A HybridWavelet-Shearlet Approach to Robust Digital ImageWatermarking (Informatica, 2017)
Watermarking systems are one of the most important techniques used to protect digital content. The main challenge facing most of these techniques is to hide and recover the message without losing much of information when a specific attack occurs. This paper proposes a novel method with a stable outcome under any type of attack. The proposed method is a hybrid approach of three different transforms, discrete wavelet transform (DWT), discrete shearlet transform (DST) and Arnold transform. We call this new hybrid method SWA (shearlet, wavelet, and Arnold). Initially, DWT applied to the cover image to get four sub-bands, we selected the HL (High-Low) sub band of DWT, since HL sub-band contains vertical features of the host image, where these features help maintain the embedded image with more stability. Next, we apply the DST with HL sub-band, at the same time applying Arnold transform to the message image. Finally, the output that obtained from Arnold transform will be stored within the Shearlet output. To evaluate the proposed method we used six performance evaluation measures, namely, peak signal to noise ratio (PSNR), mean squared error (MSE), root mean squared error (RMSE), signal to noise ratio (SNR), mean absolute error (MAE) and structural similarity (SSIM). We apply seven different types of attacks on test images, as well as apply combined multi-attacks on the same image. Extensive experimental results are undertaken to highlight the advantage of our approach with other transform based watermarking methods from the literature. Quantitative results indicate that the proposed SWA method performs significantly better than other transform based state-of-the-art watermarking approaches.