Image Watermarking Algorithm Based on Geometric Correction and Non-subsampled Shearlet Transform

To solve the defects in current image watermarking technology, including poor robustness and the high false-detection rate induced by the difficulty of resisting geometric distortion, we propose an image watermarking algorithm based on geometric correction and the non-subsample Shearlet transform. First, we use Cat mapping to permute the watermark information image. Then, we use a non-subsampled Shearlet transform to embed the watermarking information in the permutated image, output the low-pass subband and a series of high-pass subbands, and segment the low-pass subband into small blocks of the same size. To embed the information into a carrier image, we construct a watermark-embedding mechanism by modifying the non-subsampling Shearlet transform coefficients of the low-pass subband. Then, to fully describe the robust features, we construct geometric-distortion image-training samples and calculate the modulus of the polar harmonic transform coefficients of the watermark image based on the polar harmonic transformation. Then, we introduce a fuzzy support vector machine to predict the geometric-distortion parameter for correcting the watermark image. Lastly, we process the corrected watermark image using a non-sub-sampled Shearlet transform to obtain the low-pass subband, and design a watermark detection method for restoring the watermark information. The experimental results show that this algorithm has higher perceptual ability and better robustness than existing image watermarking algorithms, and for all kinds of geometric attacks, the correlation coefficients between the recovered and original watermarks are higher than 0.95.