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Invertible colour‐to‐grey algorithms protect the colour of an image against illegal usage and distribution. These schemes hide the colour information into a grayscale version of the image, making colour recovery without proper authorization challenging. A previous study proposed the incorporation of content security by distorting the protected image to hinder illegal structure restoration. This work addresses the limitations of this method, significantly improving both processing time and the quality of the recovered colour image. Specifically, processing times are reduced from 45 h to 9 s, and the mean PSNR value is increased by up to 2.23 dB. Furthermore, this proposal achieves competitive results compared to existing approaches that do not implement content security, obtaining mean peak signal‐to‐noise ratio (PSNR) and structural similarity index measure (SSIM) values above 42.32 dB and 0.992, respectively. Finally, quantitative results are supported by visual comparisons. [ABSTRACT FROM AUTHOR]

In today’s digitally-driven world flooded with digital content and the widespread availability of images online, digital image watermarking is crucial. It ensures copyright protection, maintains content authenticity, and preserves the integrity of visual information. In this paper, a reversible watermarking technique is proposed based on splitting the gray scale image pixel’s intensity value and conventional prediction error expansion. To begin with, the pixel values of an image are split and posted into two distinct groups. The values in the hundred’s and ten’s place are categorized as the higher order pixel group (α ), while the values in the units place are categorized as lower order pixel group (β ). Through this splitting process, it has been noticed that numerous adjacent pixels share identical values. In order to embed data, the conventional Prediction Error Expansion technique is employed specifically for the higher order pixel group. After determining the prediction error, it will be expanded and secret data is embedded into it. This scheme has been experimentally verified that it is superior than few existing state of art schemes. With a high embedding capacity of about 65335 bits in a single 512 × 512 image, the watermarked images exhibited a PSNR of approximately 36.34 dB and an SSIM of around 0.94. Payloads for 10,000 and 20,000 bits are tested and their PSNR values are 44.56 dB and 41.35 dB respectively. [ABSTRACT FROM AUTHOR]

The field of image processing has seen remarkable advancements over the past few decades, and Discrete Wavelet Transform (DWT) has emerged as a powerful tool within this domain. This review article provides a comprehensive overview of previously published works that focus on DWT’s application in image processing. DWT offers multi-resolution analysis capabilities, making it particularly useful for various image processing tasks such as de-noising, compression, enhancement, and feature extraction. This review explores the fundamental principles of DWT and its mathematical foundations. We delve into its advantages over traditional Fourier Transform methods, particularly its ability to handle non-stationary signals and provide both frequency and spatial information simultaneously. The article surveys the application of DWT in different image processing techniques. It discusses how DWT contributes to the efficiency and effectiveness of image compression algorithms, such as the JPEG 2000 standard, and its role in reducing noise while preserving important image features. [ABSTRACT FROM AUTHOR]

Abstract Invertible colour‐to‐grey algorithms protect the colour of an image against illegal usage and distribution. These schemes hide the colour information into a grayscale version of the image, making colour recovery without proper authorization challenging. A previous study proposed the incorporation of content security by distorting the protected image to hinder illegal structure restoration. This work addresses the limitations of this method, significantly improving both processing time and the quality of the recovered colour image. Specifically, processing times are reduced from 45 h to 9 s, and the mean PSNR value is increased by up to 2.23 dB. Furthermore, this proposal achieves competitive results compared to existing approaches that do not implement content security, obtaining mean peak signal‐to‐noise ratio (PSNR) and structural similarity index measure (SSIM) values above 42.32 dB and 0.992, respectively. Finally, quantitative results are supported by visual comparisons.

Abstract Image hiding is a task that hides secret images into cover images. The purposes of image hiding are to ensure the secret images are invisible to the human and the secret images can be recovered. The current state‐of‐the‐art steganography methods run the risk of secret information leakage. A safe image hiding network (SIHNet) is presented to reduce the leakage of secret information. Based on some phenomena of image hiding methods which use invertible neural network, a reversible secret image processing (SIP) module is proposed to make the secret images suitable for hiding and make the stego images leak less secret information. Besides, a reversible lost information hiding (LIH) module is used to hide the lost information into the cover images, thus the method can recover the secret images better than the method that uses random noise to replace the lost information. Experimental results show that SIHNet outperforms other state‐of‐the‐art methods on the PSNR and SSIM values of the recovered secret images and the stego images. Besides, residual images of other state‐of‐the‐art methods all contain information about secret images while residual images of SIHNet leak almost no secret information. Thus the method can prevent the listener of transmission channel from obtaining the information of the secret image through the residual image, which means SIHNet performs better in security than other state‐of‐the‐art methods.

In recent years, image watermarking has become the most active research in the information hiding field. This paper presents an application of a computational intelligence technique to obtain robust and secure image-watermarking schemes for data image transmission. The optimization goal is achieved via a new robust method based on the hybridization (in the digital domain) of the image-watermarking scheme using Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The Forensic-Based Investigation (FBI) optimization algorithm is considered to search for the best scaling factor and the appropriate location for the watermark insertion. The Arnold Transform (AT) encryption is also introduced to enhance the watermark image process security. To show the efficiency of the proposed schemes, several watermarked images are subjected to several attacks, and their imperceptibility and robustness are checked via structural similarity index measure (SSIM) and Normalized Correlation Coefficient (NCC) where the proposed schemes provide competitive simulation results. Statistical analysis is also carried out to prove the performance of the used optimization algorithm.

Image hiding is a task that hides secret images into cover images. The purposes of image hiding are to ensure the secret images are invisible to the human and the secret images can be recovered. The current state‐of‐the‐art steganography methods run the risk of secret information leakage. A safe image hiding network (SIHNet) is presented to reduce the leakage of secret information. Based on some phenomena of image hiding methods which use invertible neural network, a reversible secret image processing (SIP) module is proposed to make the secret images suitable for hiding and make the stego images leak less secret information. Besides, a reversible lost information hiding (LIH) module is used to hide the lost information into the cover images, thus the method can recover the secret images better than the method that uses random noise to replace the lost information. Experimental results show that SIHNet outperforms other state‐of‐the‐art methods on the PSNR and SSIM values of the recovered secret images and the stego images. Besides, residual images of other state‐of‐the‐art methods all contain information about secret images while residual images of SIHNet leak almost no secret information. Thus the method can prevent the listener of transmission channel from obtaining the information of the secret image through the residual image, which means SIHNet performs better in security than other state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Advanced internet technology allows unauthorized individuals to modify and distribute digital images. Image watermarking is a popular solution for copyright protection and ensuring digital security. This research presents an embedding scheme with a set of conditions using non-subsampled Shearlet transform (NSST), lifting wavelet transform (LWT), and discrete cosine transform (DCT). Red and green channels are employed for the embedding process. The red channel is converted by NSST-LWT. The low-frequency area (LL) frequency is then split into small blocks of 8×8, each partition block is then transformed by DCT. The DCT coefficient of (3,4), (5,2), (5,3), (3,5), called matrix M1, and (2,5), (4,3), (6,2), (4,4), called matrix M2 are selected for singular value decomposition (SVD) process. With a set of conditions, the watermark bits are incorporated into those singular values. The green channel is cropped to get the center image before splitting into 4×4 pixels. The block components are then selected based on the least entropy value for the embedding regions. The selected blocks are then computed using LWT-SVD. A set of conditions for U(1,1) and U(2,1) are used to incorporate the watermark logo. The experimental findings reveal that the suggested scheme achieves high imperceptibility and resilience under various evaluating attacks with an average peak signal-to-noise ratio (PSNR) and correlation value (NC) values are up to 43.89 dB and 0.96, respectively. [ABSTRACT FROM AUTHOR]

In the field of image watermarking technology, it is very important to balance imperceptibility, robustness and embedding capacity. In order to solve this key problem, this paper proposes a new color image adaptive watermarking scheme based on discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD). In order to improve the security of the watermark, we use Lorenz hyperchaotic mapping to encrypt the watermark image. We adaptively determine the embedding factor by calculating the Bhattacharyya distance between the cover image and the watermark image, and combine the Alpha blending technique to embed the watermark image into the Y component of the YCbCr color space to enhance the imperceptibility of the algorithm. The experimental results show that the average PSNR of our scheme is 45.9382 dB, and the SSIM is 0.9986. Through a large number of experimental results and comparative analysis, it shows that the scheme has good imperceptibility and robustness, indicating that we have achieved a good balance between imperceptibility, robustness and embedding capacity. [ABSTRACT FROM AUTHOR]

Robustness, imperceptibility, and watermark capacity are three indispensable and contradictory properties for any image watermarking systems. It is a challenging work to achieve the balance among the three important properties. In this paper, by using bivariate Birnbaum–Saunders (BRBS) distribution model, we present a statistical image watermark scheme in nonsubsampled shearlet transform (NSST)-pseudo Zernike moments (PZMs) magnitude hybrid domain. The whole watermarking algorithm includes two parts: watermark embedding and extraction. NSST is firstly performed on host image to obtain the frequency subbands, and the NSST subbands are divided into non overlapping blocks. Then, the significant high-entropy NSST domain blocks are selected. Meanwhile, for each selected NSST coefficient block, PZMs are calculated to obtain the NSST-PZMs amplitude. Finally, watermark signals are inserted into the amplitude hybrid domain of NSST-PZMs. In order to decode accurately watermark signal, the statistical characteristics of NSST-PZMs magnitudes are analyzed in detail. Then, NSST-PZMs magnitudes are described statistically by BRBS distribution, which can simultaneously capture the marginal distribution and strong dependencies of NSST-PZMs magnitudes. Also, BRBS statistical model parameters are estimated accurately by modified closed-form maximum likelihood estimator (MML). Finally, a statistical watermark decoder based on BRBS distribution and maximum likelihood (ML) decision rule is developed in NSST-PZMS magnitude hybrid domain. Extensive experimental results show the superiority of the proposed image watermark decoder over some state-of-the-art statistical watermarking methods and deep learning approaches. [ABSTRACT FROM AUTHOR]

Image watermarking often involves the use of handheld devices under non-structured conditions for authentication purposes, particularly in the print-cam process where smartphone cameras are used to capture watermarked printed images. However, these images frequently suffer from perspective distortions, making them unsuitable for automated information detection. To address this issue, Cam-Unet, an end-to-end neural network architecture, is presented to predict the mapping from distorted images to rectified ones, specifically tailored for print-cam challenges applied to ID images. Given the limited availability of large-scale real datasets containing ground truth distortions, we created an extensive synthetic dataset by subjecting undistorted images to print-cam attacks. The proposed network is trained on this dataset, using various data augmentation techniques to improve its generalization capabilities. Accordingly, this paper presents an image watermarking system for the print-cam process. The approach combines Fourier transform-based watermarking with Cam-Unet as perspective distortion correction. Results show that the proposed method outperforms existing watermarking approaches typically employed to counter print-cam attacks and achieves an optimal balance between efficiency and cost-effectiveness. [ABSTRACT FROM AUTHOR]

Abstract In open networks, the geometric deformation and common image processing are common image manipulation modes, which pose a great challenge in robust watermarking. To improve the robustness of GRHFM‐based watermarking, a watermarking algorithm based on the fast GRHFM calculation method and ant colony optimization (ACO) based fractional parameter selection method is proposed. With the similarity between the discrete Fourier transform and GRHFM moment calculation, the algorithm utilizes fast Fourier transform to improve the GRHFM calculation accuracy and speed. To select the optimal GRHFM fractional parameter for watermarking algorithm, ACO is introduced to the fractional parameter adaptive selection method. Here, the fast Fourier transform‐based calculation method is combined with the adaptive parameter selection method to maximize the invisibility and robustness of watermarking. The experimental results indicate that the algorithm achieves higher robustness with the same payload and invisibility compared with other existing watermarking methods.

There is a plethora of image authentication techniques in the literature. Almost all of these methods use either a form of watermarking or data hiding techniques to embed data directly in the original image or its decomposed sub-bands. Recently, new multiple watermarking methods have emerged to tackle more robust forgery challenges where a single watermark fails or insufficient. Most of these methods are directed towards medical images for obvious reasons. This paper presents a new precise blind image-variant authentication method. This method initiates a new direction for research on image authentication as it does not embed any sort of data in the original image or its decomposed sub-band(s) but rather produces an image-variant via manipulating some statistics of the original image. These variations represent two sequences which were infused in two QR-codes that enabled the variation process. We tested this method against image processing attacks including JPEG compression, resizing, and Gaussian-noise using images from several databases including the USC – SIPI, McGill Calibrated Color Image, DICOM medical image. Also, we compared this method performance with results from seven 7 published methods and found that our method scored higher performance results for robustness and imperceptibility and it regenerated the variation secret sequences with 100% accuracy in each case. Furthermore, this method capacity is large enough to prevent data-overflow. [ABSTRACT FROM AUTHOR]

In recent years, image watermarking has become the most active research in the information hiding field. This paper presents an application of a computational intelligence technique to obtain robust and secure image-watermarking schemes for data image transmission. The optimization goal is achieved via a new robust method based on the hybridization (in the digital domain) of the image-watermarking scheme using Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The Forensic-Based Investigation (FBI) optimization algorithm is considered to search for the best scaling factor and the appropriate location for the watermark insertion. The Arnold Transform (AT) encryption is also introduced to enhance the watermark image process security. To show the efficiency of the proposed schemes, several watermarked images are subjected to several attacks, and their imperceptibility and robustness are checked via structural similarity index measure (SSIM) and Normalized Correlation Coefficient (NCC) where the proposed schemes provide competitive simulation results. Statistical analysis is also carried out to prove the performance of the used optimization algorithm. [ABSTRACT FROM AUTHOR]

Nowadays, many image watermarking algorithms based on matrix decomposition have been proposed. In this paper, the properties of polar decomposition in the field of image watermarking is found, that is, embedding the watermark information into diagonal elements of the semi-positive definite matrix can improve the invisibility of the watermark. However, the diagonal elements have poor robustness. Based on this, lifting wavelet transform, which is the second generation wavelet transform, and Hadamard transform are used to improve the robustness of watermarking. In addition, image geometric correction algorithms are also combined to resist geometric attacks. The robustness and comparison experiments show that the proposed algorithm is superior to some state-of-the-art algorithms in some attacks. [ABSTRACT FROM AUTHOR]

Since multimedia data are now more widely distributed in digital form and easier to copy and change, copyright protection has become an essential need. One of the most common copyright protection techniques is watermarking. Invisibility and robustness are crucial aspects of watermarking; however, many of the currently used techniques simply focus more on invisibility than how robust they are. Moreover, the trade-off between invisibility and robustness is challenging. To this end, this paper proposes a novel watermark technique that efficiently overcomes the idea of a trade-off between robustness and invisibility, thereby increasing both under most attacks. Schur decomposition and a dynamic weighting factors matrix are added to the embedding process to improve the robustness of the proposed technique. Besides that, the embedding function is improved to simultaneously maximize imperceptibility and robustness. Another key contribution of the proposed approach is its use of a trajectory-based optimization algorithm rather than the more prevalent population-based algorithms to determine the optimal scaling factors. Consequently, the proposed technique rapidly identifies the best scaling factors for the embedding function. Statistical analysis is performed using the Friedman test. Experimental results show that the proposed technique outperforms other existing techniques for different sizes, shapes, and types of watermarks. [ABSTRACT FROM AUTHOR]

In open networks, the geometric deformation and common image processing are common image manipulation modes, which pose a great challenge in robust watermarking. To improve the robustness of GRHFM‐based watermarking, a watermarking algorithm based on the fast GRHFM calculation method and ant colony optimization (ACO) based fractional parameter selection method is proposed. With the similarity between the discrete Fourier transform and GRHFM moment calculation, the algorithm utilizes fast Fourier transform to improve the GRHFM calculation accuracy and speed. To select the optimal GRHFM fractional parameter for watermarking algorithm, ACO is introduced to the fractional parameter adaptive selection method. Here, the fast Fourier transform‐based calculation method is combined with the adaptive parameter selection method to maximize the invisibility and robustness of watermarking. The experimental results indicate that the algorithm achieves higher robustness with the same payload and invisibility compared with other existing watermarking methods. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced watermarking technique through discrete wavelet transform (DWT), singular value decomposition (SVD) and Bi- dimensional empirical mode decomposition (BEMD) is presented. During the embedding process, the first level of DWT has applied to decompose an original image into distinct sub-bands (LL, LH, HH, HL). Further, BEMD decomposition is applied to divide sub-bands of DWT according to the robust and least fragile bands. SVD is employed to compute the singular coefficient on a certain band for an embedding process. The proposed technique is implemented with haar wavelet. Further, an inverse process of IDWT, ISVD and IBEMD is applied to this method to get the watermarked image. Moreover, watermark images can be extracted by the extraction process. BEMD is used to get the multiple range representation in the form IMFs. Also, it is used to improve the visual quality of an image. Moreover, the fusion of SVD, DWT and arnold transform is employed to increase the security, robustness and imperceptibility of an image against various attack. Finally, the subjective measure is used to assess the visual quality of the watermarked image. The proposed method provides better imperceptibility, security and robustness against numerous geometrical and non- geometrical attacks such as salt & pepper, Gaussian attack, JPEG compression, median filter, shearing. [ABSTRACT FROM AUTHOR]

Nowadays, medical imaging has become an indispensable tool for the diagnosis of some pathologies and as a health prevention instrument. In addition, medical images are transmitted over all types of computer networks, many of them insecure or susceptible to intervention, making sensitive patient information vulnerable. Thus, image watermarking is a popular approach to embed copyright protection, Electronic Patient Information (EPR), institution information, or other digital image into medical images. However, in the medical field, the watermark must preserve the quality of the image for diagnosis purposes. In addition, the inserted watermark must be robust both to intentional and unintentional attacks, which try to delete or weaken it. This work presents a bio-inspired watermarking algorithm applied to retinal fundus images used in computer-aided retinopathy diagnosis. The proposed system uses the Steered Hermite Transform (SHT), an image model inspired by the Human Vision System (HVS), as a spread spectrum watermarking technique, by leveraging its bio-inspired nature to give imperceptibility to the watermark. In addition, the Singular Value Decomposition (SVD) is used to incorporate the robustness of the watermark against attacks. Moreover, the watermark is embedded into the RGB fundus images through the blood vessel patterns extracted by the SHT and using the luma band of Y'CbCr color model. Also, the watermark was encrypted using the Jigsaw Transform (JST) to incorporate an extra level of security. The proposed approach was tested using the image public dataset MESSIDOR-2, which contains 1748 8-bit color images of different sizes and presenting different Diabetic Retinopathy (DR). Thus, on the one hand, in the experiments we evaluate the proposed bio-inspired watermarking method over the entire MESSIDOR-2 dataset, showing that the embedding process does not affect the quality of the fundus images and the extracted watermark, by obtaining average Peak Signal-to-Noise Ratio (PSNR) values higher to 53 dB for the watermarked images and average PSNR values higher to 32 dB to the extracted watermark for the entire dataset. Also, we tested the method against image processing and geometric attacks successfully extracting the watermarking. A comparison of the proposed method against state-of-the-art was performed, obtaining competitive results. On the other hand, we classified the DR grade of the fundus image dataset using four trained deep learning models (VGG16, ResNet50, InceptionV3, and YOLOv8) to evaluate the inference results using the originals and marked images. Thus, the results show that DR grading remains both in the non-marked and marked images. [ABSTRACT FROM AUTHOR]

This work presents a robust digital image watermarking scheme to protect digital images from illegal usage and manipulations. The excellent re-constructional attributes of integer wavelets transform (IWT) coefficients are fused with all phase discrete cosine bi-orthogonal transform (APDCBT), which helps preserve the image's visual quality. Human visual system (HVS) parameters help to choose an optimal watermarking region to improve image imperceptibility to a greater extent. To achieve better watermark robustness in diverse attack conditions (in the presence of geometric and non-geometric attacks), we proposed two stages distortion correction technique for restoring watermarked geometry followed by a non-geometric correction. Geometric distortion correction (GDC) techniques have been implemented in a deep framework employing a pre-trained network of MobileNet-V2, customized to perform the task of a regressor to handle diverse geometric attacks. Statistical non-geometric correction technique addresses the non-geometric attack and restores the deviated coefficient values without considering any other local characteristics of the watermarked image. This method provides adequate image imperceptibility as well as satisfactory robustness of the watermark under both attack conditions. Also, the technique can give an average imperceptibility (in PSNR) of ~ 49.03 dB with a payload of 1024 bits. The experimental results suggest that the proposed scheme is secure and provides enhanced performance compared to existing techniques. [ABSTRACT FROM AUTHOR]

The modern internet technology enables unauthorized individuals to alter the content of digital images. This work introduces a method for enhancing the robustness of an embedded watermark in images using Lifting Wavelet Transform (LWT) and Hessenberg Decomposition. This study utilizes Hessenberg Decomposition (HD) to insert a watermark image into the LL-sub band of the LWT transform. Singular Value Decomposition (SVD) is employed to convert the H value of HD. Subsequently, the watermark image is put into the singular value. The suggested system underwent testing against a range of image processing assaults, including compression, filters, and noise additions. The testing was conducted using multiple watermark sizes, specifically 256×256, 128×128, and 64×64 pixels. The experimental results demonstrate exceptional imperceptibility, with an average PSNR value of 39.5640 dB and a SSIM value of 0.9993. The results demonstrate a high level of resilience, as indicated by the NC value of 0.96390.

This paper proposed two evaluation metrics of the tamper coincidence in a block map design for image watermarking. These evaluation metrics are called Tamper Coincidence Block Ratio (TCBR) and Tamper Coincidence Block Density (TCBD). A tamper coincidence occurred in image authentication and self-recovery when the recovery data and the original block location were tampered with simultaneously. A high tamper coincidence limits image inpainting’s capability to recover the region, leading to an imprecise recovered image. The ratio and density of the tamper coincidence may significantly affect the final recovered image quality. Previously, researchers mentioned the tamper coincidence in their experiment but did not evaluate it with any metrics. They evaluated the robustness of their technique based on the final recovered image quality using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM). Tamper coincidences are primarily affected by the block map design implemented by the researcher. Thus, TCBR and TCBD provide valuable insight into the block map design’s effectiveness in preventing tamper coincidence. The experimental result shows that the TCBR and TCBD values are inversely proportional to the recovered image quality. A high TCBR and TCBD value leads to low recovered image quality. Therefore, this paper will help the researchers design an effective block map by minimizing the TCBR and TCBD values to obtain the highest recovered image quality.

This paper presents a new triple self-embedding fragile watermarking technique for image tamper detection and recovery. This approach divides the host image into non-overlapping regions according to the block map and further divides each region into $5\times 5$ non-overlapping blocks. For each block, block directions are obtained from the adjacent pixel differences. The recovery information for each block is constructed by computing the block directions, differences of the directions and the mean value of each block. The authentication information for each block is generated using an Singular Value Decomposition (SVD)-based approach. The recovery information is embedded in three different blocks determined using a block map while authentication information is embedded in the block itself using the three least significant bits. The developed approach provides a triple recovery opportunity for each block due to the triple embedding. Consequently, the watermark constructing and embedding processes of this approach provide more successful image tamper recovery than the methods based on average values of blocks. The proposed approach has been evaluated against various attacks and compared with state-of-the-art methods. Experimental results shows that the proposed approach can resist attacks up to 75%.

Imperceptibility and robustness are a part of trade-off components in image watermarking schemes and become one of the most studied in this field. Increasing imperceptibility usually will reduce the robustness, conversely, increasing the robustness may reduce the imperceptibility. This study is intended to overcome this challenge by proposing an image watermarking scheme using the Mojette transform to increase both imperceptibility and robustness. This transform is derived from the Radon transform which has some advantages in geometrical representations that have benefits for imperceptibility and robustness analyses. For evaluation purposes, the performance of the Mojette transform is evaluated on an image watermarking scheme in the singular value decomposition as this domain is stable in response to various image processing operations and also has a simple computation. The use of the Mojette transform in the proposed method involves both main image watermarking processes, which are watermark embedding and extraction. Towards achieving the trade-off of the watermarking requirement, the embedding watermark is designed at the maximum capacity. This means that the watermark is designed at the same size as the host image although it is embedded in various levels of scale factor. The watermarked image is then evaluated in the imperceptibility aspect, and the extracted watermark is evaluated in the robustness aspect after some attacks are applied to the watermarked images. Experimental results on some test images show that embedding the watermark at the maximum size using the proposed method kept producing a good perceptible watermarked image without reducing imperceptibility and robustness. For example, the imperceptibility of the watermarked image at 1% of the embedded scale factor could produce the visual quality at 45.2373 dB and the watermark could be extracted well although some attacks have occurred on the watermarked image. Almost all of the extracted watermarks after being distorted by nosing, filtering, compression, rotation, cropping, and flipping attacks have normalized correlation coefficients above 95%. Although the payload capacity of the watermark still needs further analysis, however, this study shows that the Mojette transform can contribute toward achieving the trade-off in the image watermarking requirements.

Abstract Steganography and secret sharing are schemes to increase the security of private information against attackers. Steganography emphasizes secrecy while secret sharing distributes the secret key in shares that are conditionally classified to reconstruct the original secret. This paper introduces a counting‐based secret sharing scheme that aims to reduce the computational complexity for longer keys, thereby providing a practical steganographic approach for efficient sharing. The scheme integrates counting‐based secret sharing with integer wavelet transform (IWT) and steganography. The subscriptions created using the Hamming code are embedded in the cover image. Using this method, IWT significantly reduces the occurrence of common rounding errors. As a result, secret key extraction becomes very accurate and eliminates the need to access the original images. This design, using secret sharing based on counting, not only has simplicity and efficiency, but also features such as flexibility, scalability, and lack of central authority. In addition, high‐quality steganography was obtained for keys with lengths of 64, 256, 512, 1024, and 3072, showing an average PSNR=80.11 in different color images. This outstanding performance makes it a highly efficient alternative to previous designs, representing a groundbreaking contribution with significant public interest in the field.

Abstract Blind watermark extraction in discrete cosine transform (DCT) domain has a wide application prospect as well as a challenging subject. The imperceptibility of watermark signal makes watermark extraction a weak signal reception issue in essence. For DCT coefficients of host image generally disobey Gaussian distribution, at which the performance of linear correlated reception is no longer optimal. Aiming at this, a novel blind watermark extraction scheme combining the uncorrelated reception with adaptive bistable stochastic resonance (ABSR) technique is proposed. First, by block DCT transformation for host image, an additive watermark embedding algorithm is introduced, in which the watermarked image can be converted to one dimensional time domain weak signal (binary watermark image) reception under additive Laplacian noise (selected DCT coefficients). On this basis, through the key technology research on quantitatively cooperative resonance relationship under Laplacian noise, the ABSR system can be implemented by bistable system parameters self‐adaptive adjustment, in which the ABSR system output signal will be enhanced rather than be weakened by random noise. Finally, the ABSR‐based watermark extraction scheme is investigated, and both the visual effect, bit error ratio performance and robustness of proposed scheme are testified to be superior to that of traditional uncorrelated extraction.

The piracy of digital products has become an urgent problem to be solved. Robust watermarking is a promising technique for copyright protection. To go against rapidly increasing attacks, many techniques have been proposed in the transform domain for ensuring the quality of water marked image, the robustness of extracted watermark, and execution time. Among these techniques, the LU decomposition is considered an out- standing transformation in terms of computation. However, some pixel matrices cannot be decomposed as the product of a lower triangular matrix and an upper triangular matrix, and embedding them into two elements reduces the quality of the watermark image. Therefore, this paper proposes a novel image watermarking scheme based on a LU block selection strategy and an improved embedding algorithm. First, a pixel block is only applied LU decomposition and embedded a watermark bit when all determinants of sub-matrices are non-zero. Second, an effective embedding formula is proposed where the watermark is embedded into one element of suitable blocks. This solution helps to limit the modification of pixel values and enhance the quality of the watermarked image. Third, to decrease the extraction time, a novel formula is built for calculating embedded elements instead of LU decomposition. The experimental results show that our proposed method has the better visual quality of watermarked images and can effectively extract the watermark under some attacks, such as blurring, sharpening, and salt & pepper noise. [ABSTRACT FROM AUTHOR]

Digital image watermarking provides security, copyright protection, and authenticity to multimedia content by embedding digital content like text, image, and video. In the modern digital age, watermarking of digital images is an essential aspect of providing authenticity to digital content. Digital image watermarking is also used for the authenticity of the medical image in telemedicine applications. In these applications, digital image watermarking provides security to various medical images like Computerized tomography (CT) scans, Magnetic resonance imaging (MRI) images, and X-radiation (X-ray) images. In the past decades, many intellectuals have been working in the field of image watermarking to provide various characteristics features to watermarking like sufficient embedding capacity, strong robustness, and better imperceptibility. This paper covers watermarking techniques based on Schur decomposition and various types of moments like Zernike moment, Fourier harmonic moments, polar harmonic moments, etc. A survey on watermarking techniques suitable for telemedicine applications which include various medical images like CT-scan, MRI image, and X-ray images, is also presented. Various performance measures proposed by different researchers are also discussed, and the suitability of these measures for watermarking schemes is analysed under various attacks. In this paper, novel classification of watermarking schemes, recent essential requirements for different categories of image watermarking applications are covered. A tabular comparison of various watermarking schemes based on different families of moments are presented and also a comparative analysis of outcomes of different categories of moment based watermarking schemes is included. Various challenges and opportunities are also included to make this review more comprehensive. [ABSTRACT FROM AUTHOR]

The field of digital image watermarking has collected considerable attention from researchers and scholars, that eventually presents interesting challenges and opportunities for technological advancements. We can successfully address issues with multimedia access control by utilizing technological advancements, such as transform domain techniques, steganography, multimedia synchronization, robust watermark extraction, and many. This can be used to enhance technology in many ways like intellectual property protection, data integrity and security, and others. Photographic Image Watermarking is the process of inserting a message as a watermark to host image in some multimedia format. We can try to restrict multimedia from unwanted access through the help of digital watermarking. A few elements such as capacity, security, imperceptibility, and robustness must be considered while creating an effective and productive digital watermarked image. This paper compares All Phase Discrete Cosine Biorthogonal Transform (APDCBT) and Discrete Cosine Transform (DCT) in the field of image authentication and Digital Watermarking. Our proposed system uses a PN – Sequence algorithm and a secret user key called K to generate random vectors for selected coefficients to increase the security and robustness. The above two algorithms are combined with commonly used algorithms like Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) for effective Digital Watermarking. For evaluating the imperceptibility of Watermarked Image, Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are taken into consideration. [ABSTRACT FROM AUTHOR]

With the extensive adoption of generative models across various domains, the protection of copyright for these models has become increasingly vital. Some researchers suggest embedding watermarks in the images generated by these models as a means of preserving IP rights. In this paper, we find that existing generative model watermarking introduces high-frequency artifacts in the high-frequency spectrum of the marked images, thereby compromising the imperceptibility and security of the generative model watermarking system. Given this revelation, we propose an innovative image watermarking technology that takes into account frequency-domain imperceptibility. Our approach abandons the conventional convolutional neural network (CNN) structure typically used as the watermarking embedding network in popular watermarking techniques. This helps the image watermarking system to avoid the inherent high-frequency artifacts commonly produced by CNNs. In addition, we design a frequency perturbation generation network to generate low-frequency perturbations. These perturbations are subsequently added as watermarks to the low-frequency components of the carrier image, thus minimizing the impact of the watermark embedding process on the high-frequency properties of the image. The results show that our proposed watermarking framework can effectively embed low-frequency perturbation watermarks into images and effectively suppress high-frequency artifacts in images, thus significantly improving the frequency-domain imperceptibility and security of the image watermarking system. The introduced approach enhances the average invisibility performance in the frequency domain by up to 24.9 % when contrasted with prior methods. Moreover, the method attains superior image quality (>50 dB) in the spatial domain, accompanied by a 100 % success rate in watermark extraction in the absence of attacks. This underscores its capability to uphold the efficacy of the protected network and preserve the integrity of the watermarking process. It always maintains excellent imperceptibility and robustness. Thus, the framework shows great potential as a state-of-the-art solution for protecting intellectual property. [ABSTRACT FROM AUTHOR]

Steganography and secret sharing are schemes to increase the security of private information against attackers. Steganography emphasizes secrecy while secret sharing distributes the secret key in shares that are conditionally classified to reconstruct the original secret. This paper introduces a counting‐based secret sharing scheme that aims to reduce the computational complexity for longer keys, thereby providing a practical steganographic approach for efficient sharing. The scheme integrates counting‐based secret sharing with integer wavelet transform (IWT) and steganography. The subscriptions created using the Hamming code are embedded in the cover image. Using this method, IWT significantly reduces the occurrence of common rounding errors. As a result, secret key extraction becomes very accurate and eliminates the need to access the original images. This design, using secret sharing based on counting, not only has simplicity and efficiency, but also features such as flexibility, scalability, and lack of central authority. In addition, high‐quality steganography was obtained for keys with lengths of 64, 256, 512, 1024, and 3072, showing an average PSNR=80.11 in different color images. This outstanding performance makes it a highly efficient alternative to previous designs, representing a groundbreaking contribution with significant public interest in the field. [ABSTRACT FROM AUTHOR]

In recent years, internet technology has grown in advance, and multimedia data-sharing growth rates have skyrocketed. As a result, protecting multimedia data in digital networks has become a significant problem. Multimedia data such as audio, text, video, and image are highly used as a data-sharing communication system which demands security, particularly in image and video. Digital watermarking is the one solution that has gained widespread recognition over the past two decades for data embedding in image and video, a key tactic in multimedia tamper detection and recovery. The review tells about the growth rate and data breaches on multimedia data across different applications, which raises the issue of multimedia security. Notably, social network platforms are highly targeted due to their rapid growth, which has created opportunities for data breaches and multimedia manipulation. Here, the forensic field comes into play, where some data-hiding strategies are used to look for evidence of tampering. Even though watermarking techniques can attain security in tamper detection, they face some issues and challenges across various applications. This motivated us to analyze the existing work carried out by data hiding watermarking techniques in the field of multimedia tamper detection in detail and the gap analyzed. Overall, dataset availability, watermarking performance quality metrics, and several image-processing attacks are all explicitly mentioned. This review paper discusses a comprehensive study of the existing system in the field of tamper detection (both in Image and Video) in detail. Also, the development of existing watermarking techniques, issues, and challenges are covered in detail in this paper. [ABSTRACT FROM AUTHOR]

Invisibility, robustness and payload are three indispensable and contradictory properties for any image watermarking systems. To achieve the tradeoff among the three requirements, statistical watermarking approaches have received increasing attention in recent years. But, most existing schemes often bear a number of drawbacks, in particular: (1) They mainly utilize transform coefficients, which are always fragile to some attacks, especially global geometric transforms, for watermark inserting and statistical modeling; (2) the adopted statistical models always cannot capture accurately both marginal distribution and various strong dependencies between coefficients; and (3) the used parameter estimation usually has high time complexity and poor computational accuracy. This has motivated us to introduce in this paper a novel statistical image watermarking in singular value decomposition (SVD)-undecimated discrete wavelet transform (UDWT) difference domain using vector Alpha Skew Gaussian (VB-ASG) distribution. We begin with a detailed study on the robustness and statistical characteristics of local SVD-UDWT difference coefficients of natural images. This study reveals the excellent robustness, highly non-Gaussian marginal statistics and strong dependencies of local SVD-UDWT difference coefficients. We also find that conditioned on their generalized neighborhoods, the local SVD-UDWT difference coefficients can be approximately modeled as vector Alpha Skew Gaussian (VB-ASG) variables. Meanwhile, model parameters can be estimated effectively by using approximate maximum likelihood estimation (AMLE) approach. Based on these findings, we model local SVD-UDWT difference coefficients using VB-ASG model that can capture marginal statistics and strong dependencies. Finally, we develop a new statistical image watermark decoder using the VB-ASG model and maximum likelihood (ML) decision rule. Our experimental evaluation results validate that our image watermarking leads to performance improvements comparable to several state-of-the-art statistical watermarking methods and some approaches based on convolutional neural networks. In particular, under the condition of the same watermarking capacity, the imperceptibility and robustness of this method show certain superiority compared with other algorithms. [ABSTRACT FROM AUTHOR]

Blind watermark extraction in discrete cosine transform (DCT) domain has a wide application prospect as well as a challenging subject. The imperceptibility of watermark signal makes watermark extraction a weak signal reception issue in essence. For DCT coefficients of host image generally disobey Gaussian distribution, at which the performance of linear correlated reception is no longer optimal. Aiming at this, a novel blind watermark extraction scheme combining the uncorrelated reception with adaptive bistable stochastic resonance (ABSR) technique is proposed. First, by block DCT transformation for host image, an additive watermark embedding algorithm is introduced, in which the watermarked image can be converted to one dimensional time domain weak signal (binary watermark image) reception under additive Laplacian noise (selected DCT coefficients). On this basis, through the key technology research on quantitatively cooperative resonance relationship under Laplacian noise, the ABSR system can be implemented by bistable system parameters self‐adaptive adjustment, in which the ABSR system output signal will be enhanced rather than be weakened by random noise. Finally, the ABSR‐based watermark extraction scheme is investigated, and both the visual effect, bit error ratio performance and robustness of proposed scheme are testified to be superior to that of traditional uncorrelated extraction. [ABSTRACT FROM AUTHOR]

In the field of image watermarking, imperceptibility, robustness, and watermarking capacity are key indicators for evaluating the performance of watermarking techniques. However, these three factors are often mutually constrained, posing a challenge in achieving a balance among them. To address this issue, this paper presents a novel image watermark detection algorithm based on local fast and accurate polar harmonic Fourier moments (FAPHFMs) and the BKF–Rayleigh distribution model. Firstly, the original image is chunked without overlapping, the entropy value is calculated, the high-entropy chunks are selected in descending order, and the local FAPHFM magnitudes are calculated. Secondly, the watermarking signals are embedded into the robust local FAPHFM magnitudes by the multiplication function, and then MMLE based on the RSS method is utilized to estimate the statistical parameters of the BKF–Rayleigh distribution model. Finally, a blind image watermarking detector is designed using BKF–Rayleigh distribution and LO decision criteria. In addition, we derive the closed expression of the watermark detector using the BKF–Rayleigh model. The experiments proved that the algorithm in this paper outperforms the existing methods in terms of performance, maintains robustness well under a large watermarking capacity, and has excellent imperceptibility at the same time. The algorithm maintains a well-balanced relationship between robustness, imperceptibility, and watermarking capacity. [ABSTRACT FROM AUTHOR]

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Invisibility, robustness and payload are three indispensable and contradictory properties for any image watermarking systems. Recently, to achieve the tradeoff among above three requirements, statistical watermarking schemes have gained a lot of attention. Most existing approaches, however, often bear a number of drawbacks, in particular: (i) They all employ directly transform coefficients, which are always fragile to some attacks, for watermark embedding and statistical modeling; (ii) The adopted model cannot capture accurately the statistical distributions of the transform coefficients; (iii) Most of them simply use the linear function for watermark embedding, which often either miss higher capacity or may cause visible distortions. This has motivated us to introduce in this paper a novel non-linear statistical image watermark detector based on undecimated discrete wavelet transform (UDWT)-polar complex exponential transform (PCET) magnitude and the exponentiated Cauchy-Rayleigh distribution. We begin with a detailed study on the robustness and statistical characteristics of local UDWT-PCET magnitudes of natural images. This study reveals the strong robustness and highly non-Gaussian marginal statistics of local UDWT-PCET magnitudes. We also find that, with a small number of parameters, the new exponentiated Cauchy-Rayleigh model can capture accurately the statistical properties of the robust UDWT-PCET magnitudes of the image. Meanwhile, the statistical model parameters can be computed effectively by using the genetic simulated annealing (GSA)-based maximum likelihood (ML) estimation. Based on these findings, we finally develop a new non-linear statistical image watermark detector using the exponentiated Cauchy-Rayleigh PDF and locally most powerful (LMP) decision rule. Also, we use the exponentiated Cauchy-Rayleigh statistical model to derive the closed-form expressions for the watermark detector. Extensive experimental results show the superiority of the proposed blind watermark detector over most of the state-of-the-art methods recently proposed in the literature. [ABSTRACT FROM AUTHOR]

In the field of image watermarking technology, it is very important to balance imperceptibility, robustness and embedding capacity. In order to solve this key problem, this paper proposes a new color image adaptive watermarking scheme based on discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD). In order to improve the security of the watermark, we use Lorenz hyperchaotic mapping to encrypt the watermark image. We adaptively determine the embedding factor by calculating the Bhattacharyya distance between the cover image and the watermark image, and combine the Alpha blending technique to embed the watermark image into the Y component of the YCbCr color space to enhance the imperceptibility of the algorithm. The experimental results show that the average PSNR of our scheme is 45.9382 dB, and the SSIM is 0.9986. Through a large number of experimental results and comparative analysis, it shows that the scheme has good imperceptibility and robustness, indicating that we have achieved a good balance between imperceptibility, robustness and embedding capacity.