Host Image Research Articles

Characterization of JWST NIRCam PSFs and Implications for AGN+host Image Decomposition

We present a detailed analysis of the point-spread function (PSF) of JWST NIRCam imaging in eight filters: F070W, F115W, F150W, F200W, F277W, F356W, F444W, and F480M, using publicly available data. Spatial variations in the PSF FWHM generally decrease with wavelength: the maximum and rms fractional variations are ∼20% and 5% in F070W, reduced to ∼3% and 0.6% in F444W. We compare three commonly used methods (SWarp, photutils, and PSFEx) to construct model PSFs and conclude that PSFEx delivers the best performance. Using simulated images of broad-line active galactic nuclei (AGNs), we evaluate the impact of PSF mismatches on the recoverability of host galaxy properties. Host fluxes are generally overestimated when adopting mismatched PSF models, with larger overestimation for more AGN-dominated systems. Broader PSFs tend to produce less concentrated hosts, while narrower PSFs tend to produce more concentrated and compact hosts. Systematic uncertainties in host measurements from PSF and model mismatches are generally larger than the formal fitting uncertainties for high signal-to-noise ratio data. Image decomposition can also lead to an artificial offset between the AGN and host centroids, which is common (e.g., >1σ [3σ] detection in ∼80% [∼20%–30%] of systems), and scales with the mean host surface brightness (SB). Near the SB limit, this artificial offset can reach as large as ∼80%, 26%, and 7% of R e in systems with R e = 0.″12, 0.″48, and 1.″92, respectively. We demonstrate our PSF construction and image decomposition methods with an example broad-line quasar at z = 1.646 in the CEERS field.

Active Galactic Nuclei and Host Galaxies in COSMOS-Web. I. NIRCam Images, Point-spread-function Models and Initial Results on X-Ray-selected Broad-line AGNs at 0.35 ≲ z ≲ 3.5

We present detailed and comprehensive data reduction and point-spread-function (PSF) model construction for all public JWST NIRCam imaging data from the COSMOS-Web treasury program (up to 2023 June, totaling 0.28 deg2). We show that the NIRCam PSF has significant short-timescale temporal variations and random spatial variations in all four filters (F115W, F150W, F277W, and F444W). Combining NIRCam with archival Hubble Space Telescope imaging, we perform multiwavelength active galactic nucleus (AGN)+host image decomposition to study the properties of 143 X-ray-selected (L bol = 1043.6–47.2 erg s−1) broad-line AGNs at 0.35 ≲ z ≲ 3.5. Leveraging the superb resolution, wavelength coverage, and sensitivity of NIRCam, we successfully detect host stellar emission after decomposing the central AGN point source in 142 objects. ∼2/3 AGNs are in star-forming galaxies based on the UVJ diagram, suggesting that there is no instantaneous negative AGN feedback. X-ray-selected broad-line AGN hosts follow a similar stellar mass–size relation as inactive galaxies, albeit with slightly smaller galaxy sizes. We find that although major mergers are rare (∼7%–22%) among the sample, more subtle nonaxisymmetric features from stellar bars, spiral arms, and minor mergers are ubiquitous, highlighting the importance of secular processes and minor mergers in triggering AGN activity. For a subsample of 30 AGNs at 1 < z < 2.5 with black hole mass measurements from single epoch spectra, they follow a similar black hole mass-stellar mass relation as local inactive early-type galaxies but reside preferentially near the upper envelope of nearby AGNs. We caution that selection biases and the intrinsic differences of AGN populations at different redshifts may significantly affect their location on the black hole mass-stellar mass plane.

Image Watermarking Using Discrete Wavelet Transform and Singular Value Decomposition for Enhanced Imperceptibility and Robustness

Digital multimedia elements such as text, image, audio, and video can be easily manipulated because of the rapid rise of multimedia technology, making data protection a prime concern. Hence, copyright protection, content authentication, and integrity verification are today’s new challenging issues. To address these issues, digital image watermarking techniques have been proposed by several researchers. Image watermarking can be conducted through several transformations, such as discrete wavelet transform (DWT), singular value decomposition (SVD), orthogonal matrix Q and upper triangular matrix R (QR) decomposition, and non-subsampled contourlet transform (NSCT). However, a single transformation cannot simultaneously satisfy all the design requirements of image watermarking, which makes a platform to design a hybrid invisible image watermarking technique in this work. The proposed work combines four-level (4L) DWT and two-level (2L) SVD. The Arnold map initially encrypts the watermark image, and 2L SVD is applied to it to extract the s components of the watermark image. A 4L DWT is applied to the host image to extract the LL sub-band, and then 2L SVD is applied to extract s components that are embedded into the host image to generate the watermarked image. The dynamic-sized watermark maintains a balanced visual impact and non-blind watermarking preserves the quality and integrity of the host image. We have evaluated the performance after applying several intentional and unintentional attacks and found high imperceptibility and improved robustness with enhanced security to the system than existing state-of-the-art methods.

Optical color fragile watermark based on pixel-free expansion visual cryptography

In recent years, with the continuous development of computer technology, it has brought convenience to people to obtain image information. However, at the same time, the falsification and theft of image information have also emerged, so information security has received increasing attention. When images are used for medicine, military, court, and other purposes, it is necessary to ensure the authenticity and integrity of the image content. Fragile watermarks are used to verify the authenticity and integrity of image content due to their sensitivity to tampering. The watermark information is embedded in the image and integrated with the image. When it is necessary to detect the authenticity and integrity of image information, the extracted watermark can be used to determine whether the image is reliable and complete. Therefore, we propose an optical color fragile watermarking system based on pixel-free expansion visual cryptography. On the one hand, encoding watermark images by using pixel-free expansion visual cryptography avoids pixel expansion issues caused by visual cryptography, allowing for the selection of color host images with the same pixel size as the watermark image in the future, greatly reducing the network bandwidth and storage space occupied during transmission. On the other hand, phase recovery algorithm is used to process the encoded watermark image to obtain phase information for embedding into the host image, further improving the security of the watermark image in an optical way. The feasibility and imperceptibility of the proposed optical color fragile watermark are verified through computer simulation, and its good fragility is verified through a series of simulation attack experiments. It can sensitively detect image tampering in the face of common attacks such as noise pollution, rotation, motion blur processing, filtering, etc.

Concealed Chosen Plaintext Attack on Multiple S-boxes Based Image Encryption

Chosen plaintext attacks (CPA) pose a significant security risk to encryption algorithms. However, it can be difficult to perform such an attack without direct access to the encryption process. This paper introduces a new cryptoanalysis method that uses hidden CPA to analyze image encryption schemes based on substitution boxes (S-boxes) Unlike traditional CPA methods, the proposed algorithm does not require that they can directly into the encryption process. Instead, a hidden attack vector is embedded in the natural host image to reduce the risk of attack detection. By asking the owner of the encryption algorithm to encrypt this encryption image and provide a cipher image, the input vector can be compared with its encrypted counterpart This can have an effective S-box and break encryption the algorithm, which does not interact directly with the encryption process. Experimental results demonstrate that the proposed method can completely recover cipher images in cascading S-box encryption schemes, regardless of the number of S-boxes used. Additionally, it conceals the CPA vector within the host image imperceptibly, achieving a high PSNR of 49.47 dB, indicating minimal visual distortion. Furthermore, our CPA significantly outperforms existing techniques in speed, recovering a grayscale image in just 1.2 seconds. This method provides a simple yet effective cryptanalysis tool to evaluate the security of such image encryption schemes against CPAs.

Robust Image Watermarking using DWT, DCT, and PSO with CNN-Based Attack Evaluation

Digital Content Protection is one of the most significant research areas that lies at the intersection of cyber-security and multimedia processing. Protect multimedia content from copyright violation, unauthorized use, replication, and online content theft is needed. Digital Image Watermarking is utilized to preserve the copyright of different digital images from forgery. Various techniques had been developed in this regard with two main issues, the method robustness and the resistance against various types of attacks like, Salt and Pepper noise, filtering and blurring. Current Digital watermarking techniques may reduce the quality of the original digital media content if it is not robust. The purpose of this research is to create a robust image watermarking technique against different attack types such as salt and pepper noise and Gaussian noise, ensuring the image content is protected. Specifically, this study proposed a new mechanism for Image watermarking based on combining Discrete Wavelet Transform (DWT), and Discrete Cosine Transform (DCT). Additionally, Particle Swarm Optimization (PSO) was applied to perform the optimization for both the embedding and extraction processes. At the final stage we assess the proposed approach against some types of attacks such as Additive White Gaussian Noise (AWGN). The Denoising Convolutional Neural Network, (DnCNN) was used to evaluate the mechanism against AWGN. For testing, we utilized measures such as Peak Signal-to-Noise Ratio (PSNR) and Normalized Correlation Coefficient (NCC). The experimental results of implementing our proposed method for embedding and extracting watermarks across various host image sizes were encouraging, achieving a PSNR ratio of 0.998 and an NCC of 1 in the absence of attacks. Additionally, our evaluation revealed that a specific type of denoising attack, while damaging the watermark (though not completely), actually improved the image quality. It is also important to highlight that our findings surpassed those reported in existing literature, with the PSNR and NCC values serving as evidence of this superior performance.

Shingle cell IV$$ IV $$ characterization based on spatially resolved host cell measurements

AbstractEach solar cell is characterized at the end‐of‐line using current‐voltage ( ) measurements, except shingle cells, due to multiplied measurement efforts. Therefore, the respective host cell quality is adopted for all resulting shingles, which is sufficient for samples with laterally homogeneous quality. Yet, for heterogeneous defect distributions, this procedure leads to (i) loss of high‐quality shingles due to defects on neighboring host cell parts, (ii) increased mismatch losses due to inaccurate binning, and (iii) lack of shingle‐precise characterization. In spatially resolved host measurements, such as electroluminescence images, all shingles are visible along with their properties. Within a comprehensive experiment, 840 hosts and their resulting shingles are measured. Thereafter, a deep learning model has been designed and optimized which processes host images and determines parameters like efficiency or fill factor, curves, and binning classes for each shingle cell. The efficiency can be determined with an error of enabling a improvement in correct assignment of shingles to bin classes compared with industry standard. This results in lower mismatch losses and higher output power on module level as demonstrated within simulations. Also, curves of defective and defect‐free shingle cells can be derived with good agreement to actual shingle measurements.

Performance Analysis of The Last Significant Bit (LSB) Method in Steganography for Data Hiding in Image Data

Technology as a means of conveying information can have significant implications for the security and confidentiality of data and information content. When a sender wishes to convey a message to someone and does not want the message to be easily visible, the concealment of this message becomes crucial for the sender. One commonly used method for data concealment is the Least Significant Bit (LSB) method in steganography. The LSB method is preferred for its simplicity, fast process, and greater capacity. Messages are embedded by replacing the least significant bit in the host image with the message bits, with the rule that the number of message bits does not exceed the number of bits in the host image. Based on research findings, the results of steganography are difficult to distinguish from the original content through visual observation. Therefore, it can be concluded that the steganography method is highly effective for concealing a message.

AdvEWM: Generating image adversarial examples by embedding digital watermarks

With the increasing attention to deep neural network (DNN) models, attacks are also upcoming for such models. For example, an attacker may carefully construct images in specific ways (also referred to as adversarial examples) aiming to mislead the DNN models to output incorrect classification results. Similarly, many efforts are proposed to detect and mitigate adversarial examples, usually for certain dedicated attacks. In this paper, we propose a novel framework called AdvEWM based on embedding digital watermark to generate image adversarial examples for fooling DNN models. Specifically, partial main features of the watermark image are embedded into the host image almost invisibly, aiming to tamper with and damage the recognition capabilities of the DNN models. We devise an efficient mechanism to select host images and watermark images and utilize the improved discrete wavelet transform (DWT) based Patchwork watermarking algorithm with a set of valid hyperparameters to embed digital watermarks from the watermark image dataset into original images for generating image adversarial examples. The experimental results illustrate that the attack success rate on common DNN models can reach an average of 95.47% on the CIFAR-10 dataset and the highest at 98.71%. Besides, our scheme is able to generate a large number of adversarial examples efficiently, concretely, an average of 1.17 s for completing the attacks on each image on the CIFAR-10 dataset. In addition, we design a baseline experiment using the watermark images generated by Gaussian noise as the watermark image dataset that also displays the effectiveness of our scheme. Similarly, we also propose the modified discrete cosine transform (DCT) based Patchwork watermarking algorithm. To ensure repeatability and reproducibility, the source code is available on GitHub.

A Hybrid DWT-SVD Based Adaptive Image Watermarking Scheme

In the digital age, protecting the ownership and data veracity of digital documents is a major challenge. To address the issues concerning copyright protection and data verification of digital media, digital watermarking has emerged as a solution. In this paper, we aspire to make a modest contribution to this emerging and exciting field by presenting our proposed adaptive hybrid image watermarking approach that combines Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). Our method involves applying DWT to both the host image and watermark, followed by singular decomposition using SVD on the Low-Low (LL) component of both images. Now modify the singular values of the host image by the singular values of the watermark, and then inverse SVD is applied, followed by inverse DWT, to obtain the watermarked image. After that, the reverse process is applied to obtain the watermark image. Finally, we evaluate our approach’s performance by measuring the Peak Signal-to-Noise Ratio (PSNR) between the original and watermarked image as well as the Normalized Cross-Correlation (NCC) between the original and extracted watermark. Simulation results indicate that the proposed method is rich in terms of robustness, imperceptibility and capacity than the previously presented schemes.

Watermarking using DCT and DWT on Pneumonia images

Watermarking is a branch of the data hiding technique. Watermarking is a technique used to insert a copyright label on an image, so that the copyright of the image can be protected. Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are techniques that can be used to watermark. In this study, the Discrete Cosine Transform and Discrete Wavelet Transform methods will be used to watermark images to 5 different host images. In the tests carried out, watermarking techniques will be compared using DCT, DWT, DCT-DWT combination and DWT-DCT combination. The results obtained in this study were the highest PSNR value obtained at 41.931, the highest SSIM obtained 0.99515, the highest entropy was also obtained at 7.4186, The best UACI value is 0.0071158 and the best NCPR value is obtained at 93.9068% then, for the best CC value is obtained at 0.99953. As well as the NCC value, the value obtained is the same all in each test, namely with a value of 1.

Blind watermarking scheme for medical and non-medical images copyright protection using the QZ algorithm

The widely used watermarking technique is to hide the watermark information through adding process, which means the watermark is added with the host image to realize embedding. The constraints of these addition-based watermarking systems mainly are non-blind, they are vulnerable to forgery attacks and have the false-positive problem. To solve these problems, a novel blind watermarking scheme based on the QZ algorithm for medical and normal images is first presented in this paper. In the presented scheme, we take the watermark and the host image as two inputs of the QZ algorithm to realize embedding, rather than the adding process. The outputs of the QZ algorithm include four parts: two upper quasitriangular matrices and two unitary matrices. Then the three parts of the outputs are synthesized by the vector synthesis and inverse discrete wavelet transform-singular value decomposition (DWT-SVD) to obtain the watermarked host image. Due to the characteristics of the QZ algorithm, our scheme is blind. The performance is tested and compared by applying our scheme to both medical and non-medical images. The experimental results show that our scheme is robust against various image-processing attacks, forgery attacks, and false-positive problem. And from the comparison results, the proposed scheme outperforms the existing addition-based schemes in terms of robustness against the Median filter, Low-pass filter, Gaussian blur attacks, and forgery attacks, while maintaining good invisibility.

Two-dimensional histogram-based reversible contrast enhancement using bi-histogram equalization

In recent years, the reversible data hiding with contrast enhancement (RDH-CE) technique has been proposed and developed significantly; it can perform CE for images and restore the host image losslessly. To improve the embedding rate, CE capability, and visual quality, this paper proposes a reversible CE scheme based on 2D histogram equalization, which maintains the image quality and low brightness distortion with fewer iterations and has a high embedding rate and CE capability. Specifically, to prevent image brightness distortion, the 2D histogram is separated to obtain two 2D sub-histograms before histogram shifting. The dimension with the highest embedding capacity is dynamically selected for the embedding operation in each iteration, and the two-sided histogram equalization and information embedding are performed on the separated sub-histograms. The proposed method is evaluated on two datasets, and the results show that the method has high embedding and CE capabilities with low iteration and good visualization.

A secure and robust color image watermarking method using SVD and GAT in the multiresolution DCHWT domain

This paper introduces an innovative and robust watermarking technique for safeguarding the copyright of color digital images. The method operates within the domain of SVD-based multiresolution discrete cosine harmonic wavelet transforms. In this approach, the pre-processing phase employs successive generalized Arnold transforms to encrypt the RGB watermark layers, significantly enhancing the security of the watermarking algorithm. Subsequently, the blue layer of the host image undergoes R-level 2D-DCHWT processing. The encrypted watermark is embedded by altering the singular values of the host image's approximation coefficients. Additionally, a reliable extraction algorithm is devised to recover the watermark from potentially compromised watermarked images without requiring access to the original image. Through extensive experiments and comparisons with other relevant watermarking algorithms, the findings demonstrate that this scheme effectively embeds a color digital image watermark into the host image. This not only ensures high levels of invisibility but also establishes robustness, making it well-suited for the protection of digital image copyrights.

Optimal location using genetic algorithms for chaotic image steganography technique based on discrete framelet transform

The development of network technology and its use have led society into the internet world and communication through digital data. The ease of access to digital resources and the possibility of unauthorized copies and distribution of them have gave rise to the significant challenge of protecting the ownership of these data. In this context, steganography is cited as a possible solution to some of these problems. Steganography can be understood as the practice of hiding secret information within another object, as for instance a text, image or video, such that the presence of this hidden information is not evident and it can be extracted if necessary. In this paper we provide an image steganography algorithm in order to insert a grayscale secret image into a RGB color cover image. This algorithm is based on a general hybrid chaos map and a 3D shift function applied to the pixels of a color image. In order to select suitable hiding places in the host image, we develop a genetic algorithm with permutation encoding aiming to optimize this task. We demonstrate empirically the effectiveness of the proposed method from various perspectives, including transparency, security, and resistance.

Quality guided reversible data hiding with contrast enhancement

Reversible data hiding with contrast enhancement (RDH-CE) enables contrast enhancement of the image and lossless recovery of host image after embedded data extraction. Although the current RDH-CE methods are effective in enhancing carrier images and ensuring reversibility, image quality control is still lacking, which may lead to poor image visualization. In more serious situations, the image detail information may be lost. The peak pair selection mechanism plays an extremely crucial role in image quality enhancement; however, existing work often neglects this. In this paper, we propose an RDH-CE algorithm that pursues high image quality maintenance, aiming to maintain image quality by guiding and controlling the selection of peaks and the direction of histogram shift through quality metrics. Specifically, instead of simply selecting only one pair of peaks at each peak selection stage, our algorithm selects several pairs of peaks that meet the requirements as candidate peak pairs. It then first performs simulated histogram equalization on these candidate peaks, followed by analyzing the situation of the quality metrics generated by each pair of peaks accordingly, and then selects the optimal peaks for the current iteration based on the performance of each pair of candidate peaks to be used in the equalization process. Our selection mechanism also dynamically changes the peak selection strategy based on before-and-after changes in the actual metrics, which can better ensure image quality stability over the iterations. Under the evaluations of a series of image quality metrics, the proposed method can still maintain high quality and visual effect under high iteration and has strong stability for image quality control, thus demonstrating the effectiveness and superiority of the proposed method.

Optical encoding and hiding scheme for a double image based on chaotic fingerprint phase masks and phase-shifting digital holography.

This paper proposes a novel, to the best of our knowledge, double-image hiding scheme based on the chaotic fingerprint phase masks (CFPMs) and three-step phase-shifting digital holography (PSDH). First, the two images to be hidden are encoded into a complex amplitude image, and then with the help of the CFPM located in the Fresnel transform (FrT) domain and the three-step PSDH, the complex amplitude image can be encoded into three noise-like interference holograms. Finally, the three noise-like interference holograms are hidden into the texture part of the host image by the discrete wavelet transform based fusion approach and variational image decomposition technique. This scheme can simultaneously hide two images into one host image, and the invisibility and robustness of the hiding scheme can be well balanced by embedding the secret image in the texture of the host image. Additionally, the introduction of a biometric feature increases the association of the key and the authorized user, and the parameters of the chaotic map and FrT can also provide additional security tothe proposed scheme. We have verified the scheme's feasibility, security, and robustness through extensive experiments.

Visually meaningful image encryption based on 2D compressive sensing and dynamic embedding

Conventional image encryption methods typically encrypt images into noise-like images, which can provide a degree of security for the image, but the non-visually meaningful appearance can easily trigger the suspicion of hackers. To address this issue, visually meaningful image encryption (VMIE) which can produce a visually meaningful cipher image is developed. Nevertheless, current VMIE algorithms still exhibit certain limitations in embedding capacity and the quality of the cipher images. To solve the above issues, a novel VMIE algorithm based on the improved sine-tangent (IST) map, two-dimensional compressive sensing (2DCS), and dynamic embedding is proposed in this paper. First, to enhance the embedding capacity of the proposed algorithm, 2DCS is applied to the plain image to obtain the compressed data, wherein the measurement matrix is generated by an IST map to reduce the use of storage space and optimized by the simulated annealing algorithm to reduce the distortion of the decrypted image. Then, scrambling and diffusion operations are applied to the compressed image to disguise its statistical properties. Finally, to adapt to plain images with different texture features and enhance the quality of VMIE, a dynamic embedding algorithm is devised to embed the encrypted image into the host image. Simulation results and robustness analysis confirm that our scheme is feasible. Additionally, the proposed algorithm shows the superior visual quality and reconstruction quality compared to existing related schemes.

A robust watermarking approach against high‐density salt and pepper noise (RWSPN) to enhance medical image security

AbstractThis paper proposes a robust watermarking method against high‐density salt and pepper noise attacks. Automatic region of interest (ROI) detection, embedding encoded data, removing different densities of noise, data extraction by omitting, and labeling the noisy pixels of Region of Non‐Interest (RONI), and decoding the extracted data using ROI pixel information as a key, are various steps of the presented scheme. The automatic ROI detection method separates the RONI from ROI with four vertices of the smallest rectangle, for the embedding process. The encoded watermark data is embedded into the least significant bits of RONI in four neighbour pixels. Adaptive Removal of high‐density Salt and pepper Noise method can enhance image quality and reduce the effect of salt and pepper noise attacks. The embedded information is preserved from destruction if the host image is impaired through the power of robustness. The best results are obtained through the action of extracting the watermark from RONI pixels, utilizing the same ROI detection method. Omitting and labeling the noisy pixels of the RONI will ensure healthy extracted watermark data, leading to decreased Bit Error Rate (BER) values. Finally, these data are interpreted using the key of ROI pixels, and the watermark data is decoded and retrieved. Due to salt and pepper noise obliterating pixel bits and their corresponding transform coefficients in the transform domain, the spatial domain is employed to enhance robustness against such attacks. The results show the high performance of the presented scheme. The average BER value for five MRI databases in a 97% salt and pepper noise attack is 38.6.

Adaptive bistable stochastic resonance based blind watermark extraction in discrete cosine transform domain

AbstractBlind 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.