RSIRW-DCF: Dual-Channel Feature-Guided Robust Watermarking Against Dual Attacks for Remote Sensing Image

Remote sensing image (RSI) involves sensitive information such as military and national. If these data are attacked or stolen during transmission, intellectual property rights could be violated. In some cases, national security might also be jeopardized. Therefore, protecting the copyright of RSI data is essential. However, the existing digital watermarking schemes do not effectively defend RSI against the screen-shooting attack on top of other geometric and non-geometric attacks, i.e., dual attacks. To defend against the threats posed by dual attacks, this paper proposes a dual-channel feature-guided robust watermarking scheme against dual attacks for RSI, called RSIRW-DCF. RSI contains rich texture information. However, it is vulnerable to screen-shooting attack during transmission. So, we employ texture and scale-invariant feature transform (SIFT) features as dual-channel feature to guide watermark embedding in RSI. Specifically, we extract texture complex points from the grayscale covariance matrix and keypoints from SIFT. The intersection of these points determines where the watermark will be embedded. The watermarked RSI generated by this scheme can withstand dual attacks during transmission, protecting the copyright of RSI data. Experiments exhibit that after dual attacks, the bit error rate (BER) of our method is significantly lower than that of the traditional robust watermarking. It is also, on average, 1.67% lower than the BER of the screen-shooting resilient watermarking.

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Publication Details

Journal
IEEE Transactions on Consumer Electronics
Published
2025-08-14
DOI
https://doi.org/10.1109/tce.2025.3598821
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

RSIRW-DCF: Dual-Channel Feature-Guided Robust Watermarking Against Dual Attacks for Remote Sensing Image

Jiameng Hu, Wenying Wen, Xiangli Xiao, Baolin Qiu et al.
IEEE Transactions on Consumer Electronics
Advanced Steganography and Watermarking Techniques
article

RSIRW-DCF: Dual-Channel Feature-Guided Robust Watermarking Against Dual Attacks for Remote Sensing Image

Jiameng Hu, Wenying Wen, Xiangli Xiao, Baolin Qiu, Yushu Zhang
article en

Abstract

Remote sensing image (RSI) involves sensitive information such as military and national. If these data are attacked or stolen during transmission, intellectual property rights could be violated. In some cases, national security might also be jeopardized. Therefore, protecting the copyright of RSI data is essential. However, the existing digital watermarking schemes do not effectively defend RSI against the screen-shooting attack on top of other geometric and non-geometric attacks, i.e., dual attacks. To defend against the threats posed by dual attacks, this paper proposes a dual-channel feature-guided robust watermarking scheme against dual attacks for RSI, called RSIRW-DCF. RSI contains rich texture information. However, it is vulnerable to screen-shooting attack during transmission. So, we employ texture and scale-invariant feature transform (SIFT) features as dual-channel feature to guide watermark embedding in RSI. Specifically, we extract texture complex points from the grayscale covariance matrix and keypoints from SIFT. The intersection of these points determines where the watermark will be embedded. The watermarked RSI generated by this scheme can withstand dual attacks during transmission, protecting the copyright of RSI data. Experiments exhibit that after dual attacks, the bit error rate (BER) of our method is significantly lower than that of the traditional robust watermarking. It is also, on average, 1.67% lower than the BER of the screen-shooting resilient watermarking.

IEEE Transactions on Consumer ElectronicsVol. 71(4)
Jiangxi University of Finance and Economics (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 79%
Advanced Steganography and Watermarking Techniques
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RSIRW-DCF: Dual-Channel Feature-Guided Robust Watermarking Against Dual Attacks for Remote Sensing Image — Jiameng Hu, Wenying Wen, et al. · IEEE Transactions on Consumer Electronics (2025) | TGRS Research Map | TGRS