Digital Image Transmission Research Articles

Memristor-coupled cubic hyperchaotic system, feedback synchronization and its application in image encryption

Discrete memristive chaotic systems play a crucial role in information security, and chaotic synchronization form the bedrock of secure and confidential communication. To enhance the chaotic complexity of the Cubic map, we introduce a memristor-coupled Cubic hyperchaotic system by integrating a discrete absolute memristor model with the Cubic map. The dynamics are thoroughly investigated through attractor phase diagrams, bifurcation diagrams, SE complexity analysis, and diagrams illustrating the distribution of dynamic behaviors. Furthermore, we establish methods for chaos control and nonlinear feedback synchronization for the memristive Cubic map. Leveraging this feedback synchronization, we achieve encrypted transmission of digital images. Simulation results validate the feasibility and robust security of the proposed encrypted transmission scheme.

Improved Chua’s chaotic system with a novel memristor: generating multi-scroll hidden attractors and applications in image encryption

In this paper, a new method for generating multi-scroll chaotic attractors by introducing a new memristor model into an improved Chua’s system is presented. The dynamic characteristics of the system are analyzed, including equilibria and stability, bifurcation diagrams, Lyapunov exponents and phase diagrams. Strikingly, it can exhibit three-scroll, four-scroll and five-scroll hidden attractors by only changing one system parameter and different shapes of chaotic attractors coexist with the same parameter. Furthermore, the high randomness of the system is verified through 0–1 test and NIST test. By using the high randomness of the system, an image encryption algorithm (IEA) is designed to guarantee the secure and efficient transmission of digital images. This IEA uses whirlpool transformation to scramble pixel positions and DNA computation to diffuse pixel values. The simulation and performance analysis results indicate that the proposed IEA has high security and reliable encryption performance, which in turn confirms the availability of the new memristor-based Chua’s chaotic system.

Embedded-deep-learning-based sample-to-answer device for on-site malaria diagnosis.

Improvements in digital microscopy are critical for the development of a malaria diagnosis method that is accurate at the cellular level and exhibits satisfactory clinical performance. Digital microscopy can be enhanced by improving deep learning algorithms and achieving consistent staining results. In this study, a novel miLab™ device incorporating the solid hydrogel staining method was proposed for consistent blood film preparation, eliminating the use of complex equipment and liquid reagent maintenance. The miLab™ ensures consistent, high-quality, and reproducible blood films across various hematocrits by leveraging deformable staining patches. Embedded-deep-learning-enabled miLab™ was utilized to detect and classify malarial parasites from autofocused images of stained blood cells using an internal optical system. The results of this method were consistent with manual microscopy images. This method not only minimizes human error but also facilitates remote assistance and review by experts through digital image transmission. This method can set a new paradigm for on-site malaria diagnosis. The miLab™ algorithm for malaria detection achieved a total accuracy of 98.86% for infected red blood cell (RBC) classification. Clinical validation performed in Malawi demonstrated an overall percent agreement of 92.21%. Based on these results, miLab™ can become a reliable and efficient tool for decentralized malaria diagnosis.

Plastic deformation delocalization at cryogenic temperatures in a nickel-based superalloy

A nickel-based superalloy is examined during monotonic deformation from ambient to cryogenic temperatures, reaching as low as liquid helium temperature. A detailed multimodal analysis of the microstructure and plasticity is conducted to discern changes in deformation mechanisms and plastic deformation localization under cryogenic conditions. This study employs high-resolution digital image correlation and transmission electron microscopy to identify the deformation mechanisms and understand their influence on plastic deformation localization as the temperature varies. At cryogenic temperatures, unusual plastic deformation localization processes are observed, attributed to the competing activation of a range of deformation processes. Furthermore, a mechanism of slip delocalization, i.e., local plastic deformation homogenization through closely spaced slip, is noted at these extreme temperatures. Ultimately, the impact of the microstructure is identified across the temperature range, from room to cryogenic temperatures.

A Secure Transmission of Digital Images using Multiple Chaotic Maps and Elliptic Curve

A Secure Transmission of Digital Images using Multiple Chaotic Maps and Elliptic Curve

Effect Analysis of Fourier Transform and Neural Network on Image Noise Reduction

During the acquisition, transmission, and processing of digital images, noise often appears in the pictures, seriously affecting the quality of the images and the accuracy of subsequent analysis. To solve this problem, many scholars have conducted in-depth research on image denoising, aiming to find denoising methods suitable for different scenarios. This study aims to compare the effects of Fourier transform and neural network methods in eliminating stripes in pictures. The discrete Fourier transform denoising method performs best in sharpness and has a fast processing time, but its image restoration is poor. Although the artificial neural network method has a long processing time and depends on the training set, it has good noise reduction effect. The Photoshop (beta) method is relatively simple and easy to use, with good overall effect. It is hoped that through further research, a better understanding of the role of Fourier transform and neural network methods in image noise elimination can be achieved, providing more references for the development of image processing technology. This article introduces in detail the Fourier transform method and neural network method, analyzes their advantages and disadvantages and scope of application. These results shed light on guiding further exploration of noise reduction.

DICOM Standard and Its Application in Radioinformatics

The DICOM standard is the emerging standard in the field of medical informatics. It defines the standard network interface and data model makes the medical image equipment manufacturers on the standard network equipment interconnection, simplify the development of various types of medical image, promote open unrelated to the factory of medical digital image transmission and exchange, prompting the image archiving and communication system of PACS (Picture Archiving and Communication Systems) and the combination of various hospital information system HIS (Hospital Information Systems). Radiation therapy departments in many hospitals have purchased more than one manufacturer of radiotherapy planning systems, and treatment information has to be communicated using DICOM standards. The use of DICOM in radiotherapy is called DICOM RT. At home, doctors are not fully aware of its importance and researchers do not. This paper mainly discusses the implementation and application of DICOM and protocol in precision radiotherapy system. The main contents include: (1) DICOM RT defines a total of seven information objects, which play a pivotal role in the information exchange of radiotherapy system. Discuss the content of DICOM RT; discuss the development of radiotherapy technology at home and abroad. (2) At present, DICOM standard has been widely used in the field of medical informatics, but no authority can provide DICOM compatibility verification of imaging equipment or DICOM application system, which still has many difficulties in system interconnection, that is, the research and implementation of DICOM test method. (3) The application of DICOM in PACS system. (4) Impaired compression study without visual loss in medical images based on DICOM standard.

Novel self-embedding holographic watermarking image encryption protection scheme

For digital image transmission security and information copyright, a new holographic image self-embedding watermarking encryption scheme is proposed. Firstly, the plaintext is converted to the RGB three-color channel, the corresponding phase hologram is obtained by holographic technology and the watermark is self-embedded in the frequency domain. Secondly, by applying the Hilbert transform principle and genetic center law, a complete set of image encryption algorithms is constructed to realize the encryption of image information. Finally, simulation results and security analysis indicate that the scheme can effectively encrypt and decrypt image information and realize the copyright protection of information. The introduced scheme can provide some support for relevant theoretical research, and has practical significance.

Application of compressive sensing techniques for advanced image processing and digital image transmission

The field of compressive sensing (CS) has emerged as a transformative approach in the acquisition and processing of high-dimensional data. This paper presents a comprehensive study on the application of compressive sensing techniques to advanced image processing and digital image transmission. By leveraging the inherent sparsity in natural images, CS allows for significant reductions in the amount of data required for accurate reconstruction, thereby overcoming the limitations imposed by the traditional Shannon-Nyquist sampling theorem. We explore the theoretical foundations of CS, including the principles of sparsity and incoherence, and provide a detailed overview of the Orthogonal Matching Pursuit (OMP) algorithm, a prominent greedy algorithm used for sparse signal recovery. Experimental results demonstrate the efficacy of CS in improving image reconstruction quality, as evidenced by enhancements in peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Additionally, we discuss the practical implementation of CS in single-pixel cameras and its potential impact on future imaging technologies. The findings suggest that CS offers a robust framework for efficient image acquisition and processing, making it a valuable tool for various applications in multimedia, medical imaging, and remote sensing.

Research on Digital Image Record in Intangible Cultural Heritage Inheritance Innovation under the Background of Big Data

Abstract The purpose of this paper is to investigate the digital lens presentation effect and image dissemination effect of intangible cultural heritage. In order to test the lens boundary detection technology of ICH digital images, we focus on analyzing the number of image frames, the number of mutations and the number of gradual changes of ICH characters, space-time and events, and exploring the checking completeness, the checking accuracy and the comprehensive detection rate of this paper’s algorithm and the dual-threshold comparative method on different types of ICH image fragments. Combined with the descriptive analysis of valid samples, we explore the main types of transmission of NRM digital images and clarify the degree of media utilization and the ranking of transmission power of NRM digital images in the Yangtze River Delta region. Shanghai has the strongest online dissemination power of traditional theater, traditional fine arts and traditional arts and crafts, with 1284586, 310468, and 237818, respectively, while traditional music, Chinese opera and folklore have the weakest dissemination power in Shanghai. Traditional music makes up 18.73% of them. To ensure non-heritage culture’s inheritance, it is necessary to strengthen the use of digital imaging technology to achieve linkage communication between non-heritage cultures and build an overall communication system.

Research on the Social Effects of the Digital Divide and Network Image Transmission: Taking Tik Tok as an Example

Research on the Social Effects of the Digital Divide and Network Image Transmission: Taking Tik Tok as an Example

SOFTWARE IMPLEMENTATION OF ALGORITHMS FOR SELECTING THE OUTLINES OF OBJECTS IMAGES IN INTELLECTUAL VIDEO SURVEILLANCE SYSTEMS

The rapid advancement in digital image acquisition and transmission technologies poses challenges in processing vast volumes of video information streams. Images serve as crucial sources of decision-making information across a wide range of tasks. Key objectives addressed by intelligent video surveillance systems include object identification, trajectory determination, object speed measurement, and real-time detection of critical events for securing premises. Among the primary operations in intelligent video surveillance systems is the extraction of object contours from images, as contours contain essential information for object recognition based on their shape. This approach excludes internal image points, significantly reducing the amount of processed information and enabling real-time image analysis. Contour analysis encompasses methods for selecting, describing, and processing image contours to describe, store, compare, and search for objects based on their external contours. This methodology effectively addresses fundamental challenges in pattern recognition, such as transferring, rotating, and scaling object images. The paper discusses prominent contour analysis methods and presents software implementations of algorithms for extracting object outlines in intelligent video surveillance systems. A promising future direction involves synthesizing algorithms that extract object contours using a two-scale statistical image model.

A Combination of Vigenere Cipher and Advanced Encryption Standard for Image Security

In an era where digital information security is paramount, this research addresses the pressing need for robust encryption methods. We propose a novel approach that combines the Vigenere Cipher and the Advanced Encryption Standard (AES) for secure digital image transmission. Our study recognizes the research gap in secure image transmission methods and aims to bridge it with a powerful encryption solution. We implement this hybrid encryption approach using the Vigenere Cipher in C++ and the AES algorithm in MATLAB. Our experiments validate the effectiveness of our program in concealing and restoring digital images during transmission. This hybrid encryption technique has promising applications in healthcare, military, and confidential business operations, bolstering image security in real-life scenarios. By enhancing image security, our research can contributed to safeguarding sensitive information in the digital age

Retraction Note: Paillier homomorphic cryptosystem with poker shuffling transformation based water marking method for the secured transmission of digital medical images

Retraction Note: Paillier homomorphic cryptosystem with poker shuffling transformation based water marking method for the secured transmission of digital medical images

Enabling secure image transmission in unmanned aerial vehicle using digital image watermarking with H-Grey optimization

Drone technology, also known as Unmanned Aerial Vehicles (UAVs), has advanced rapidly in the last decade owing to the huge number of users. This approach has an immense opportunity in areas like healthcare, agriculture, and forestry. However, the transmission of digital images via drone technology is associated with vulnerabilities and risks, due to a lack of efficient security solutions. Digital Image Watermarking (DIW) has emerged as a viable solution for digital image transmission in UAV applications. However, achieving robustness, security, and imperceptibility in a watermarking system at the same time is a difficult task. To address the aforementioned concerns, this paper proposes a secure digital image watermarking scheme in the hybrid DWT-SVD domain. The scaling factor is chosen adaptively from the hybrid Harmony-Grey Wolf (H-Grey) optimization algorithm to maintain a balance between imperceptibility and robustness. In addition, a novel symmetric cryptographic-based four-level encryption approach PSMD (Partitioning, Substituting, Merging, Division) is proposed to address UAV image security concerns by using Fibonacci and prime number series to generate two random keys. The proposed encryption scheme provides high security at low computational cost. The experimental results show that the visual quality and robustness are both high (Avg. PSNR = 41.27 dB and Avg. SSIM = 0.99, NC = 0.99, and BER = 0.0008 calculated for 100 images). The subjective and objective experimental analysis indicates that the proposed encryption scheme is highly secure and the computational cost is also low. The average embedding and extraction time is 0.25 s and 0.09 s It is resistant to various image processing attacks. A comparison with some of the most recent popular schemes confirms the scheme’s effectiveness. The presented DIW can be used for copyright protection, UAV image transmission applications, military applications, and other purposes.

The Critical Value of Telepathology in the COVID-19 Era.

Telepathology, which includes the use of telecommunication links, helps enable transmission of digital pathology images for primary diagnosis, quality assurance, education, research, or second opinion diagnoses. This review covers all aspects of telepathology implementation, including the selection of platforms, budgets and regulations, validation, implementation, education, quality monitoring, and the potential to improve practice. Considering the long-term trends, the lessons of the COVID-19 pandemic, and the potential for future pandemics or other disasters, the validation and implementation of telepathology remains a reasonable choice for laboratories looking to improve their practice. Though barriers to implementation exist, there are potential benefits, such as the wide spectrum of uses like frozen section, telecytology, primary diagnosis, and second opinions. Telepathology represents an innovation that may transform the future of pathology practice.

Research on No-reference Image Quality Assessment Algorithm Based on Generative Adversarial Networks

Currently, with the massive generation and transmission of digital images, especially the rapid development of the Internet and mobile Internet industries where images are widely used, the study of reference-free image quality assessment has attracted much attention in academia and practical applications, and is a popular research direction in the field of computer vision. In response to the low performance of existing reference-free image quality assessment algorithms in the face of real distorted images, a reference-free image quality assessment algorithm based on generative adversarial networks is proposed. Firstly, the generator structure is changed, the U-Net structure is improved, and the channel attention mechanism SeNet structure is introduced to update the feature map after down sampling. Secondly, a feature similarity measurement system is incorporated and a dual discriminator structure is used to discriminate multiple groups of images. The FPN structure is combined in the feature extractor to produce a multi-scale feature representation. Experiments are conducted on KonIQ-10k dataset and LIVEC dataset, and the experimental results show that the algorithm exhibits good prediction accuracy as well as good generalization performance in the face of real distorted images.

Performance comparison of machine learning driven approaches for classification of complex noises in quick response code images

Quick response codes (QRCs) are found on many consumer products and often encode security information. However, information retrieval at receiving end may become challenging due to the degraded clarity of QRC images. This degradation may occur because of the transmission of digital images over noise channels or limited printing technology. Although the ability to reduce noises is critical, it is just as important to define the type and quantity of noises present in QRC images. Therefore, this study proposed a simple deep learning-based architecture to segregate the image as either an original (normal) QRC or a noisy QRC and identifies the noise type present in the image. For this, the study is divided into two stages. Firstly, it generated a QRC image dataset of 80,000 images by introducing seven different noises (speckle, salt & pepper, Poisson, pepper, localvar, salt, and Gaussian) to the original QRC images. Secondly, the generated dataset is fed to train the proposed convolutional neural network (CNN)-based model, seventeen pre-trained deep learning models, and two classical machine learning algorithms (Naïve Bayes (NB) and Decision Tree (DT)). XceptionNet attained the highest accuracy (87.48%) and kappa (85.7%). However, it is worth noting that the proposed CNN network with few layers competes with the state-of-the-art models and attained near to best accuracy (86.75%). Furthermore, detailed analysis shows that all models failed to classify images having Gaussian and Localvar noises correctly.

One-Dimensional Quadratic Chaotic System and Splicing Model for Image Encryption

Digital image transmission plays a very significant role in information transmission, so it is very important to protect the security of image transmission. Based on the analysis of existing image encryption algorithms, this article proposes a new digital image encryption algorithm based on the splicing model and 1D secondary chaotic system. Step one is the algorithm of this article divides the plain image into four sub-parts by using quaternary coding, and these four sub-parts can be coded separately. Only by acquiring all the sub-parts at one time can the attacker recover the useful plain image. Therefore, the algorithm has high security. Additionally, the image encryption scheme in this article used a 1D quadratic chaotic system, which makes the key space big enough to resist exhaustive attacks. The experimental data show that the image encryption algorithm has high security and a good encryption effect.

File Encryption and Decryption using AES and RSA Algorithm

In the present scenario, no technology that's connected to the internet is unhackable. All digital services like internet communication, military and medical imaging systems, multimedia systems require reliable security in storage and transmission of digital images. The importance of protecting digital images cannot be overstated. Therefore, there is a need for image encryption techniques in order to hide images from such attacks. In this encryption process, we use AES and RSA Algorithm in order to hide images. This encryption techniques helps us to avoid intrusive attacks. Since, the image is encrypted using the AES technique, only the receiver can view it, as the key is known only to the sender and receiver. Overall, image encryption improves data integrity and can raise consumer trust.