Article
Optics
Muhammad Rafiq Abuturab, Ayman Alfalou
Summary: A new method for multiple color image fusion, compression, and encryption using compressive sensing, chaotic-biometric keys, and optical fractional Fourier transform is proposed in this paper. The proposed cryptosystem has advantages of reduced data storage, uniqueness of biometric keys in CBPMs, very sensitive orders of the FrFT, and a single-channel hybrid optoelectronic setup.
OPTICS AND LASER TECHNOLOGY
(2022)
Article
Mathematics, Interdisciplinary Applications
Guodong Ye, Huishan Wu, Min Liu, Xiaoling Huang
Summary: In this paper, a reversible image-hiding algorithm based on a novel chaotic system is proposed using compressive sensing and singular value sampling techniques. The algorithm extracts the plain messages from the secret image and encrypts them using the RSA algorithm. It then transforms the messages into initial keys, which are used to produce a random key stream. The secret image is scrambled and partitioned, and the non-zero blocks are sampled using CS. The new sampling values are embedded into the wavelet coefficients to obtain a new carrier image containing the secrets.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Computer Science, Information Systems
Kuiyuan Zhang, Zhongyun Hua, Yuanman Li, Yongyong Chen, Yicong Zhou
Summary: This paper proposes an adaptive multi-scale image compressive sensing network in the wavelet domain called AMS-Net, which fully exploits the different importance of image low-frequency and high-frequency components, resulting in improved reconstruction quality.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Engineering, Electrical & Electronic
Liya Zhu, Donghua Jiang, Jiangqun Ni, Xingyuan Wang, Xianwei Rong, Musheer Ahmad, Yingpin Chen
Summary: In this paper, a stable image visually secure encryption algorithm is presented, which uses 2D discrete fractional-order chaotic map (FOCM), Bayesian compressive sensing (BCS), and discrete V transform (DVT) to protect the digital image information during public channel transmission and localized storage.
Article
Engineering, Electrical & Electronic
Zhongyun Hua, Kuiyuan Zhang, Yuanman Li, Yicong Zhou
Summary: In this work, a new visually secure image encryption scheme is proposed to improve the quality of reconstructed image, processing efficiency, and security level through adaptive-thresholding sparsification, parallel CS technique, and matrix encoding strategy. The proposed scheme shows higher efficiency and quality in simulations and comparisons.
Article
Computer Science, Information Systems
Dolendro Singh Laiphrakpam, Leepeng Singh Waikhom, Digambar Brahma, Pratikshit Baruah, Sarthak Biswas
Summary: This paper proposes an algorithm for compressing digital images and encrypting the compressed data for security. By utilizing a combination of various encryption techniques, the algorithm provides protection for data. Through experiments and analysis, the algorithm is shown to excel in both security against attacks and performance metrics.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Saumya Patel, Ankita Vaish
Summary: This paper introduces a novel image encryption technique using Compressive Sensing (CS) and DNA encoding. The plain image is decomposed into significant and less significant information through Multi-Resolution Singular Value Decomposition (MSVD), and then encrypted through confusion and diffusion processes. Simultaneous compression encryption is applied to the less significant information using CS. The proposed algorithm is tested against various attacks and proven to be secure and robust.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Saumya Patel, Ankita Vaish
Summary: This paper introduces a new approach to gray scale image coding based on Block Compressive Sensing (BCS). The proposed algorithm utilizes the advantages of encrypted DWT basis to achieve sparsity in the Discrete Wavelet Transform (DWT) domain. The use of a piecewise chaotic system for generating encrypted DWT basis provides enhanced signal security. The effectiveness of the algorithm is demonstrated through testing on various images, and the results show good perceptual quality even with a compression ratio of 0.5. The algorithm is also shown to be resilient against statistical attacks compared to existing methods.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Environmental Sciences
Jihoon Choi, Wookyung Lee
Summary: An adaptive block compressive sensing method is proposed for compression of synthetic aperture radar images in this paper. The method divides the image into blocks, subsamples them with different compression ratios, and utilizes a new clustered recovery method to reduce computational complexity. Experimental results show that the proposed scheme provides a good tradeoff between peak signal-to-noise ratio and computational load compared to conventional BCS-based compression techniques.
Review
Physics, Multidisciplinary
Rodrigo Capobianco Guido
Summary: Wavelet-based analyses have made remarkable achievements in physics and related sciences. However, many people still misunderstand the fundamentals of wavelets. This article provides clear explanations of different types of wavelet transforms and their applications, helping readers to effectively utilize wavelets in their research.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2022)
Article
Computer Science, Information Systems
Jiao Cai, Shucui Xie, Jianzhong Zhang
Summary: An image encryption scheme based on compressive sensing and chaos is proposed in this study. The plain image is transformed into a sparse coefficient matrix through the discrete wavelet transform, and then compressed and encrypted using a measurement matrix constructed by the Logistic-Tent system. The security of the cryptosystem is enhanced through a re-encryption process involving dual random index permutation and bit-level diffusion.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Arpita Banik, Laiphrakpam Dolendro Singh, Amit Agrawal, Ripon Patgiri
Summary: This paper discusses the importance of image data security and addresses the drawbacks of a block-based image encryption scheme. To overcome these issues, a new encryption algorithm is proposed and security and statistical analysis are conducted to evaluate its strength.
DIGITAL SIGNAL PROCESSING
(2022)
Article
Physics, Multidisciplinary
Yu-Guang Yang, Fei-Er Cheng, Dong-Hua Jiang, Yi-Hua Zhou, Wei-Min Shi, Xin Liao
Summary: The traditional image encryption technology produces noise-like visual features in cipher images, which explicitly reflect the presence of secret information. To address this issue, a visually meaningful image encryption algorithm is proposed based on a newly designed 2D memristive chaotic map, P-tensor product compressive sensing (PTP-CS), and discrete Hartley transform (DHT). This algorithm balances encryption security and decryption recovery, and exhibits excellent performance in important indicators such as visual quality, robustness, and timeliness.
Article
Physics, Multidisciplinary
Andy M. Ramos, Jose A. P. Artiles, Daniel P. B. Chaves, Cecilio Pimentel
Summary: This article presents a new proposal for image fragile watermarking algorithms for tamper detection and image recovery. The watermarked bits are obtained from the parity bits of an error-correcting code. The proposed algorithm is analyzed for both grayscale and colored images and performs better than some existing methods.
Article
Computer Science, Artificial Intelligence
Dustin Carrion-Ojeda, Rigoberto Fonseca-Delgado, Israel Pineda
Summary: This study focuses on the analysis of factors influencing the performance of a biometric system based on electroencephalogram signals. Different classifiers were used to compare decomposition levels and examine the significance of recording time, showing that SVM and AdaBoost are the most effective for this specific problem. The study highlights the unique nature of EEG signals and the potential for their use in developing robust biometric systems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Multidisciplinary
Zia Ullah, Hasan Saeed Qazi, Ahmad Alferidi, Mohammed Alsolami, Badr Lami, Hany M. Hasanien
Summary: This study presents a novel method for optimizing energy trading within microgrids by using a hybrid of particle swarm optimization and gravitational search algorithms. The proposed approach promotes cooperative energy trading among microgrids and the main grid, considering network constraints and the uncertainty of renewable energy. Simulation results show that this method maximizes renewable energy utilization, reduces load burden on the main grid, and significantly decreases energy costs.
ALEXANDRIA ENGINEERING JOURNAL
(2024)
Article
Engineering, Multidisciplinary
Chin Joo Tan
Summary: In this study, the effect of mesh sensitivity on the hole-flanging process was investigated by varying the mesh layouts and punch surface meshing techniques. The results showed that the punch displacement and mesh parameters have significant effects on the wall thickness distributions and forming load profiles. Additionally, calibrating the simulation model's stiffness with the experimental peak load through matching the simulated peak load with the experimental peak under stability conditions was recommended.
ALEXANDRIA ENGINEERING JOURNAL
(2024)
Article
Engineering, Multidisciplinary
Wei-Chao Yang, Lun Zhao, E. Deng, Yi-Qing Ni, Wen Zhao, Yi-Kang Liu, De-Hui Ouyang
Summary: This paper establishes a three-dimensional coupled train-subgrade-wind dynamics model, and investigates the aerodynamic load variation and flow field mechanisms when high-speed trains transit different types of subgrade-cutting transition sections in crosswind conditions. The results indicate that the aerodynamic performance of the train deteriorates in these transition sections, and the aerodynamic load of the head car varies in different operating scenarios.
ALEXANDRIA ENGINEERING JOURNAL
(2024)
Article
Engineering, Multidisciplinary
Shashi Bhushan, Anoop Kumar, Eslam Hussam, Manahil SidAhmed Mustafa, Mohammed Zakarya, Wedad R. Alharbi
Summary: In the sample survey theory, accurate estimation of parameters is essential for survey practitioners. This paper suggests optimal classes of estimators by modifying conventional estimators under stratified ranked set sampling (SRSS). The suggested estimators have been shown to outperform traditional estimators, particularly regression (BLU) estimators, both theoretically and experimentally.
ALEXANDRIA ENGINEERING JOURNAL
(2024)
Article
Engineering, Multidisciplinary
Laila A. Al-Essa, Ahmed A. Soliman, Gamal A. Abd-Elmougod, Huda M. Alshanbari
Summary: In this study, the class of lifetime distributions with bathtub-shaped failure rate functions is examined. Statistical inference methods are used to estimate the parameters of the model, and the Bayesian approach is compared with classical methods. The study also discusses the evaluation of product relative merits based on lifetime duration under a hybrid censoring scheme.
ALEXANDRIA ENGINEERING JOURNAL
(2024)
Article
Engineering, Multidisciplinary
Mohammad Partohaghighi, Marzieh Mortezaee, Ali Akguel, Ahmed M. Hassan, Necibullah Sakar
Summary: The study introduces a new variant of the fractal-fractional diffusion equation using the fractal-fractional operator. It proposes a novel operational matrix technique to solve the equation, transforming it into an algebraic system. The study presents graphical and tabular representations of exact and approximated solutions, along with corresponding errors, and conducts comparative analysis of solutions at specific time points.
ALEXANDRIA ENGINEERING JOURNAL
(2024)