The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images
Abstract
We propose an unsupervised deep convolutional coupling network for change detection based on two heterogeneous images acquired by optical sensors and radars on different dates. Most existing change detection methods are based on homogeneous images. Due to the complementary properties of optical and radar sensors, there is an increasing interest in change detection based on heterogeneous images. The proposed network is symmetric with each side consisting of one convolutional layer and several coupling layers. The two input images connected with the two sides of the network, respectively, are transformed into a feature space where their feature representations become more consistent. In this feature space, the different map is calculated, which then leads to the ultimate detection map by applying a thresholding algorithm. The network parameters are learned by optimizing a coupling function. The learning process is unsupervised, which is different from most existing change detection methods based on heterogeneous images. Experimental results on both homogenous and heterogeneous images demonstrate the promising performance of the proposed network compared with several existing approaches.
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Chen, H., & Shi, Z. (2020) · Remote Sensing · doi:10.3390/rs12101662 · Cited by 1,903
A deep translation (GAN) based change detection network for optical and SAR remote sensing images
Li, X., Du, Z., Huang, Y., & Tan, Z. (2021) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2021.07.007 · Cited by 396
Li, X., Zhang, G., Cui, H., Hou, S., Wang, S., Li, X., Chen, Y., Li, Z., & Zhang, L. (2022) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2021.102638 · Cited by 303
A deep learning framework for remote sensing image registration
Wang, S., Quan, D., Liang, X., Ning, M., Guo, Y., & Jiao, L. (2018) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2017.12.012 · Cited by 292
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Metadata
- Authors
- Liu, J., Gong, M., Qin, K., & Zhang, P.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2018-03
- Volume
- 29
- Issue
- 3
- Pages
- 545-559
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W2564140372
- Cited by
- 522
- References
- 39
- FWCI
- 26.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, J., Gong, M., Qin, K., & Zhang, P. (2018). A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2016.2636227
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