MATLAB environment.

## References

If you use this code, please kindly cite the paper: @ARTICLE{9817391,
author={Fu, Hang and Zhang, Aizhu and Sun, Genyun and Ren, Jinchang and Jia, Xiuping and Pan, Zhaojie and Ma, Hongzhang},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification},
year={2022},
volume={60},
pages={1-13},
doi={10.1109/TGRS.2022.3189015}}

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  • Name: SZU-AdvTech-2023
  • Login: SZU-AdvTech-2023
  • Kind: organization

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