A remote sensing image change detection method incorporating variable convolution and attention mechanism

Yunfei Feng; Jingwen Li; Yanling Lu

doi:10.1117/12.2684240

1 August 2023 A remote sensing image change detection method incorporating variable convolution and attention mechanism

Yunfei Feng, Jingwen Li, Yanling Lu

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127540U (2023) https://doi.org/10.1117/12.2684240
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

In order to solve the problem that the existing remote sensing image change detection methods based on deep learning mostly focus on designing complex convolutional neural network models to enhance the detection capability, ignoring the counteracting elimination of background interference information of image features and the attention and characterization of target information of image features in the detection process, a VCA-Net remote sensing image change detection method incorporating variable convolution and attention mechanism is proposed based on the U-Net model, which introduces deformable convolution and attention mechanism modules in the encoding and jumping stages of the model, respectively, to adaptively acquire the feature information of the before and after changes of remote sensing images, filter and suppress the background noise interference in the detection process, and enhance the learning and characterization ability of the network model on the key feature information of the ground feature.In the experiments conducted on LEVIR-CD and CDD datasets, VCA-Net obtained 91.31% and 94.12% accuracy results, respectively, and the experimental comparison and analysis with existing model methods showed that the method has better accuracy and stability in remote sensing image building change detection.

Citation Download Citation

Yunfei Feng, Jingwen Li, and Yanling Lu "A remote sensing image change detection method incorporating variable convolution and attention mechanism", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127540U (1 August 2023); https://doi.org/10.1117/12.2684240

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KEYWORDS

Data modeling

Remote sensing

Convolution

Deformation

Image enhancement

Image processing

Performance modeling

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