Host Feasibility Investigation to Improve Robustness in Hybrid DWT+SVD Based Image Watermarking Schemes

Abstract

Today, we face different approaches to enhance the robustness of image watermarking schemes. Some of them can be implemented, but others in spite of spending money, energy, and time for programming purpose would fail because of not having a strong feasibility study plan before implementation. In this paper, we try to show a rational feasibility study before implementation of an image watermarking scheme. We develop our feasibility study by proposing three types of theoretical, mathematical, and experimental deductions. Based on the theoretical deduction, it is concluded that the “S” coefficients in the second level of Singular Value Decomposition (SVD) offer high robustness to embed watermarks. To prove this, a mathematical deduction composed of two parts is presented and the same results were achieved. Finally, for experimental deduction, 60 different host images in both normal and medical images from various sizes of 256⁎256 to 1024⁎1024 were imposed to 9 common geometric and signal processing attacks and the resistances of “S” coefficients against the attacks in the first and second levels of SVD were compared. Experimental result shows significant enhancement in stability and robustness of the “S” coefficients in the second level of SVD in comparison to the first level. Consequently all theoretical, mathematical, and experimental deductions confirmed domination of the “S” coefficients in the second level of SVD than the first level. In this paper, we do not show any specific implementation for the watermarking scheme. Instead, we investigate the potential performance gains from the singular values (S), of the second level of SVD and Discrete Wavelet Transform (DWT), and prove their superiority in comparison to conventional SVD+DWT watermarking schemes.

Analysis and effectiveness of deeper levels of SVD on performance of hybrid DWT and SVD watermarking

“…We denote "SVD2" as the use of a second level of SVD, whereas "SVD1" refers to a single level of the SVD. The feasibility of implementing SVD2 is tested and verified in [29] , and the value of n for image blocking is selected as 16, whereas the reason of this selection is provided in [11]. Finally, a pre-processing step is performed on the watermark image in both schemes in order to repeat the watermark redundantly, so that the sizes of both watermark and host images become equal.…”

“…Amongst these techniques an optimum resistance against attacks has been achieved by hybrid DWT and SVD techniques [16,28,29,34,48]. Hence, we focus on the combination of these two techniques in the literature review.…”

Boosting image watermarking authenticity spreading secrecy from counting‐based secret‐sharing

“…In fact, the Hide-XOR scheme guaranteed privacy of hiding bits reliant on This Hide-XOR stimulated our work considering the size of CBSS shadow share TK combined to image size for providing unpredictable spreading (based on data) to increase watermarking ambiguity security. Similarly, Hide-Octagon is dividing the image, which encourages us to develop the watermarking bits spreading over the complete image, as found in principle comparable to watermarking work in [43].…”

“…In this work of fair spreading hiding process, the watermarking privacy is put in diverse LSB positions auto dependent on sizes of image and confidential CBSS TK. Accordingly, the watermarking spreading locations change smartly similar in principle to the matrices spreading of secrets within watermarking research [43]. Linking our work to CBSS, the secret shadow shares are based on secret data, which gives the required security [35].…”

“…Linking our work to CBSS, the secret shadow shares are based on secret data, which gives the required security [35]. In general, our method is a preferred boosting secrecy as secret watermarking data is small compared to the huge size of images remarking uncertainty spreading privacy all over the images [43].…”