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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

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A Survey of Low-Light image Enhancement 5

A Survey of Low-Light Image Enhancement

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5th International conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Wei, Wangjuan Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9781450396899

image sensors imaging in low-light environments can cause problems such as high image noise, low contrast, and failure to represent large amounts of detailed information, which affect not only human eye observation but also applications related to computer vision and low-light image processing. The use of image enhancement methods and deep learning methods can improve the contrast of low-light images and improve the image quality. The article first introduces the traditional low-illumination image enhancement algorithms categorized and summarizes the improvement process of these algorithms in recent years, then introduces the low-illumination image enhancement methods based on deep learning, and finally introduces the existing low-illumination image datasets and the evaluation criteria of the enhanced images. © 2022 ACM.

关键词： image enhancement

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Design of a large-range dispersive objective for line-sweep spectral confocal displacement sensors 6

Design of a large-range dispersive objective for line-sweep ...

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6th conference on Frontiers in Optical Imaging and Technology: Novel Technologies in Optical systems

作者： Yang, Weiguang Qi, Meijie Yan, Jiayue Cheng, Mohan Zhang, Zhoufeng Laboratory of Spectral Imaging Technology Xi'an Institute of Optical Precision and Mechanical Research Chinese Academy of Sciences Shaanxi Xi'an710119 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781510679672

ISBN: (纸本)9781510679665

Spectral Confocal Displacement Sensor is a new type of displacement sensor that can meet the requirements of high precision, high speed and non-destructive testing, and can be applied in aerospace, medical and industrial testing fields. The traditional point-scan spectral confocal displacement sensor only collects depth information of one point at a time, which is slow and has a large amount of back-end data. In order to improve the scanning speed of the point-scan spectral confocal displacement sensor and reduce the workload of data processing, it is proposed to extend the point-scan type to line-scan type, which can obtain the depth information of thousands of points at one time, improve the scanning speed and reduce the workload of data processing by processing all the points on the scanning line at one time. Aiming at the dispersive objective lens design in the line-scan spectral confocal displacement sensor, a dispersive lens with a large linear dispersion range is designed based on the principle of linear axial chromatic aberration design. The lens consists of four single lenses and two double-glued lenses and a beam-splitting prism, in order to solve the problem of energy uniformity into the spectrometer and the problem of uniformity of illumination on the image surface, the double telecentric optical path design is adopted, and the size of the detector element selected is 5.5 um, and the Nyquist cutoff frequency is 91 Lp/mm. The design results show that: the dispersive range of the lens reaches 3 mm, and the length of the scanning line reaches 10 mm. At the Nyquist cutoff frequency, the MTF value of the whole field of view is greater than 0.6, which indicates that the system has good imaging quality. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical design

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Fusion of Infrared and Visible Sensor images Based on Anisotropic Diffusion and Fast Guided Filter 14

Fusion of Infrared and Visible Sensor Images Based on Anisot...

引用

14th International conference on Digital image processing, ICDIP 2022

作者： Nan, Jingwen Song, Zongxi Lei, Hao Li, Wei Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Shaanxi Xi'an710119 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510657564

Infrared images and visible images can obtain different image information in the same scene, especially in low-light scenes, infrared images can obtain image information that cannot be obtained by visible images. In order to obtain more useful information in the environment such as glimmer, infrared and visible images can be fused. In this paper, an image fusion method based on anisotropic diffusion and fast guided filter is proposed. Firstly, the source images are decomposed into base layers and detail layers by anisotropic dispersion. Secondly, the visible images and the infrared images are passed through the side window Gaussian filter to obtain the saliency map, and then the saliency map is passed through fast guided filter to obtain the fusion weight. Thirdly, the fused base layers and the fused detail layers are reconstructed to obtain the final fusion image. The application of the side window Gaussian filter helps to reduce the artifact information of the fused image. The results of the proposed algorithm are compared with similar algorithms. The fusion results reveal that the proposed method are outstanding in subjective evaluation and objective evaluation, and are better than other algorithms in standard deviation(STD) and entropy(EN), and other quality metrics are close to the optimal comparison algorithm. © 2022 SPIE.

关键词： image fusion

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Fourier-enhanced Implicit Neural Fusion Network for Multispectral and Hyperspectral image Fusion 38

Fourier-enhanced Implicit Neural Fusion Network for Multispe...

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38th conference on Neural Information processing systems, NeurIPS 2024

作者： Liang, Yu-Jie Cao, Zihan Deng, Shangqi Dou, Hong-xia Deng, Liang-Jian University of Electronic Science and Technology of China China Xi'an Jiaotong University China Xihua University China

Recently, implicit neural representations (INR) have made significant strides in various vision-related domains, providing a novel solution for Multispectral and Hyperspectral image Fusion (MHIF) tasks. However, INR is prone to losing high-frequency information and is confined to the lack of global perceptual capabilities. To address these issues, this paper introduces a Fourier-enhanced Implicit Neural Fusion Network (FeINFN) specifically designed for MHIF task, targeting the following phenomena: The Fourier amplitudes of the HR-HSI latent code and LR-HSI are remarkably similar;however, their phases exhibit different patterns. In FeINFN, we innovatively propose a spatial and frequency implicit fusion function (Spa-Fre IFF), helping INR capture high-frequency information and expanding the receptive field. Besides, a new decoder employing a complex Gabor wavelet activation function, called Spatial-Frequency Interactive Decoder (SFID), is invented to enhance the interaction of INR features. Especially, we further theoretically prove that the Gabor wavelet activation possesses a time-frequency tightness property that favors learning the optimal bandwidths in the decoder. Experiments on two benchmark MHIF datasets verify the state-of-the-art (SOTA) performance of the proposed method, both visually and quantitatively. Also, ablation studies demonstrate the mentioned contributions. The code can be available at https://***/294coder/Efficient-MIF. © 2024 Neural information processing systems foundation. All rights reserved.

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Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement 38

Diffusion Model with Cross Attention as an Inductive Bias fo...

引用

38th conference on Neural Information processing systems, NeurIPS 2024

作者： Yang, Tao Lan, Cuiling Lu, Yan Zheng, Nanning National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China Microsoft Research Asia China

Disentangled representation learning strives to extract the intrinsic factors within the observed data. Factoring these representations in an unsupervised manner is notably challenging and usually requires tailored loss functions or specific structural designs. In this paper, we introduce a new perspective and framework, demonstrating that diffusion models with cross-attention itself can serve as a powerful inductive bias to facilitate the learning of disentangled representations. We propose to encode an image into a set of concept tokens and treat them as the condition of the latent diffusion model for image reconstruction, where cross attention over the concept tokens is used to bridge the encoder and the U-Net of the diffusion model. We analyze that the diffusion process inherently possesses the time-varying information bottlenecks. Such information bottlenecks and cross attention act as strong inductive biases for promoting disentanglement. Without any regularization term in the loss function, this framework achieves superior disentanglement performance on the benchmark datasets, surpassing all previous methods with intricate designs. We have conducted comprehensive ablation studies and visualization analyses, shedding a light on the functioning of this model. We anticipate that our findings will inspire more investigation on exploring diffusion model for disentangled representation learning towards more sophisticated data analysis and understanding. © 2024 Neural information processing systems foundation. All rights reserved.

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Low-Light image Enhancement Based on Retinex Reflectance Compensation 36

Low-Light Image Enhancement Based on Retinex Reflectance Com...

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36th International conference on Software Engineering and Knowledge Engineering, SEKE 2024

作者： Zhang, Zhaozheng Wang, Wujun Yang, Weiran Ma, Ningtao Sun, Mingyang Wang, xinxin Ruan, Liangyu Yi, Ru College of Computer Science Inner Mongolia University Hohhot China

ISBN: (纸本)1891706594

Enhancement of low-light images is a low-level visual task aimed at improving the quality of images captured under low-light conditions. In this study, a low-light image enhancement algorithm is proposed by compensating for the reflection loss of illumination components obtained through object reflection. Specifically, the algorithm first utilizes Gaussian filtering to process the value component (V) of the image, separating the illumination component from the reflection component. Then, through a illumination compensation strategy, the illumination component is processed and combined with the reflectance component to synthesize the enhanced value component (V). Finally, an adaptive global balance strategy is applied to optimize the enhanced value component (V) to ensure that the resulting image appears more natural and conforms to human visual perception habits. Experimental results demonstrate the effectiveness and superiority of our method compared to existing traditional processing algorithms and deep learning methods, showing excellent performance in enhancing dark details of images and maintaining natural colors. © 2024 Knowledge systems Institute Graduate School. All rights reserved.

关键词： image enhancement

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Data Optimization Method for Ship Infrared image Recognition

Data Optimization Method for Ship Infrared Image Recognition

引用

2023 International conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Zhang, Haoxiang Liu, Chao Ma, Jianguan Sun, Hui University of Electronic Science and Technology of China School of Mathematical Sciences Chengdu China Beijing China

ISBN: (纸本)9798350312492

This study aims to address two challenging problems that affect the accurate and reliable recognition of ship infrared (IR) images in various scenarios: the interference of radiation highlights from specular reflections of target background sunlight and the difficulty of distinguishing ship targets from background confusion under low light conditions. We propose a data optimisation method for ship IR deep learning recognition, which uses processing tools such as median noise reduction and local histogram equalisation image enhancement to improve the performance and stability of ship IR recognition under the above unfavourable conditions. And the effectiveness of the method is verified on high fidelity mid-wave infrared (MWIR) ship simulation data using deep learning image classification algorithms such as AlexNet, VggNet and EfficientNet. To further demonstrate the effectiveness of the method, research has also adopted model feature gradient visualization technique, which indirectly verifies that our method can effectively improve the predictive reliability of ship recognition models. Overall, the data optimization method proposed in this study provides a feasible solution to address the challenges in ship IR image recognition and can provide a valuable reference for military mission-related research. © 2023 IEEE.

关键词： Infrared radiation

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Boosting Accuracy and Reducing Time in Laser Shooting Practices: Video processing Solutions for Impact Evaluation 1

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8th International conference on Information and Communication Technology for Intelligent systems, ICTIS 2024

作者： Rivas-Lalaleo, David Bautista-Naranjo, Víctor Vayas-Ortega, Germania Iza-Chango, Erika Lema-Jumbo, Pamela Bran, Carlos Universidad de las Fuerzas Armadas—ESPE Sangolquí Ecuador Universidad Indoamerica Ambato Ecuador Instituto Investigación e Innovación en Electrónica Universidad Don Bosco Soyapango El Salvador

ISBN: (数字)9789819757992

ISBN: (纸本)9789819757985

This study explores the most effective method for impact measurement in laser shooting ranges, crucial for security training, accident prevention, and cost reduction. It utilizes video surveillance and image processing algorithms in Python to accurately determine laser impact locations. The research found that employing a single target per silhouette is most efficient, minimizing errors to ±1 impact and enabling heat map generation for feedback. The combination of video surveillance and image processing significantly enhances safety and reduces costs by providing real-time data. The findings advocate for the single target approach due to its precision and the comprehensive insights gained from heat maps, maintaining accuracy within a two-hit margin. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Video signal processing

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Matrix Inversion Accelerated MCU Circuit for image Recognition Pertinent Computation

Matrix Inversion Accelerated MCU Circuit for Image Recogniti...

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2023 International Technical conference on Circuits/systems, Computers, and Communications, ITC-CSCC 2023

作者： Wang, Weisheng Jin, Yu Yuan, Quan Sun, Heming Beijing University of Chemical Technology Beijing China Waseda Research Institute for Science and Engineering Tokyo Japan

ISBN: (纸本)9798350326413

As the most complex computation in the fundamental matrix manipulation, the operation of matrix inversion limits the processing capability in the field of the image recognition and the pertinent application specified circuit. The intensive computation of matrix inversion is mitigated by efficient algorithms such as the Sherman-Morrison formula and accelerated floating-point multiplication and addition, while still suffering from division operations. Here, we present a high-performance floating-point divider circuit, which is capsuled as an instructor in to a general processor Cortex-M3 MCU to efficiently improve the matrix inversion speed in image recognition. The reconstructed MCU circuits are fully implemented on the xilinx Spartan6 FPGA platform. Compared to the xilinx floating point IP, the proposed architecture intensively reduces the division operation time by 82%. © 2023 IEEE.

关键词： image recognition

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image Based Security System in cloud resource Scheduling 5

Image Based Security System in cloud resource Scheduling

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5th International conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Chakraborty, Koushik Dora Pravina, C.T. Arya, Nancy Sharma, Sunil Rakesh, Shanu Kuttan Singh, Arvind Kunar Adamas University Kolkata India Department of Mathematics Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Avadi India Department of Computer Science and Engineering Shree Guru Gobind Singh Tricentenary University Gurugram India Department of Computer Science and Engineering Vivekananda Global University Jaipur India Department of Computer Science and Engineering Chouksey Engineering College Bilaspur Chhattisgarh India Department of Computer Science and Engineering S.V.N.I.E.T Barabanki India

ISBN: (纸本)9798400709418

The popularity of cloud computing in scheduling work processes, particularly logical work processes, is growing. The cloud computing environment may encounter significant issues with execution time and cost during resource allocation, resulting in disruptions in customer support quality. Text Passwords are right now a totally utilized insistence part, however graphical passwords and biometrics are likewise utilized. However, we really want to improve both comfort and security in any system to make it extremely secure. image-based security systems leverage visual information and image processing techniques to enhance security measures. These systems use images or video streams from cameras to monitor, detect, and respond to security threats. Most likely, the framework employs our algorithm to improve performance. It utilizes parts of both Graphical and Text Secret phrase plans. Advanced image processing algorithms analyze captured images for various security-related purposes, such as object detection, facial recognition, and anomaly detection. In contrast to the most well-known scheduling algorithms, such as multi-objective scheduling (MOS) and cost-conscious scheduling, the various scheduling algorithms in this proposed hybrid algorithm mannequin are used to make cloud services secure and highly available to end users. Identifying and verifying individuals based on facial features. This is used for access control, identity verification, and tracking individuals of interest. Analyzing images to detect unauthorized persons or objects in restricted areas, triggering alerts or alarms. In this investigation, we attempt to demonstrate the execution of various algorithm systems for the most well-known three static booking calculations. All the calculations are working out the all-out execution cost and timing of various calculations. © 2023 ACM.

关键词： Security systems

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