A Review of Spaceborne High-Resolution Spotlight/Sliding Spotlight Mode SAR Imaging by Baolong Wu, Chengjin Liu, Jianlai Chen

“…These include the following: eliminating the azimuth spectral aliasing by azimuth deramp preprocessing; implementing imaging processing using imaging kernels (RD, CS, RMA, etc.); and degrading the back-folded phenomenon in the final focused image domain by reference function multiplication post-processing. …”
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Image Denoising of Adaptive Fractional Operator Based on Atangana–Baleanu Derivatives by Xiaoran Lin, Yachao Wang, Guohao Wu, Jing Hao

“…Furthermore, the image processed by the Ada_TA_ABC operator has less noise and more detail, which means the proposed adaptive function has universality.…”
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Digital Media Image of Business University Professor by M. A. Lukashenko, N. V. Gromova, A. A. Ozhgikhina

“…Relevance of this article is in the research of the digital image process formation by professors of business universities, which are the flagships and market-oriented subjects of local higher education.The article aims to identify the current state of forming the digital image of teachers of entrepreneurial universities in social networks. …”
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Array Three-Dimensional SAR Imaging via Composite Low-Rank and Sparse Prior by Zhiliang Yang, Yangyang Wang, Chudi Zhang, Xu Zhan, Guohao Sun, Yuxuan Liu, Yuru Mao

“…Firstly, an imaging optimization model based on composite SLRP is established, which captures both sparse and low-rank features simultaneously by combining non-convex regularization functions and improved nuclear norm (INN), reducing bias effects during the imaging process and improving imaging accuracy. Then, the framework that integrates variable splitting and alternative minimization (VSAM) is presented to solve the imaging optimization problem, which is suitable for high-dimensional imaging scenes. …”
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A Novel Pattern Recognition Method for Self-Powered TENG Sensor Embedded to the Robotic Hand by Azat Balapan, Rauan Yeralkhan, Alikhan Aryslanov, Gulnur Kalimuldina, Azamat Yeshmukhametov

“…To capitalize on these benefits, we propose a novel machine learning approach that represents time-series data as two-dimensional images processed using a two-dimensional convolutional neural network (2D CNN). …”
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Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI by Yonghui Kang, Yonghong Zhang, Hong'an Wu, Jujie Wei, Xiaoxue Sun, Yue Zuo

“…In the enhanced spectral diversity coregistration, slave images are segmented by temporal baseline, with the first image processed serially and others in parallel. Validation with 30 Sentinel-1 SAR images from Tianjin-Tangshan (plain) and Zhejiang (mountainous) regions demonstrates significant improvements. …”
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Partial Volume Reduction by Interpolation with Reverse Diffusion by Olivier Salvado, Claudia M. Hillenbrand, David L. Wilson

“…On gray level, scanned text, MRI physical phantom, and brain images, restored images processed with the new method were visually much closer to high-resolution counterparts than those obtained with common interpolation methods.…”
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Evolution of Artificial Intelligence in Medical Education From 2000 to 2024: Bibliometric Analysis by Rui Li, Tong Wu

“…The citation burst time of terms revealed that AI technologies shifted from imaging processing (2000), augmented reality (2013), and virtual reality (2016) to decision-making (2020) and model (2021). …”
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Partial Volume Reduction by Interpolation with Reverse Diffusion

“…On gray level, scanned text, MRI physical phantom, and brain images, restored images processed with the new method were visually much closer to high-resolution counterparts than those obtained with common interpolation methods.…”
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Application of Remote Sensing Image Data Scene Generation Method in Smart City by Yuanjin Xu

“…This paper uses POV ray photon reverse tracking software to simulate the imaging process of remote sensing sensors, coordinate transformation is used to convert a triangle text file to POV ray readable information and input the RGB value of the base color based on the colorimetry principle, and the final 3D scene is visualized. …”
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Reversible data hiding scheme based on enhanced image smoothness by Jinghan WANG, Hui ZHU, Helin LI, Hui LI, Xiaopeng YANG

“…With the prosperity of Internet technology and the popularity of social networks, reversible data hiding technology has been widely adopted in concealed information transmission of medical and military fields with its advantages on secret information recovery.Traditional reversible data hiding schemes mainly focus on the enhancement of embedding capacity and the reduction of the distortion rate of stego image, but pay less attention to the understanding of image details with the human eyes.Thus, it is difficult to resist hidden information detection methods.To solve the above challenge, a reversible data hiding algorithm was proposed, which ensured the visual quality of the stego image in the process of data hiding through the image visual smoothness enhancement.Specifically, the original image was divided into reference area and non-reference area.The secret data was embedded through the translation of the difference, which was calculated according to the predicted pixel value and the original pixel value of the non-reference area.To guarantee the visual quality of the image, smoothing mechanism was constructed, in which a Gaussian filter was utilized as a template to filter the predicted value and to add the filter difference into the cover image without loss.The pixel value of the reference region was used as edge information for lossless restoration of the original image.The filtering coefficient in Gaussian function was exploited as the embedded key to ensure the security of secret information.Simulation results regarding a large number of classical image data sets illustrated that the visual smoothness of stego image processed by this scheme was effectively enhanced with lower distortion rate, higher embedding rate, and higher embedding and extraction efficiency.In a typical circumstance, the similarity between the generated stego image and the Gaussian filter image can reach 0.9963.The PSNR and the embedded capacity can be up to 37.346 and 0.3289 BPP, respectively.…”
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CR-DEQ-SAR: A Deep Equilibrium Sparse SAR Imaging Method for Compound Regularization by Guoru Zhou, Yixin Zuo, Zhe Zhang, Bingchen Zhang, Yirong Wu

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A Study of a New Technique of the CT Scan View and Disease Classification Protocol Based on Level Challenges in Cases of Coronavirus Disease by Ahmed B. Salem Salamh, Abdulrauf A. Salamah, Halil Ibrahim Akyüz

“…The preliminary study is to compare the radiological findings of COVID-19 pneumonia in conventional chest CT images with images processed by a new tool and reviewed by expert radiologists. …”
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A multi-modal multi-branch framework for retinal vessel segmentation using ultra-widefield fundus photographs by Qihang Xie, Qihang Xie, Xuefei Li, Yuanyuan Li, Yuanyuan Li, Jiayi Lu, Jiayi Lu, Shaodong Ma, Yitian Zhao, Yitian Zhao, Jiong Zhang, Jiong Zhang

“…The segmentation network includes the Selective Fusion Module (SFM), which enhances feature extraction within the segmentation network by integrating features generated during the FFA imaging process. To further address the challenges of high-resolution UWF fundus images, we introduce a Local Perception Fusion Module (LPFM) to mitigate context loss during the segmentation cut-patch process. …”
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Through the Citizen Scientists’ Eyes: Insights into Using Citizen Science with Machine Learning for Effective Identification of Unknown-Unknowns in Big Data by Kameswara Bharadwaj Mantha, Hayley Roberts, Lucy Fortson, Chris Lintott, Hugh Dickinson, William Keel, Ramanakumar Sankar, Coleman Krawczyk, Brooke Simmons, Mike Walmsley, Izzy Garland, Jason Shingirai Makechemu, Laura Trouille, Clifford Johnson

“…In this work, we present a case study from the Galaxy Zoo: Weird & Wonderful project, where volunteers inspected ~200,000 astronomical images—processed by an ML-based anomaly detection model—to identify those with unusual or interesting characteristics. …”
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Optical Coherence Tomography Angiography to Distinguish Changes of Choroidal Neovascularization after Anti-VEGF Therapy: Monthly Loading Dose versus Pro Re Nata Regimen by Alexandra Miere, Hassiba Oubraham, Francesca Amoroso, Pauline Butori, Polina Astroz, Oudy Semoun, Elsa Bruyere, Alexandre Pedinielli, Manar Addou-Regnard, Camille Jung, Salomon Y. Cohen, Eric H. Souied

“…CNV size was measured using a free image analysis software (ImageJ, open-source imaging processing software, 2.0.0). Results. Twenty-five eyes of 25 patients were enrolled in our study (mean age 78.32 ± 6.8 years): 13 treatment-naïve eyes in group A and 12 treated eyes in group B. …”
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Revealing speckle obscured living human retinal cells with artificial intelligence assisted adaptive optics optical coherence tomography by Vineeta Das, Furu Zhang, Andrew J. Bower, Joanne Li, Tao Liu, Nancy Aguilera, Bruno Alvisio, Zhuolin Liu, Daniel X. Hammer, Johnny Tam

“…However, because noise inherent to the imaging process (e.g., speckle) makes it difficult to visualize RPE cells from a single volume acquisition, a large number of 3D volumes are typically averaged to improve contrast, substantially increasing the acquisition duration and reducing the overall imaging throughput. …”
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Characterization of Complex Image Spatial Structures Based on Symmetrical Weibull Distribution Model for Texture Pattern Classification by Jinping Liu, Jiezhou He, Zhaohui Tang, Pengfei Xu, Wuxia Zhang, Weihua Gui

“…It firstly makes a theoretical explanation of the Weibull distribution (WD) behavior of the LHFs of the imaged surface in the imaging process based on the sequential fragmentation theory (SFT), which consequently derives a symmetrical WD model (SWDM) to characterize the LSD of the TP’s SS. …”
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Application of Enhanced Weighted Least Squares with Dark Background Image Fusion for Inhomogeneity Noise Removal in Brain Tumor Hyperspectral Images by Jiayue Yan, Chenglong Tao, Yuan Wang, Jian Du, Meijie Qi, Zhoufeng Zhang, Bingliang Hu

“…The approach discussed in this paper, according to the experiments, produces the best results in terms of the subjective effect and unreferenced image denoising evaluation indices (MICV and MNR). The image processed by this method has almost no residual non-uniform noise, the image is clear, and the best visual effect is achieved. …”
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Improving remote sensing dehazing quality through local hybrid correction and optimization of atmospheric attenuation model based on wavelength by Daihong Zhao, Kun Shi, Zheng Li, Zheng Li, Meixiang Chen

“…The quantitative analysis of the dehazed images, using gray-level co-occurrence matrix (GLCM) metrics, indicated that the LHC method offered a balanced advantage in enhancing image details, texture consistency, and structural complexity. Specifically, images processed by LHC exhibit moderate contrast and correlation, low homogeneity and high entropy, all these made the LHC method a very suitable solution for near-ground remote sensing tasks that required enhanced image detail and reduced artifacts. …”
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