Robust image watermarking method and system based on deep learning and attention network
An image watermarking and deep learning technology, applied in image data processing, image data processing, biological neural network models, etc., can solve the problems of imperceptibility and unsatisfactory robustness, and achieve resistance to various attacks and imperceptibility The effect of sex and robustness
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Embodiment 1
[0046] Embodiment 1 of the present invention introduces a robust image watermarking method based on deep learning and attention network.
[0047] Such as figure 1 A robust image watermarking method based on deep learning and attention network is shown, including three stages: watermark embedding stage, simulated attack stage and watermark extraction stage, specifically including the following steps:
[0048] Step S01: Perform data reorganization on the original image data, the input size is The original image of , restructured as The tensor, in this embodiment due to consideration of the follow-up DCT transform, h = M / 8, w = N / 8, c =64.
[0049] Step S02: build as figure 2 The attention model shown, the size generated by step S01 is The raw image tensor input figure 2 In the network, the attention weights are inferred sequentially along the two dimensions (channel and space), multiplied by the original tensor and adaptively adjusted to generate attention fe...
Embodiment 2
[0094] Embodiment 2 of the present invention introduces a robust image watermarking system based on deep learning and attention network.
[0095] Such as Figure 6 A robust image watermarking system based on deep learning and attention networks is shown, including:
[0096] The watermark embedding module is configured to obtain the original image tensor, obtain the attention image tensor according to the obtained original image tensor and the attention model, and generate the watermarked image tensor based on the obtained attention image tensor and the watermark embedding model image;
[0097] The simulated attack module is configured to generate an attacked image according to the generated image containing the watermark and the constructed attack network model;
[0098] The watermark extraction model is configured to extract the image watermark according to the attacked image, the attention model and the deep learning model.
[0099] The detailed steps are the same as the ...
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