An Improvement Technique Based on Structural Similarity Thresholding for Digital Watermarking

Digital watermarking is extensively used in ownership authentication and copyright protection. In this paper, we propose an efficient thresholding scheme to improve the watermark embedding procedure in an image. For the proposed algorithm, watermark casting is performed separately in each block of an image, and embedding in each block continues until a certain structural similarity threshold is reached. Numerical evaluations demonstrate that our scheme improves the imperceptibility of the watermark when the capacity remains fixed, and at the same time, robustness against attacks is assured. The proposed method is applicable to most image watermarking algorithms. We verify this issue on watermarking schemes in discrete cosine transform (DCT), wavelet, and spatial domain. 1. Introduction The rapid growth of the Internet and multimedia technologies has revealed the need for the copyright protection and the proof of the ownership of digital documents [1]. In particular, with images widely available on the Internet, digital watermarking is a common way of identifying images and protecting them from unauthorized usage in online advertisements. In this regard, the most important characteristic of watermark casting is its imperceptibility, where a certain degree of the statistical invisibility of the embedded watermark is required. In addition, in most watermarking techniques, it is desirable to embed messages with appropriate length so that the accurate extraction is assured, and at the same time, the embedded watermark should be perceptually invisible and robust to common signal processing and intentional attacks. Thus, there exists a trade-off between the imperceptibility, capacity, and robustness of the watermarking methods [2]. Broadly, watermarking techniques are divided into two categories: (i) spatial domain watermarking and (ii) transform domain watermarking. Spatial domain watermarking approaches, where the mark is directly embedded into each pixel of the host image, benefit from the advantages of a low degree of complexity and delay [3–5]. In addition, the temporal/spatial localization of the watermark in the spatial domain watermarking schemes is automatically achieved. This permits a better characterization of the distortion introduced by the watermark and reduces the annoying effects. In transform domain watermarking techniques, however, the watermark is inserted into the coefficients of a digital transform of the host asset [6, 7], for instance, Barni’s work [6] on watermarking using the discrete cosine transform (DCT) and the discrete Fourier