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Change Detection of Open-Pit Mine Based on Siamese Multiscale Network | IEEE Journals & Magazine | IEEE Xplore

Change Detection of Open-Pit Mine Based on Siamese Multiscale Network


Abstract:

Automatic change detection of open-pit mines from high-resolution remote sensing images is of great significance for the mining and management of mineral resources. For t...Show More

Abstract:

Automatic change detection of open-pit mines from high-resolution remote sensing images is of great significance for the mining and management of mineral resources. For this purpose, we propose a siamese multiscale change detection network (SMCDNet) with an encoder-decoder structure. First, the multiscale low-level and high-level features of the bi-temporal image are extracted by a siamese network. Second, a multilevel feature absolute difference (MFAD) module is proposed to fuse the low-level and high-level change features. Finally, convolution and up-sampling operations are used to recover the details of the changed areas. A self-made open-pit mine change detection (OMCD) dataset is employed to conduct experiments. Experimental results have demonstrated that the proposed method is superior to the comparison networks. F1 - score of 88.13% is achieved by the proposed SMCDNet. The OMCD dataset produced in this study has been made public at the following link: https://figshare.com/s/ae4e8c808b67543d41e9.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 20)
Article Sequence Number: 2500105
Date of Publication: 28 December 2022

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