Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…Imaging through dense fog presents unique challenges, with essential visual information crucial for applications like object detection and recognition, thereby hindering conventional image processing methods. …”
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Evaluation of Global-Scale and Local-Scale Optimized Segmentation Algorithms in GEOBIA With SAM on Land Use and Land Cover by Tao He, Jianyu Chen, Linchong Kang, Qiankun Zhu

“…However, obtaining outstanding segmentation results in all scenarios proves challenging with a single algorithm. This study investigates seven segmentation algorithms: mean shift (MF), O Sistema de Processamento de informações georreferenciadas (the geographic information and image processing system) (SPRING), Estimation of scale parameter 2 (ESP2) (three global-scale algorithms), image object detection approach (IODA), SA, edge-guided image object detection approach (EIODA) (three local-scale optimization algorithms), and segment anything model (SAM) (deep learning). …”
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Security-Enhanced Image Encryption: Combination of S-Boxes and Hyperchaotic Integrated Systems by Renjie Song, Haixia Zhao

“…In the field of image encryption, with the continuous development of attack techniques, the requirements for the attack resistance and robustness of encryption algorithms are increasing, and the method of image encryption using a single chaotic system can no longer provide sufficient security and randomness. …”
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Sparse point spread function-based multi-image optical encryption by Ning Xu, Dalong Qi, Long Cheng, Zhen Pan, Chengyu Zhou, Wenzhang Lin, Hongmei Ma, Yunhua Yao, Yuecheng Shen, Lianzhong Deng, Zhenrong Sun, Shian Zhang

“…Abstract Multi-image optical encryption (MOE) has demonstrated promising potential in image data protection owing to its parallel processing capability and abundant degrees of freedom. …”
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Research progress of digital image forensic techniques based on deep learning by Tong QIAO, Hongwei YAO, Binmin PAN, Ming XU, Yanli CHEN

“…In the new era of rapid development of internet, where massive forgery images with updated tampering techniques flood into, traditional algorithms are no longer able to deal with the latest multimedia tampering techniques, especially those caused by Deepfake and deep learning techniques.Thus, a universal framework for image forensics including image pre-processing module, feature extraction module and post-processing module designed for specific classification were proposed creatively.Accordingly, the state-of-the-art algorithms were reviewed，and meanwhile the main strength and limitations of current algorithms were generalized.More importantly, the future studies were also listed for advancing the development of digital image forensics.…”
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Color Image Denoising Based on Guided Filter and Adaptive Wavelet Threshold by Xin Sun, Ning He, Yu-Qing Zhang, Xue-Yan Zhen, Ke Lu, Xiu-Ling Zhou

“…In the process of denoising color images, it is very important to enhance the edge and texture information of the images. …”
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Innovative design of wood texture images for indoor furniture based on variable space by Chuan Xue, Ling Jin

“…The results of comparing the proposed algorithm with other image processing algorithms showed that the research algorithm achieved a peak signal-to-noise ratio of 29.86 and a structural similarity index of 0.87 in image denoising, respectively, and had a good denoising effect. …”
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Early Detection of Parkinson’s Disease Using AI Techniques and Image Analysis by Marilena Ianculescu, Corina Petean, Virginia Sandulescu, Adriana Alexandru, Ana-Mihaela Vasilevschi

“…Background: Parkinson’s disease (PD) diagnosis benefits significantly from advancements in artificial intelligence (AI) and image processing techniques. This paper explores various approaches for processing hand-drawn Archimedean spirals in order to detect signs of PD. …”
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Charting the path forward: CT image quality assessment - an in-depth review by Siyi Xun, Qiaoyu Li, Xiaohong Liu, Pu Huang, Guangtao Zhai, Yue Sun, Peter H. N. de With, Mingxiang Wu, Tao Tan

“…It helps improve the accuracy of CT scanning equipment and the performance of CT system reconstruction algorithms, and provides a new idea for CT image processing algorithms. …”
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An algorithm of unordered wavefront propagation in terahertz phase retrieval with dense multiplane data acquisition by E.G. Tsiplakova, A. Chopard, N.S. Balbekin, O.A. Smolyanskaya, J.-B. Perraud, J.-P. Guillet, P. Mounaix, N.V. Petrov

“…Iterative phase retrieval algorithms from multiple diffraction patterns in the terahertz (THz) frequency range are a promising tool of computational imaging capable of providing high spatial resolution of reconstructed phase images. …”
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A Perception-Driven Transcale Display Scheme for Space Image Sequences by Lingling Zi, Xin Cong, Yanfei Peng, Pei Yang

“…The former concentrates on describing the transcle feature of space targets, including three algorithms, attention region computing, frame rate conversion, and image resolution resizing. …”
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SIFusion: Lightweight infrared and visible image fusion based on semantic injection. by Song Qian, Liwei Yang, Yan Xue, Ping Li

“…However, existing image fusion algorithms predominantly focus on enhancing the visual appeal of the fused image for human perception, often neglecting their impact on subsequent high-level visual tasks, particularly the processing of semantic information. …”
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Image Based Detection of Coating Wear on Cutting Tools with Machine Learning by Jan Wolf, Nithin Kumar Bandaru, Martin Dienwiebel, Hans-Christian Möhring

“…Based on cutting experiments conducted with a TiN/AlTiN-coated cutting tool, an image dataset was generated and pre-processed using multiple algorithms, such as Canny edge detection and Hough line transforms. …”
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Three-dimensional visualization of maize roots based on magnetic resonance imaging by Fang Xiaorong, Wang Nanfei, Zhang Jianfeng, Gong Xiangyang, Liu Fei, He Yong

“…The reconstruction process consisted of the following steps: image format conversion, filtering, roots target extraction, root data encapsulation, model reconstruction. …”
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A Novel Compressive Optical Encryption via Single-Pixel Imaging by Chenggong Zhang, Bennian Han, Wenqi He, Xiang Peng, Chen Xu

“…A novel compressive optical cryptosystem based on single-pixel imaging is proposed. By using random sparse sampling in the encryption process, the plaintext is encrypted and compressed into a noise-like intensity sequence. …”
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Study on rapid calculation and imaging simulation of aircraft infrared radiation characteristics by Huicheng Yang, Qingzhen Yang, Yongqiang Shi, Xubo Du, Xinyuan Liu

“…The method can achieve a calculation speed of four times per second for a single detection angle, meeting real-time processing requirements and providing valuable data for infrared target recognition algorithms.…”
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Feature Representation Using Deep Autoencoder for Lung Nodule Image Classification by Keming Mao, Renjie Tang, Xinqi Wang, Weiyi Zhang, Haoxiang Wu

“…The visual vocabulary is constructed based on the local features and bag of visual words (BOVW) is used to describe the global feature representation of lung nodule image. Finally, softmax algorithm is employed for lung nodule type classification, which can assemble the whole training process as an end-to-end mode. …”
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Single image de-raining by multi-scale Fourier Transform network. by Chaobing Zheng, Yao Yao, Wenjian Ying, Shiqian Wu

“…Following this, data-driven algorithms are employed separately to process the amplitude and phase components. …”
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Reduced-Reference Image Quality Assessment based on saliency region extraction by Farzin Yaghmaee, Ehsanhosein Kalatehjari

“…As the human visual system is sensitive to the salient region, evaluating the image quality based on the salient region could increase the accuracy of the algorithm. …”
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XTNSR: Xception-based transformer network for single image super resolution by Jagrati Talreja, Supavadee Aramvith, Takao Onoye

“…Abstract Single image super resolution has significantly advanced by utilizing transformers-based deep learning algorithms. …”
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