This paper presented a grayscale watermarking algorithm combining texture complexity and bi-dimensional empirical mode decomposition (BEMD). Firstly, the watermark image after Arnold transform was decomposed by BEMD to obtain the intrinsic modal function (IMF) and the residual information of different scales. Then, the texture complexity of the host image after segmentation was calculated, and the region of high texture complexity was selected as the embedding location. In order to better fuse the IMF of the watermark image with the host image, BEMD decomposition was performed on the host image under the same sieving conditions as those for the watermark image. Finally, the watermark information was repeatedly embedded into the pre-selected location of the host image, and then the image embedded with watermarks was reconstructed by the IMF and the residual. Watermark extraction was the inverse process of watermark embedding. The experiments on host images at different texture levels revealed that the peak signal-to-noise ratios of images embedded with watermarks were all above 40 dB, and the normalized coefficients values of watermark extraction all exceeded 0.95 in the face of eight common attacks. Compared with the existing algorithms, the proposed algorithm performs well in large scale shearing, noise attack, image filtering, and JPEG compression attack, superior to the algorithms under comparison.

"> bi-dimensional empirical mode decomposition, grayscale watermarking, texture complexity, copyright protection, Arnold transform