Enhancing Change Detection Robustness: A Whitening Transformation Approach

The vast amount of remote sensing data has been instrumental in supporting research on change detection algorithms based on deep learning.However, factors such as geographical changes and variations in sensor parameters can result in significant style differences between remote sensing images at different time points, leading to a decline in model performance.To address this issue, this paper proposes a change detection algorithm based on whitening feature extraction, aiming to alleviate distribution differences by decoupling domain-invariant discriminative features from domain-specific style features.The effectiveness of the proposed method is demonstrated through transfer experiments from the SVCD dataset to the SZADA dataset and from the SYSU dataset to the SZADA dataset.