Robust Image Watermarking Using QR Factorization In Wavelet Domain

A robust blind image watermarking algorithm in wavelet transform domain (WT) based on QR factorization, and quantization index modulation (QIM) technique is presented for legal protection of digital images. The host image is decomposed into wavelet subbands, and then the approximation subband is QR factorized. The secret watermark bit is embedded into the R vector in QR using QIM. The experimental results show that the proposed algorithm preserves the high perceptual quality. It also sustains against JPEG compression, and other image processing attacks. The comparison analysis demonstrates the proposed scheme has better performance in imperceptibility and robustness than the previously reported watermarking algorithms

The Effect of Wavelet Families on Watermarking

With the advance of technologies such as the Internet, Wi-Fi Internet availability and mobile access, it is becoming harder than ever to safeguard intellectual property in a digital form. Digital watermarking is a steganographic technique that is used to protect creative content. Copyrighted work can be accessed from many different computing platforms; the same image can exist on a handheld personal digital assistant, as well as a laptop and desktop server computer. For those who want to pirate, it is simple to copy, modify and redistribute digital media. Because this impacts business profits adversely, this is a highly researched field in recent years. This paper examines a technique for digital watermarking which utilizes properties of the Discrete Wavelet Transform (DWT). The digital watermarking algorithm is explained. This algorithm uses a database of 40 images that are of different types. These images, including greyscale, black and white, and color, were chosen for their diverse characteristics. Eight families of wavelets, both orthogonal and biorthogonal, are compared for their effectiveness. Three distinct watermarks are tested. Since compressing an image is a common occurrence, the images are compacted to determine the significance of such an action. Different types of noise are also added. The PSNR for each image and each wavelet family is used to measure the efficacy of the algorithm. This objective measure is also used to determine the influence of the mother wavelet. The paper asks the question: “Is the wavelet family chosen to implement the algorithm of consequence?” In summary, the results support the concept that the simpler wavelet transforms, e.g. the Haar wavelet, consistently outperform the more complex ones when using a non-colored watermark

Optimized DWT Based Digital Image Watermarking and Extraction Using RNN-LSTM

The rapid growth of Internet and the fast emergence of multi-media applications over the past decades have led to new problems such as illegal copying, digital plagiarism, distribution and use of copyrighted digital data. Watermarking digital data for copyright protection is a current need of the community. For embedding watermarks, robust algorithms in die media will resolve copyright infringements. Therefore, to enhance the robustness, optimization techniques and deep neural network concepts are utilized. In this paper, the optimized Discrete Wavelet Transform (DWT) is utilized for embedding the watermark. The optimization algorithm is a combination of Simulated Annealing (SA) and Tunicate Swarm Algorithm (TSA). After performing the embedding process, the extraction is processed by deep neural network concept of Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM). From the extraction process, the original image is obtained by this RNN-LSTM method. The experimental set up is carried out in the MATLAB platform. The performance metrics of PSNR, NC and SSIM are determined and compared with existing optimization and machine learning approaches. The results are achieved under various attacks to show the robustness of the proposed work

Embedding distortion analysis in wavelet-domain watermarking

Imperceptibility and robustness are two complementary fundamental requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility, but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often infuse distortions resulting in poor visual quality in host images. This article analyses the embedding distortion for wavelet-based watermarking schemes. We derive the relationship between distortion, measured in mean square error (MSE), and the watermark embedding modification and propose the linear proportionality between MSE and the sum of energy of the selected wavelet coefficients for watermark embedding modification. The initial proposition assumes the orthonormality of discrete wavelet transform. It is further extended for non-orthonormal wavelet kernels using a weighting parameter that follows the energy conservation theorems in wavelet frames. The proposed analysis is verified by experimental results for both non-blind and blind watermarking schemes. Such a model is useful to find the optimum input parameters, including the wavelet kernel, coefficient selection, and subband choices for wavelet domain image watermarking