Improvement of Detection Performance in DWT-Based Image Watermarking under Specified False Positive Probability

Image watermarking plays a vital role in providing protection from copyright violation. However, conventional watermarking techniques typically exhibit trade-offs in terms of image quality, robustness and capacity constrains. More often than not, these techniques optimize on one constrain while settling with the two other constraints. Therefore, in this paper, an enhanced saliency detection based watermarking method is proposed to simultaneously improve quality, capacity, and robustness. First, the enhanced structured matrix decomposition (E-SMD) is proposed to extract salient regions in the host image for producing a saliency mask. This mask is then applied to partition the foreground and background of the host and watermark images. Subsequently, the watermark (with the same dimension of host image) is shuffled using multiple Arnold and Logistic chaotic maps, and the resulting shuffled-watermark is embedded into the wavelet domain of the host image. Furthermore, a filtering operation is put forward to estimate the original host image so that the proposed watermarking method can also operate in blind mode. In the best case scenario, we could embed a 24-bit image as the watermark into another 24-bit image while maintaining an average SSIM of 0.9999 and achieving high robustness against commonly applied watermark attacks. Furthermore, as per our best knowledge, with high payload embedding, the significant improvement in these features (in terms of saliency, PSNR, SSIM, and NC) has not been achieved by the state-of-the-art methods. Thus, the outcomes of this research realizes a trade-off independent image watermarking method, which is a first of its kind in this domain.

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

A gray-level intensity image can be employed as a host image for hiding a watermark image to protect information security. Past research works demonstrate that a gray-level hidden image can be embedded into the host image by a digital phase-only holography method. However, the fidelity of retrieved watermark image from the host image is not very satisfactory and the host image quality is degraded due to the insertion of external data bits, especially when observers focus on the saliency regions in the host image. To address this problem, we propose a steganography method based on digital holography and the saliency map of the host image. First, we calculate the hidden capacity (number of bits to be replaced) for each host image pixel based on the weighted sum of pixel intensity and saliency value. Next, a multilevel phase-only digital hologram of the watermark image will be calculated by the Gerchberg–Saxton method under the constraint of the hidden capacity of host image. Finally, we embedded the multilevel phase-only digital hologram into the host image by replacing a corresponding number of bits in each pixel. In this way, the host image can preserve good image fidelity for its saliency regions even if we hide a large amount of digital hologram data into the host image. The experimental results show that the quality of retrieved watermark image from the host image and the quality of saliency regions in the watermarked host image, in our proposed scheme, are superior to the state-of-the-art works reported.

We propose in this paper a discrete wavelet transform (DWT) based digital image watermarking technique. For embedding process, we consider the watermark signal as a binary sequence which is embedded to the high (HL and HH) frequency band of the blue channel. For detecting process, the correlation between the high frequency band DWT coefficients of the watermarked image and the watermark signal is compared with the predefined threshold to determine whether the watermark is present or not. The experimental results show that the method is comparatively robust to several attacks such as rotation, scaling, JPEG compression, cropping, and multiple watermarking.

Digital watermarking is an emerging technique to protect data security and intellectual property right. Identification or verification of watermarking patterns can be achieved by detecting watermarks in received signals. However, one of the biggest challenges in watermarking detection is that the strengths of the watermark signals will change after being distorted by an attacker in a watermarking channel. Meanwhile, the embedding strengths may be adapted to the original signals, which are unknown at the receiver end. Further, the original signals are often highly non-Gaussian. Although some work has been done on optimum detection of watermarks, the uncertainty of watermark signal strengths and real statistical behavior of multimedia contents have not been taken into account simultaneously. Much more study is needed to enhance the performance of watermarking systems. Since multiplicative watermarks are robust and well suited for copyright protection, this paper presents our investigation on robust optimum detection of multiplicative watermarks. For sub-band transformed domains such as the discrete cosine transform (DCT), discrete wavelet transform (DWT), and pyramid transform, a class of generalized correlators is constructed based on the generalized Gaussian distributions. Thresholding methods to achieve a given false alarm rate, and the performance analyses are provided. The square-root detector is designed and demonstrated to have near performance for a large set of natural images and can be employed as a universally optimal detector or decoder for images and video. The locally most powerful detection method is then extended to DFT domain multiplicative watermarking, with the magnitudes of coefficients modeled by the Weibull distributions. Another class of detectors is built based on this statistical modeling. The robust optimum detection of multiplicative watermarks can be applied to copyright notification, enforcement, and broadcast monitoring. We have applied the robust optimum watermarking detection to combined audio and video watermarking.

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.

Fluorescence imaging and counting of single molecules adsorbed or bound to surfaces are being employed in a number of quantitative analysis applications. Reliable molecular counts with knowledge of counting uncertainties, both false-positive and false-negative probabilities, are critical to these applications. By counting stationary single molecules on a surface, spatial criteria may be applied to the image analysis to improve confidence in detection, which is especially critical when detecting single fluorescent labels. In this work, we describe a simple approach to incorporating spatial criteria for counting single molecules by using an intensity threshold to locate regions with multiple, adjacent intense pixels, where the size of these regions is guided by the point-spread function of the microscope. By requiring multiple, spatially correlated bright pixels, false-positive events resulting from random samples of background noise are minimized. The reliability of detection is established by quantitative knowledge of the distributions of background and signals. By measuring and modeling both the background and single-molecule intensity distributions, false-positive and false-negative detection probabilities are estimated for arbitrary threshold parameters by using combinatorial statistics. From this theory, detection parameters can be optimized to minimize false-positive and false-negative probabilities, which can be calculated explicitly. For detection of single rhodamine 6G molecules at a threshold set at 2.5 times the standard deviation above background, the false-negative probability was only 1.5%, determined from distributions of single-molecule intensities on well-populated surfaces, and the false-positive probability from background noise was 2.8 spots per 50 x 50 microm image. The false-positive events compare favorably with theoretical probabilities calculated using combinatorial statistical analysis and simulated false-positive events counted in images of random noise.

This paper investigates the scope of wavelets for performance improvement in spread spectrum image watermarking. Performance of a digital image watermarking algorithm, in general, is determined by the visual invisibility of the hidden data (imperceptibility), reliability in the detection of the hidden information after various common and deliberate signal processing operations (robustness) applied on the watermarked signals and the amount of data to be hidden (payload) without affecting the imperceptibility and robustness properties. In this paper, we propose a few spread spectrum (SS) image watermarking schemes using discrete wavelet transform (DWT), biorthogonal DWT and M-band wavelets coupled with various modulation, multiplexing and signaling techniques. The performance of the watermarking methods are also reported along with the relative merits and demerits.

A novel DCT domain color digital watermarking scheme based on chaotic maps is proposed, and the host image is color RGB image. The color space of the color host image is first converted from RGB to YIQ. In order to resist JPEG compression, all three watermark RGB channel signals are buried to Y component of the YIQ color space host images. In the proposed method, the image watermark is embedded into low-band DCT coefficients with different strength according to the characteristics of human vision system. The watermark signal and the embedding position of the host image are encrypted respectively by the unified chaotic map and multilayer Arnold cat map, and compared with the general Arnold cat map, the key space is highly increased. The simulation results show that the proposed scheme possesses the invisibility and the robustness to common image processing attacks, such as noise addition, JPEG compression, image rotation, cutting and so on.

An image watermarking method using Discrete Wavelet Transform (DWT) and Genetic Algorithm (GA) is presented for applications like content authentication and copyright protection. This method is robust to various image attacks. For watermark detection/extraction, the cover image is not essential. Gray scale images of size 512 × 512 as cover image and binary images of size 64 × 64 as watermark are used in the simulation of the proposed method. Watermark embedding is done in the DWT domain. 3rd and 2nd level detail sub-band coefficients are selected for further processing. Selected coefficients are arranged in different blocks. The size of the block and the number blocks depends on the size of the watermark. One watermark bit is embedded in each block. Then, inverse DWT operation is performed to get the required watermarked image. This watermarked image is used for transmission and distribution purposes. In case of any dispute over the ownership, the hidden watermark is decoded to solve the problem. Threshold-based method is used for watermark extraction. Control parameters are identified and optimized based on GA for targeted performance in terms of PSNR and NCC. Performance comparison is done with the existing works and substantial improvement is witnessed.

The improvements in ship detection performance that can be obtained by using polarimetric synthetic aperture radar (SAR) data as compared to single-channel SAR data are investigated. Statistical decision theory is used to define decision variables that quantify the trade-off between the probability of missed detection and the probability of false alarm; performance is characterized by calculating receiver operating characteristics from single-channel and polarimetric SAR data by using likelihood ratio tests with the Neyman-Pearson criterion. It is shown that improvements in detection performance can be obtained with polarimetric SAR data as compared to single channel SAR data. We evaluate the results of these algorithms applied to single channel, dual channel amplitude only, dual channel with amplitude and phase, and fully polarimetric SAR data of known ships. In this way, the relative improvement in ship detection performance that is realized by introducing polarimetric information is quantified

In this paper, an efficiently DWT-based watermarking technique is proposed to embed gray-scale logos as watermark in images to attest the owner identification and discourage the unauthorized copying. The method transforms both the host image and watermark into the discrete wavelet domain where their coefficients are fused adaptively based on Human Visual System (HVS) model to hide a higher energy hidden watermark in salient image components. The method repeatedly merges the watermark coefficients at the various resolution levels of the host image which provides simultaneous spatial localization and frequency spread of the watermark to provide robustness against different attacks. From the simulation results it can be observed that proposed method is robust to wide variety of attacks, such as image compression, linear or non-linear filtering, noise addition, image resizing, cropping, and image enhancement, etc. Keywords—Digital watermark, discrete wavelet transform, HVS characteristics,

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.

An Invisible Logo Watermarking Using Arnold Transform

In this paper, a new robust and secure video watermarking scheme based on discrete Wavelet Transform (DWT), singular value decomposition (SVD), and Laplacian pyramid is proposed for copyright protection applications. The main contributions of this work are: 1) Increasing watermark robustness towards common signal processing attacks by separating the watermark image into a high-frequency image and a low-frequency image using laplacian pyramid. Then, the singular values of each of the low-frequency watermark image and the high-frequency watermark image are hidden in two different DWT subbands of the original video frame. Separating the watermark and hiding its two parts in two different subbands of the DWT of the video frame makes it robust towards noise, filtering, and compression attacks. 2) Improving the quality of the extracted watermarks via correcting the received watermarked videos using SURF points when those videos are geometrically attacked, mainly by rotation, scaling, and shear attacks. 3) Increasing security and avoiding false positive problems (FPP) associated with SVD by using perceptual image hashing in the proposed scheme. Through experimental results and comparisons to other techniques, the proposed scheme has shown very high imperceptibility for the tested watermarked videos in terms of peak signal to noise ratio (PSNR). Also, the proposed scheme has demonstrated high watermark robustness towards various types of attacks, and an improvement in the quality of the extracted watermarks from 4 to 20 dB compared to other techniques.