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3D robust anisotropic diffusion filtering algorithm for sparse view neutron computed tomography 3D image reconstruction

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Nuclear Science and Techniques 2024年第3期35卷 13-29页

作者： Yang Liu Teng-Fei Zhu Zhi Luo xiao-Ping Ouyang School of Nuclear Science and Engineering North China Electric Power UniversityBeijing 102206China State Key Laboratory of Nuclear Resources and Environment East China University of TechnologyNanchang 330013China State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Xi’an 710024China

The most critical part of a neutron computed tomography(NCT) system is the image processing algorithm,which directly affects the quality and speed of the reconstructed *** types of noise in the system can degrade the quality of the reconstructed ***,to improve the quality of the reconstructed images of NCT systems,efficient image processing algorithms must be *** anisotropic diffusion filtering(ADF) algorithm can not only effectively suppress the noise in the projection data,but also preserve the image edge structure information by reducing the diffusion at the image ***,we propose the application of the ADF algorithm for NCT image *** compare the performance of different algorithms in NCT systems,we reconstructed images using the ordered subset simultaneous algebraic reconstruction technique(OS-SART) algorithm with different regular terms as image processing *** the iterative reconstruction,we selected two image processing algorithms,the Total Variation and split Bregman solved total variation algorithms,for comparison with the performance of the ADF ***,the filtered back-projection algorithm was used for comparison with an iterative *** reconstructing the projection data of the numerical and clock models,we compared and analyzed the effects of each algorithm applied in the NCT *** on the reconstruction results,OS-SART-ADF outperformed the other algorithms in terms of denoising,preserving the edge structure,and suppressing *** example,when the 3D Shepp–Logan was reconstructed at 25 views,the root mean square error of OS-SART-ADF was the smallest among the four iterative algorithms,at only *** universal quality index,mean structural similarity,and correlation coefficient of the reconstructed image were the largest among all algorithms,with values of 0.9877,0.9878,and 0.9887,respectively.

关键词： NCT OS-SART Sparse-view Anisotropic diffusion filtering

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Atomic-level quantitative analysis of electronic functional materials by aberration-corrected STEM

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Chinese Physics B 2024年第11期33卷 12-25页

作者： Wanbo Qu Zhihao Zhao Yuxuan Yang Yang Zhang Shengwu Guo Fei Li xiangdong Ding Jun Sun Haijun Wu State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong UniversityXi'an 710049China Electronic Materials Research Laboratory Key Laboratory of the Ministry of Educationand School of Electronic and Information EngineeringXi'an Jiaotong UniversityXi'an 710049China Instrumental Analysis Center of Xi'an Jiaotong University Xi'an Jiaotong UniversityXi'an 710049China

The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope(ACSTEM)makes it an advanced and practical characterization technique for all *** to the prosperous advancement in computational technology,specialized software and programs have emerged as potent facilitators across the entirety of electron microscopy characterization *** advanced image processing algorithms promotes the rectification of image distortions,concurrently elevating the overall image quality to superior *** high-resolution,pixel-level discrete information and converting it into atomic-scale,followed by performing statistical calculations on the physical matters of interest through quantitative analysis,represent an effective strategy to maximize the value of electron microscope *** efficacious utilization of quantitative analysis of electron microscope images has become a progressively prominent consideration for materials scientists and electron microscopy *** article offers a concise overview of the pivotal procedures in quantitative analysis and summarizes the computational methodologies involved from three perspectives:contrast,lattice and strain,as well as atomic displacements and *** further elaborates on practical applications of these methods in electronic functional materials,notably in piezoelectrics/ferroelectrics and *** emphasizes the indispensable role of quantitative analysis in fundamental theoretical research,elucidating the structure–property correlations in high-performance systems,and guiding synthesis strategies.

关键词： AC-STEM quantitative analysis polarization electronic functional materials

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20 Years of Biomedical image Acquisition and processing at BioCAS

20 Years of Biomedical Image Acquisition and Processing at B...

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2024 Biomedical Circuits and systems Conference

作者： Bermak, Amine Liu, Tianyi Zhao, Ziyao Wang, Bo Zhang, Milin Hamad Bin Khalifa Univ Coll Sci & Engn Doha Qatar Tsinghua Univ Dept Elect Engn Beijing Peoples R China

ISBN: (纸本)9798350354966;9798350354959

The development of biomedical image technology has brought significant advancements to healthcare and frontier research. Over the past 20 years, BioCAS has witnessed and documented comprehensive achievements in biomedical image sensor design and processing algorithms. This paper provides a systematic review of the work related to biomedical image acquisition and processing technology in BioCAS and offers a perspective on future developments in this field.

关键词： review biomedical image image acquisition image processing

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HQ-I2IT: Redesign the optimization scheme to improve image quality in CycleGAN-based image translation systems

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IET image processing 2024年第2期18卷 507-522页

作者： Zhang, Yipeng Hu, Bingliang Huang, Yingying Gao, Chi Yin, Jianfu Wang, Quang Chinese Acad Sci Xian Inst Opt & Precis Mech Key Lab Spectral Imaging Technol 17 Informat Ave Xian 710119 Shaanxi Peoples R China Key Lab Biomed Spect Xian Xian Shaanxi Peoples R China Univ Chinese Acad Sci Sch Optoelect Beijing Peoples R China

The image-to-image translation (I2IT) task aims to transform images from the source domain into the specified target domain. State-of-the-art CycleGAN-based translation algorithms typically use cycle consistency loss and latent regression loss to constrain translation. In this work, it is demonstrated that the model parameters constrained by the cycle consistency loss and the latent regression loss are equivalent to optimizing the medians of the data distribution and the generative distribution. In addition, there is a style bias in the translation. This bias interacts between the generator and the style encoder and visually exhibits translation errors, e.g. the style of the generated image is not equal to the style of the reference image. To address these issues, a new I2IT model termed high-quality-I2IT (HQ-I2IT) is proposed. The optimization scheme is redesigned to prevent the model from optimizing the median of the data distribution. In addition, by separating the optimization of the generator and the latent code estimator, the redesigned model avoids error interactions and gradually corrects errors during training, thereby avoiding learning the median of the generated distribution. The experimental results demonstrate that the visual quality of the images produced by HQ-I2IT is significantly improved without changing the generator structure, especially when guided by the reference images. Specifically, the Frechet inception distance on the AFHQ and CelebA-HQ datasets are reduced from 19.8 to 10.2 and from 23.8 to 17.0, respectively. In this work, it is demonstrated that the cycle consistency loss and latent regression loss in CycleGAN-based image translation models can be detrimental to image quality. The optimization scheme of CycleGAN-based image translation systems is redesigned and a new translation model named HQ-I2IT is proposed. Experiments demonstrate that the proposed method can significantly improve image quality and translation ***

关键词： computer animation computer vision image processing

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Robust Possibilistic Fuzzy Additive Partition Clustering Motivated by Deep Local Information

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CIRCUITS systems AND SIGNAL processing 2024年第12期43卷 7662-7713页

作者： Wu, Chengmao Wu, Wen Xian Univ Posts & Telecommun Sch Elect Engn Xian 710121 Peoples R China

Aiming at the weak robustness of possibilistic fuzzy clustering against noise, a robust possibilistic fuzzy additive partition clustering with master-slave neighborhood information constraints is proposed for high noise image segmentation. This algorithm first constructs a master-slave neighborhood model, which consists of the master neighborhood window of the current pixel and the slave neighborhood window around the master neighborhood pixel. Then, the master-slave neighborhood information is integrated into the possibilistic fuzzy additive partition clustering model, and a novel robust possibilistic fuzzy clustering model incorporating deep local information is constructed. Next, this clustering model is further simplified by Cauchy inequality and a robust master-slave neighborhood information-driven possibilistic fuzzy clustering algorithm is derived by optimization theory. Extensive experimental results indicate that the proposed algorithm is very effective for noisy image segmentation, and its segmentation performance is significantly better than many existing state-of-the-art fuzzy clustering-related algorithms. In short, the work of this paper has profound significance for the development of robust fuzzy clustering theory.

关键词： image segmentation Possibilistic fuzzy clustering Fuzzy local information factor Master-slave neighborhood model Noise-resistant robustness

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Zero Watermarking algorithms for Medical images Based on Multi-module Fusion with VGG16 and Dual-Logistic Mapping Encryption

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CIRCUITS systems AND SIGNAL processing 2025年 1-36页

作者： Li, Jingyou Wei, Rongle xi, xiaotian Zhang, Guangda Yang, Zixin Zhang, Fengshan Qiqihar Univ Sch Comp & Control Engn Qiqihar Heilongjiang Peoples R China Qiqihar Univ Heilongjiang Key Lab Big Data Network Secur Detect Qiqihar Heilongjiang Peoples R China

The current research proposes a new zero watermarking approach that aims to protect medical images from tampering by utilizing the powerful learning capabilities of deep learning. In this paper, we propose a robust zero watermarking scheme based on multi-module fusion of VGG16, which enhances the efficiency and security of medical image transmission. The scheme leverages depthwise separable convolution to speed up feature extraction, enabling the focus on global image features. Furthermore, by incorporating the Convolutional Attention Module with channel and spatial attention, the extracted features are enhanced with stronger perceptual, discriminative, and generalization *** preserve multi-scale information and improve feature reusability, jump-joins are employed. The multi-module fusion of VGG16 facilitates the extraction of deep features with superior generalization, multi-scale, and high perceptual capabilities. Binary feature vectors are generated using a mean hash algorithm and encrypted using a novel dual chaos dual logistics encryption method designed in this paper, which significantly enhances both image watermark security and overall network transmission *** effectiveness of the scheme is verified through extensive experiments. Experimental results demonstrate that the proposed method achieves an NC value of over 0.92 in the presence of noise filtering and rotation attacks, indicating robust security and strong resistance to common image distortions. These results confirm the scheme's capability to provide high security for medical image transmission, ensuring both robustness against attacks and confidentiality in medical systems.

关键词： Zero watermark Multi-module fusion VGG16 Dual-chaos dual-logistics encryption (DcDlE)

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Application of image Security Transmission Encryption Algorithm Based on Chaos Algorithm in Networking systems of Artificial Intelligence 5

Application of Image Security Transmission Encryption Algori...

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5th Asia-Pacific Conference on image processing, Electronics and Computers, IPEC 2024

作者： Tian, Hongmei Yuan, Zhijie Zhou, Jiao He, Rui Xi’an University of Technology Xi'an710054 China China Coal Technology & Engineering Group Xian Research Institute Xi'an710076 China

ISBN: (纸本)9781643685243

This study focuses on enhancing the security of image transmission in Networking systems of Artificial Intelligence (NSAI) by implementing an advanced encryption algorithm (AEA) based on chaotic algorithms. The research begins by exploring the fundamental concepts, structures, and practical applications of NSAI. It then introduces the development of the AEA, specifically designed to safeguard image data during transmission. The methodology involves integrating a chaotic algorithm into the encryption and decryption processes, thereby improving the confidentiality and integrity of the images. Additionally, an encryption protocol consistent with NSAI specifications is developed to further enhance the security of transmitted images. Through simulations, the AEA demonstrates exceptional performance, with minimal errors, high accuracy, and outstanding efficiency in encryption tasks. Overall, this study concludes that the AEA represents a significant advancement in securing image transmission within NSAI, providing robust protection for future applications. © 2024 The Authors.

关键词： Artificial intelligence

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A Novel Visual Communication Scenario Based on image processing algorithms 2

A Novel Visual Communication Scenario Based on Image Process...

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2nd International Conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Yang, Jinhua Hou, Li Xijing University Shaanxi Xi'an710123 China

ISBN: (纸本)9798331505745

In order to comply with the trend of intelligent visual communication, this study proposed an innovative visual communication scenario based on image processing algorithms. The framework aims to optimize traditional key technologies such as the image generation, editing, style transfer and image compression. First, as the foundation of visual communication, this study proposes a generative adversarial network model based on text semantic information for image generation and editing. The model achieves stable image generation and efficient editing from a theoretical level through paired training of text and image pairs. Secondly, for image style transfer, this study designed an improved VGG19 convolutional neural network. At the same time, the adaptive instance normalization technology was combined to optimize the effect of style transfer. Finally, in terms of image compression, the study proposed an improved generative adversarial network (REVISED-GAN) model. This model can dynamically adjust the compression error based on structured information to improve image compression efficiency. Through comparative tests, the proposed image style transfer and image compression algorithms have shown excellent performance in terms of structural similarity, image quality and compression ratio. © 2025 IEEE.

关键词： Visual communication

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4D LUT: Learnable Context-Aware 4D Lookup Table for image Enhancement

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IEEE TRANSACTIONS ON image processing 2023年 32卷 4742-4756页

作者： Liu, Chengxu Yang, Huan Fu, Jianlong Qian, Xueming Microsoft Res Asia Beijing 100080 Peoples R China Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ Minist Educ Key Lab Intelligent Networks & Network Secur Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Informat & Commun Engn SMILES Lab Xian 710049 Peoples R China Shaanxi Yulan Jiuzhou Intelligent Optoelect Techno Xian 710000 Peoples R China

image enhancement aims at improving the aesthetic visual quality of photos by retouching the color and tone, and is an essential technology for professional digital photography. Recent years deep learning-based image enhancement algorithms have achieved promising performance and attracted increasing popularity. However, typical efforts attempt to construct a uniform enhancer for all pixels' color transformation. It ignores the pixel differences between different content (e.g., sky, ocean, etc.) that are significant for photographs, causing unsatisfactory results. In this paper, we propose a novel learnable context-aware 4-dimensional lookup table (4D LUT), which achieves content-dependent enhancement of different contents in each image via adaptively learning of photo context. In particular, we first introduce a lightweight context encoder and a parameter encoder to learn a context map for the pixel-level category and a group of image-adaptive coefficients, respectively. Then, the context-aware 4D LUT is generated by integrating multiple basis 4D LUTs via the coefficients. Finally, the enhanced image can be obtained by feeding the source image and context map into fused context-aware 4D LUT via quadrilinear interpolation. Compared with traditional 3D LUT, i.e., RGB mapping to RGB, which is usually used in camera imaging pipeline systems or tools, 4D LUT, i.e., RGBC(RGB+Context) mapping to RGB, enables finer control of color transformations for pixels with different content in each image, even though they have the same RGB values. Experimental results demonstrate that our method outperforms other state-of-the-art methods in widely-used benchmarks.

关键词： image enhancement photo retouching lookup tables neural networks

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Research on Password algorithms based on Chaos and Algebraic Groups 2

Research on Password Algorithms based on Chaos and Algebraic...

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2nd IEEE International Conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： He, xi Northfield Mount Hermon School Gill United States

ISBN: (纸本)9798350317558

As information technology advances rapidly, the demand for data security continues to grow. Chaos theory and algebraic groups have become a focal point in cryptographic research, providing a foundation for designing more robust block cipher algorithms. This article introduces a password algorithm based on chaos and algebraic groups, proposing the Lorenz chaos-geometric Goppa code composite password algorithm that has demonstrated significant achievements in image processing. In comparison to traditional methods, this algorithm exhibits the shortest key length and reduced error rates in image processing, offering a more reliable data protection solution for practical applications. This research opens up new possibilities for enhancing the security and performance in the field of cryptography. © 2024 IEEE.

关键词： Algebraic Group Chaos Cryptography Error Correction Capability Geometric Goppa Code Lorenz Chaos System

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