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Due to the unlawful manipulation and image processing attacks, the copyright protection of digital image is paid more and more attention. This paper proposes a digital image watermarking technique to protect image authentication based on discrete wavelet transform (DWT), entropy and neural network. Firstly, the DWT is used to divide the host image and the watermark image into frequency sub-bands. Then, the entropy of each frequency sub-band is calculated to find the maximum entropy sub-band in order to embed the highest entropy sub-band of the watermark image into the highest entropy sub-band of the host image. Finally, the neural network is used for determining the relationship between the pixel values of the host image and the watermarked image which is used later in the watermark extraction process. Moreover, a moving average filter is used prior to the extraction process for reducing the image processing attacks. Performance of the proposed method is tested against different image processing attacks (such as Filtering, Gaussian noise, Rotation, and Cropping). Experimental results demonstrate that this proposed method not only has the superior robustness and imperceptibility but also has improved the anti-attack capability in comparison with recent works in this field.

An imperceptible & robust digital image watermarking scheme based on DWT, entropy and neural network