Hybrid Blind Watermarking Using RDWT-DCT in Singular Value Decomposition Domain

In this paper, an improved digital watermarking scheme combined with multi-level discrete cosine transform (DCT), discrete wavelet transform (DWT), and singular value decomposition (SVD) is proposed. To improve the security of the watermark, the encrypted watermark is acquired by Arnold transform before watermark embedding. The proposed scheme is proved to be robust, and its performance is evaluated with respect to the normalized correlation (NC) and peak signal-to-noise ratio (PSNR). The robustness of the proposed scheme is also evaluated under different attacks which include salt and pepper noise, Gaussian noise, and other attacks. The experimental results are also conducted to verify the effect of false positive problem which exists in most watermarking schemes based on SVD.

This paper proposes a new scheme for secure digital watermarking and copyright protection of videos. The approach presented here is based on redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD). The video frames and the watermark are decomposed by RDWT, and the watermark is embedded into the subbands of the I-frames. The singular values of the I-frames are modified with the singular values of the visual watermark. Meanwhile, the watermark embedding strength is adjusted adaptively using the noise visibility function (NVF) with local properties. The approach is efficient and appropriate for real-time applications. The experimental results demonstrate that the proposed approach has good performance in preserving high quality of the video, and the watermark can be extracted accurately after various attacks.

Hybrid and blind watermarking scheme in DCuT – RDWT domain

Day by day, the transmission or sharing of digital information online is increasing due to the fact that Internet usage has become somewhat of an addiction for the majority of people. This results in larger copyright violation problems. Nowadays, most of the data or information is being transmitted in the form of digital images or videos, which are rather simple for the violators of copyright to forge or fake and then share for profit. Thus, digital watermarking came into existence as a possible solution to address these violations of copyright. This article proposes a new blind video watermarking (BVW) using redundant discrete wavelet transform (RDWT) in singular value decomposition (SVD) domain, which utilizes the advantages of both RDWT and SVD to embed and extract the watermark information into the cover video without degrading the quality of the watermark. In addition, an efficient meta‐heuristic optimization with multi‐objective optimization (MOO) is employed to further optimize the proposed RDWT‐SVD approach. Further, various attacks were applied to the watermarked frame to disclose the robustness of proposed BVW using RDWT‐SVD with MOO approach. Extensive simulations on several test videos with comparison to the conventional BVW methodologies exhibit the transcendency of the proposed BVW using RDWT‐SVD with MOO approach in terms of watermarking quality evaluation metrics such as peak signal‐to‐noise ratio (PSNR), structural similarity index, normalized correlation, and even that of root mean square error as well.

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.

To address low training efficiency and poor reconstruction in traditional K Singular Value Decomposition (KSVD) for compressive sensing of shock wave signals, this study proposes an improved algorithm, DH-KSVD, integrating dynamic pruning and hybrid coding. The dynamic pruning mechanism eliminates redundant atoms according to their contributions and adaptive thresholds, while incorporating residual features to enhance dictionary compactness and training efficiency. The hybrid sparse constraint integrates the sparsity of ℓ0-Orthogonal Matching Pursuit (OMP) with the noise robustness of ℓ1-Least Absolute Shrinkage and Selection Operator (LASSO), dynamically adjusting their relative weights to enhance both coding quality and reconstruction stability. Experiments on typical shock wave datasets show that, compared with Discrete Cosine Transform (DCT), KSVD, and feature-based segmented dictionary methods (termed CC-KSVD), DH-KSVD reduces average training time by 46.4%, 31%, and 13.7%, respectively. At a Compression Ratio (CR) of 0.7, the Root Mean Square Error (RMSE) decreases by 67.1%, 65.7%, and 36.2%, while the Peak Signal-to-Noise Ratio (PSNR) increases by 35.5%, 39.8%, and 11.8%, respectively. The proposed algorithm markedly improves training efficiency and achieves lower RMSE and higher PSNR under high compression ratios, providing an effective solution for compressing long-duration, transient shock wave signals.

Watermarking is crucial for protecting medical images, guaranteeing data integrity and authenticity in telemedicine, especially for rural healthcare facilities with limited computational power. This paper introduces a lightweight watermarking scheme that performs a comparative study of Lifting Wavelet Transform (LWT) versus Discrete Wavelet Transform (DWT), both combined with Discrete Cosine Transform (DCT), to achieve optimal imperceptibility, robustness, and computational efficiency. The comparison of LWT and DWT is essential because LWT has lower computational complexity and memory usage, hence more appropriate for resource-limited environments than DWT, and without the use of Singular Value Decomposition (SVD) to further reduce processing requirements and improve compatibility with low-power devices. The suggested approach adopts adaptive embedding against texture complexity, secure synchronization patterns with m-sequences and Barker codes, and geometric correction utilizing ORB for guaranteed watermark extraction under attacks from JPEG compression, Gaussian noise attack, rotation attack, median filter attack, and Gaussian blur. A new error correction code interleaved with majority voting is employed to increase the watermark’s strength. Tested at various embedding strengths, the scheme attains Peak Signal to Noise Ratio (PSNR) values over 40 dB and Structural Similarity Index (SSIM) values above 0.95, signifying extremely little visual degradation. Low Bit Error Rates (BER) and high Normalized Correlation (NC) in various attack scenarios validate its success. This computational-friendly solution is designed to arm remote healthcare organizations with limited computer ability to reliably authenticate and attest to medical images, meeting severe telemedicine demands.

Transform coding has been the focus of the research for image compression. In previous research, the Amplitude and Group Partitioning (AGP) coding scheme is proved to be a low complexity algorithm with higher performance, clearly one of the state-of-art transform coding techniques. However, the previous AGP is used along with the Discrete Cosine Transform (DCT) and the discrete wavelet transform. In this paper, a different transform, the Lapped Orthogonal Transform (LOT), replaces the DCT in conjunction with the AGP. This is the first time LOT and AGP have been combined in a coding method. The definition and design of the LOT are discussed. An objective metric to measure the performance of transform, coding gain, is calculated for both the DCT and the LOT. The LOT has slightly higher coding gain than the DCT. The principles of the LOT based AGP image codec (LOT-AGP) are presented and a complete codec, encoder and decoder, is implemented in software. The performance of the LOT-AGP is compared with other block transform coding schemes: the baseline JPEG codec and the DCT based AGP image codec (DCT- AGP) by both objective evaluation and subjective evaluation. The Peak Signal to Noise Ratio (PSNR) is calculated for these three coding schemes. The two AGP codecs are much better than the JPEG codec on PSNR, from about 1.7 dB to 3 dB depending on bit rate. The two AGP schemes have PSNR differences only to a small degree. Visually, the LOT-AGP has the best-reconstructed images among these three at all bit rates. In addition, the coding results of two other state-of-art progressive image codecs are cited for further comparison. One is the Set Partitioning in Hierarchical Trees (SPIHT) algorithm with a dyadic wavelet transform, and the other is Tran and Nguyen's method with the generalized LOT transform. The AGP coding and the adaptive Huffman entropy coding of LOT-AGP are less complex and the memory usage is smaller than in these two progressive codecs. Comparing these three codecs, i.e. the LOT-AGP and the two progressive codecs in PSNR small only small differences in PSNR. SPIHT has about 1 dB higher PSNR than the LOT-AGP and Tran and Nguyen's method for the test image Lena. For the test image Barbara, the PSNR of the LOT- AGP is about 0.5 dB higher than that of the SPIHT and 0.5 dB lower than that of Tran and Nguyen's method. This low- complexity and high performance codec may provide a new direction for the implementation of image compression.

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.

This paper contrasts the implementation of several chaos-based digital image watermarking techniques in terms of imperceptibility, robustness, security and complexity. Most spatial and transform domains methods have been used namely Least Significant Bit (LSB), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Redundant Discrete Wavelet Transform (RDWT) with Singular Value Decomposition (SVD) mathematical tool which has enhanced embedding capability. Both continuous and discrete chaotic maps namely Arnold's Chaotic Map (ACM), Logistic Chaotic map (LCM) and Lorenz Chaotic Map (LoCM) are included to result in secure schemes. Exhaustive series of tests have been performed along with a range of evaluation metrics for imperceptibility evaluation. In addition, Robustness of all the techniques has also been confirmed by applying a variety of attacks on the resulting images. This study will help to adopt the most suitable methods for a given application as sufficient number of test images have been utilized.

Watermarking has become a crucial technique for protecting copyright and verifying the authenticity of images due to the rapid distribution of digital images and the ease and reliability of image content modification. In this research, we introduce a hybrid digital picture watermarking method that is both secure and resilient. This would use the discrete wavelet transform (DWT), the discrete cosine transforms (DCT), singular value decomposition (SVD), and cryptographic systems such as RSA and chaotic maps. Hence, this method tries to balance the tradeoff of robustness, security, and imperceptibility. We first encrypt the watermark using RSA, and then a chaotic logistic map (CLM) scrambles the already designed encrypted watermark to further enhance its robustness. By putting the watermark in the host image's separately calculated DWT-DCT coefficients, the proposed method works well even when compression, noise addition filtering, and geometric attacks are used. The test results demonstrate that the suggested method does better than other methods in Structural Similarity Index (SSIM), Normalized Correlation (NC), and Peak Signal-to-Noise Ratio (PSNR). Regardless of the nature of the attack, our proposed method consistently generates PSNR values above 55 dB and NC values above to 0.90, indicating correct watermark extraction and excellent image perception. We use cryptographic methods to secure the watermark from retrieval and modification by unauthenticated users. In addition, our approach is superior to the current watermarking methods in robustness and unobtrusiveness. In further works, we plan to improve the robustness of the approach against more complex geometric attacks and apply it for watermarking video and 3D content.

Due to the development of the latest technologies in the areas of communication and networking, the present businesses are moving to the digital world for accuracy, accessibility, safety and security. Normally, the medical image requires additional care to handle because treatment is mainly focused on the detail received from the medical images. Nowadays, digital watermarking is a blooming methodology for protecting medical data as for as security is concerned. This proposed method gives a new watermarking scheme for a secure transfer of Electronic Patient Record (EPR) using Hybrid Transform (DWT+DCT+SVD). Initially, the medical image is decomposed by Discrete Wavelet Transform then after Discrete Cosine Transform is performed in LH band and then Singular Value Decomposition is performed and a similar process to be done for the watermark image for embedding process and perform an inverse process for obtaining the watermarked image. Similarly, the above process to be done for the extraction process on the watermarked image to exact the EPR data and medical image. The effectiveness and performance of the proposed watermarking scheme being analyzed by measuring Peak Signal to Noise Ratio (PSNR) and Quality Index. The result is discussed with the help of experimental results using MATLAB tools.

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.

Information system security is a crucial aspect in the digital era, especially for protecting sensitive data. One method to enhance data security is steganography, a technique for concealing information within digital media. This study analyzes the effectiveness of the Discrete Cosine Transform (DCT) method in digital image steganography. The research follows several stages, including literature review, system design, DCT implementation using MATLAB/Python, and performance evaluation based on Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Normalized Correlation (NC). Experimental results indicate that the DCT method achieves a high PSNR value (averaging above 40 dB) and a low MSE value, ensuring minimal image distortion after data embedding. Compared to the Least Significant Bit (LSB) method, DCT provides better resistance to visual analysis and is more suitable for images with transform-based compressions, such as JPEG. This study concludes that the DCT method is an effective steganography technique for enhancing information system security, despite challenges related to computational complexity and data embedding capacity. Future research may explore hybrid methods that combine DCT with other techniques to improve efficiency and robustness against various steganographic analysis attacks.

Communication of the images over the network calls for an approach to ensure security and ownership protection while exchanging images over the network. This paper proposes an improved blind watermarking scheme capable of offering image authentication, protection, and detachment avoidance between the watermark and its corresponding image. The proposed technique is composed of three modules; generator, protector, and resizer. The generator deals with embedding and extracting the watermark from the host image. Protector deals with encryption and decryption using a high dimensional chaotic system. And resizer deals with compressing and decompressing the watermarked image. The novelty related scientific literature is the encryption of Singular Value Decomposition (SVD) components, and watermark in a criss-cross manner using logistic map along with hyperchaotic system to achieve the confidentiality and avoid false positive problem (FPP). Whereas, embedding into RGB (red, green, blue components) is centered on singular value decomposition and level-2 Discrete Wavelet Transform. The joint operation is performed at sender’s side and receiver’s side, i.e., encryption, embedding, and compression is performed at sender’s side whereas decompression and decryption procedures are performed at the receiver’s side. Additionally, compressing the data reduces the higher bandwidth requirements. The performance of the proposed scheme is based on subjective and objective evaluation. Experimental results such as PSNR (peak signal-to-noise ratio), NC (normalized correlation), BER (bit error rate), CR (compression ratio), NPCR (number of pixel change rate), and SSIM (structural similarity index) indicate that the proposed technique approaches the standard main level.