Hyperspectral-Change-Detection-Based-on-Multiple-Morphological-Profiles

Fig.1. Framework of proposed dual-pipeline hyperspectral change detection framework using multiple morphological profiles

Prerequisites

MATLAB R2018a
C++ Language (Visual Studio 2017 and OpenCV 3.4.1)

Source

Paper Download:

• https://ieeexplore.ieee.org/document/9469924

Hermiston dataset:

• Google Drive
• Baidu Disk, Extraction code: ox7g

Statement:

• The morphological feature extraction in max-tree/min-tree was conducted in VISUAL STUDIO 2017 using C++ language, which provied by prof. Lu Li. Due to copyright, this part of the codes cannot be shared. However, in order to reproduce the experimental results, we have encapsulated it into an EXE program, and now it has been released.
  
• C++ Matree/Mintree codes
  

Instructions:

Installation and Configuration Instructions:

• English Blog: A Detailed Installation and Configuration Processing of OpenCV 3.4.1 and Visual Studio 2017
• Chinese CSDN: OpenCV3.4.1和VS2017配置过程详解

Citation

If these codes and dataset are helpful for you, please cite this paper:

BibTex Format:

@ARTICLE{9469924,
author={Hou, Zengfu and Li, Wei and Li, Lu and Tao, Ran and Du, Qian},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Hyperspectral Change Detection Based on Multiple Morphological Profiles},
year={2021},
volume={},
number={},
pages={1-12},
doi={10.1109/TGRS.2021.3090802}}

Plain Text Format:

Z. Hou, W. Li, L. Li, R. Tao and Q. Du, "Hyperspectral Change Detection Based on Multiple Morphological Profiles," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2021.3090802.

Other Related Papers

[1] Zengfu Hou, Wei Li, Ran Tao, and Qian Du. Three-Order Tucker Decomposition and Reconstruction Detector for Unsupervised Hyperspectral Change Detection [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, doi: 10.1109/JSTARS.2021.3088438]

[2] Zengfu Hou, Wei Li, and Qian Du. A PATCH TENSOR-BASED CHANGE DETECTION FOR HYPERSPECTRAL IMAGES[C]. International Geoscience and Remote Sensing Symposium, 2021, inprint.

My Website

• Github Website
• Chinese CSDN