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[ISPRS P&RS 2025] Rules-Induced Energy Model (RIEM) for Multimodal Change Detection

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RIEM

Detecting Changes without Comparing Images: Rules Induced Change Detection in Heterogeneous Remote Sensing Images

Related Datasets and supporting algorithms

#2-TexasALI、#8-TexasL8 are download from Professor Michele Volpi's webpage at https://zenodo.org/records/8046719.

#3-Img7、#4-Img17、#7-Img5 are download from Professor Max Mignotte's webpage (http://www-labs.iro.umontreal.ca/~mignotte/).

#5-California is download from Dr. Luigi Tommaso Luppino's webpage (https://sites.google.com/view/luppino/data).

The Gaussian Mixture Model based superpixel segmentation is download from Dr. Ban Zhihua's webpage at https://github.com/ahban/GMMSP-superpixel.

LSA energy minimization algorithm is download from https://vision.cs.uwaterloo.ca/code/.

If you use these resources, please cite their relevant papers.

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Citation

If you use this code for your research, please cite our paper. Thank you!

@article{SUN2025241,
title = {Detecting Changes without Comparing Images: Rules Induced Change Detection in Heterogeneous Remote Sensing Images},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
volume = {230},
pages = {},
year = {2025},
issn = {0924-2716},
doi = {https://doi.org/10.1016/j.isprsjprs.2025.09.009},
author = {Yuli Sun and Lin Lei and Zhang Li and Gangyao Kuang and Qifeng Yu} }

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Running

Unzip the Zip files (GMMSP and LSA) and run the RIEM demo file (tested in Matlab 2016a)!

RIEM contains two methods, RIEM-O and RIEM-L, which you can choose according to your needs.

If you have any queries, please do not hesitate to contact me (sunyuli@mail.ustc.edu.cn).

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