Gray image watermarking using slant transform, lifting wavelet transform and singular value decomposition

In this paper, a novel image watermarking method is proposed which is based on discrete wave transformation (DWT), Hessenberg decomposition (HD), and singular value decomposition (SVD). First, in the embedding process, the host image is decomposed into a number of sub-bands through multi-level DWT, and the resulting coefficients of which are then used as the input for HD. The watermark is operated on the SVD at the same time. The watermark is finally embedded into the host image by the scaling factor. Fruit fly optimization algorithm, one of the natural-inspired optimization algorithms is devoted to find the scaling factor through the proposed objective evaluation function. The proposed method is compared to other research works under various spoof attacks, such as the filter, noise, JPEG compression, JPEG2000 compression, and sharpening attacks. The experimental results show that the proposed image watermarking method has a good trade-off between robustness and invisibility even for the watermarks with multiple sizes.

In this paper, we propose a new method of image watermarking by using contourlet transform along with singular value decomposition. Contourlet transform is a new two-dimensional extension of the wavelet transform using multi-scale and directional filter banks. For security aspect of the watermarking algorithm and to improve imperceptibility of the algorithm, watermark bits are permuted by an interleaver. In embedding part, contourlet transform is applied to host image and appropriate direction is selected by considering intensity variance of all directions. Coefficients are modified by combining singular values of selected direction with singular values of watermark image. Experimental results show no visible difference between host and watermarked images. The proposed watermarking method is also robust to various attacks such as JPEG compression, rotation, histogram modification, Gaussian and median filtering and gamma correction.

In this paper, a novel medical image watermarking (MIW) technique for tele ‐ medicine applications is proposed. In this approach homomorphic transform (HT), redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD) transforms are successfully utilized for developing an effective watermarking technique. Reflectance component of medical host image is obtained using HT, on which RDWT decomposition and SVD are applied. Similarly medical watermark image is processed with RDWT and SVD. Singular values (Svs) were used for embedding the watermark image into host image. 2‐D chaotic Arnold transform (AT) is used for providing extra security to the watermark image by encrypting the watermarked image. Moreover, proposed technique is also tested for several wavelet families. Robustness and imperceptibility of the proposed technique is enhanced as depicted in experimental results under various attacks. Furthermore, better robustness is attained from proposed technique on comparing it with other formerly reported schemes.

Image compression is preferred for less storage space, sending image on the internet and often for medical imaging in health industry, technical drawings or comics. Because of wide popularity of sharing media in internet, compression plays a major role in the watermarking algorithm. This paper presents a compression technique through image watermarking algorithm based on Non-subsampled Contourlet Transform (NSCT) and Singular Value Decomposition (SVD). NSCT and SVD both are explored for image watermarking. For image compression, only Singular Value Decomposition is used. The NSCT can give more accurate coefficients of the edges and contours in image which is shift invariant. After getting the coefficients from NSCT decomposition SVD is applied to break the matrix in a convenient way so that image compression can be done without losing meaningful data. The compressed singular values of NSCT decomposed coefficients of cover image are added with the compressed singular values of NSCT decomposed coefficient of gray key image. This helps to improve the performance of the compression using watermarking method. In terms of PSNR and compression ratio, the performance of this scheme is analyzed. The proposed algorithm is robust and suitable for copyright protection and data transmission against compression applications.

The tradeoff between the embedding energy of watermark and the perceptual translucence and the image fidelity following attacks represents an important issue in watermarking images. This paper hence proposed a population based method called jumping particle swarm optimization algorithm (JPSO) to improve the ownership and imperceptibility of image. Accordingly, JPSO algorithm is utilized in the maximization the quality of watermarked image, particularly within the extracted watermarks. The former is resolvable via embedding owner’s watermark components of into the host image while the latter is determined by the amount of the embedded scaling factor of the principle components. The robustness of watermarking can be improved using JPSO, where the appropriate scaling factor is optimized. JPSO invisible watermarking involves the use of the host’s global and local characteristics, besides watermark images within the Singular Value Decomposition (SVD) domain. The obtained results of the recommended technique affirm the reliable identification of the watermark image ownership and even following severe attacks. Comparisons with other comparable techniques affirm the superiority of this study’s recommended technique.

In telemedicine, the authenticity and integrity of medical images must be safeguarded. Copyright protection is provided through robust medical image watermarking (MIW) methods, and the original pictures may be retrieved at the receiver's end. But existing algorithms have limits in terms of balancing the tradeoff between robustness, imperceptibility, and embedded capacity. Aside from that, most MIW algorithms aren't built for color images. This article proposes a novel MIW technique based on the redundant discrete wavelet transform (RDWT) with singular value decomposition (SVD) to increase their performance in preserving medical color picture information. First and foremost, the RDWT -SVD is a reliable solution as compared to the conventional DWT. Second, modifying the wavelet domain coefficient ensures that integer values in the spatial domain change and that the watermarking process is reversible. Finally, the embedding approach makes full advantage of the original image's features and watermarking. The simulation results showed that the proposed method decreases the amount of original picture change and improves imperceptibility as compared to the conventional approaches.

An enhanced hybrid image watermarking scheme for security of medical and non-medical images based on DWT and 2-D SVD

This paper propose a robust image watermarking scheme based on the singular value decomposition (SVD) and genetic algorithm (GA). SVD based watermarking techniques suffer with an issue of false positive problem. This leads to even authentication the wrong owner. Prevention of false positive errors is a major challenge for ownership identification and proof of ownership application using digital watermarking. We employed GA algorithm to optimize the watermarked image quality (robustness) of the extracted watermarks. The former can be overcome by embedding the owner’s components of the watermark into the host image, the latter is dependent on how much the quantity for the scaling factor of the principle components is embedded. To improve the quality of watermarking (robustness), GA is used for optimize the suitable scaling factor. Experimental result of the proposed technique proves the watermark image ownership and can be reliably identified even after severe attacks. The comparison of the proposed technique with the state of the art show the superiority of our proposed technique where it is outperforming the methods in comparison.

In this paper, a novel image watermarking scheme using an encrypted kinoform in the hybrid nonsubsampled contourlet transform (NSCT) and singular value decomposition (SVD) domain is presented. In the scheme, a watermark is firstly transformed into an encrypted kinoform with fractional Fourier transform and Gerchberg-Saxton algorithm. Then the host image is decomposed with NSCT and the low frequency sub-band is divided into nonoverlapping blocks. SVD is applied to every block. The kinoform is embedded into the low frequency NSCT coefficients by modifying the largest singular value of each block. To withstand geometric attacks, the geometric distortion parameters of the attacked watermarked image are computed first by the Zernike moment-based geometric correction method in the detection process. Then the mark kinoform is extracted from the recovered image. In comparison with other method, the proposed watermarking scheme offers better performances for imperceptibility. Experimental results demonstrate that the proposed image watermarking is not only invisible but also robust against a variety of attacks including scaling, rotation, flipping, noise addition, filtering, JPEG compression, etc.

A blind dual color images watermarking based on singular value decomposition

With the fast development in computer network and multimedia technology, digital data (such as image, video, audio or text) are stored, transmitted and distributed through internet without any loss or damage of content. Digital image watermarking is use for the protection of digital data from the illegal manipulations. Watermarking not only allow user to access, view and interpret the image but also protects the ownership of the content, as protection is a crucial area. In this paper, a new semi-blind composite image watermarking algorithm based on DWT-SVD that is robust against various attacks is proposed. We obtained four different frequency images using DWT and IDWT transform. Watermark is embedded in high frequency sub-band by modifying the values of Singular Value Decomposition (SVD). Scaling factor is used to improve. Various experimental results demonstrate that proposed algorithm is able to withstand under various attack.

Digital imaging and communications in medicine are being applied widely to improve health care for people, and their security attracted our attention when they are transmitted through the Internet. The paper proposes a digital watermarking method for medical images based on digital holography and three-level discrete wavelength transform (DWT) singular value decomposition (SVD), where a live code including privacy information is transformed into digital holography by an improved computer-generated hologram method. The holography then is embedded into the singular values of the LL3 subband wavelet of the medical image. Experimental results show that the proposed method provides sufficient security results against various attacks, especially geometrical attacks.

ABC optimized secured image watermarking scheme to find out the rightful ownership

In this proposed work, a dual image watermarking algorithm is used to protect the data against copyright violations. In this work, the DICOM image is used as a host image. Two watermark images used are the MNNIT logo and the personal data of the patient. This method utilizes the advantages of Schur decomposition, lifting wavelet transform (LWT), discrete cosine transform (DCT) and singular value decomposition (SVD). The scaling factor is a vital parameter of watermarking technique. The firefly optimization technique is used to get the optimized scaling factor. The Speeded-up robust features (SURF) are used for watermarking authentication. To evaluate the performance of the proposed algorithm, peak signal-to-noise ratio (PSNR), normalized correlation coefficient (NCC), and structural similarity index measurement (SSIM) are used. The proposed method is tested against various attacks such as Salt and Pepper noise, Gaussian noise, Gaussian low pass filter, Average filter, Median filter, Histogram equalization, Sharpening, Rotation and Region of interest filtering. The proposed algorithm shows a high level of robustness and imperceptibility. It is found that the features of the input host image and the watermarked image are matching correctly on applying the SURF technique.

Digital watermarking provides the solution for problems such as copyright and authentication in today’s digital world of communication. Trustworthy watermarking techniques should provide the protection for rightful ownership, robustness and resist against attacks such as filtering and modification. In this paper, we proposed an efficient watermarking scheme based on singular value decomposition (SVD) and quantum Hilbert image scrambling. In the proposed watermarking scheme, first watermark is scrambled using quantum Hilbert image scrambling then perform alpha blending on scrambled watermark and SVD transformed cover image followed by alpha mixing operation. Finally, perform SVD operation of the generated signal; after alpha blending operation, we get watermarked image. The experimental results show strength of the proposed technique in terms of the robustness and security. Performance of the proposed scheme is tested on different image quality parameters of watermarked and host image. These are peak signal-to-noise ratio (PSNR), mean square error (MSE) and normalized cross-correlation (NCC), average difference (AD), maximum difference (MD), and structural contents (SC).KeywordsSingular value decompositionWatermarkQuantum Hilbert image scramblingSteganography