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

共 16349 条记录，以下是4881-4890 订阅

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Single-image Blind Deconvolution Using Gradient Saliency Map 36

Single-Image Blind Deconvolution Using Gradient Saliency Map

引用

第36届中国控制会议

作者： xiaoguang Di Lei Yin Control and Simulation Center Harbin Institute of Technology

ISBN: (纸本)9781538629185

Single-image blind deconvolution is one of the most challenging fields in image processing which restores a sharp image from its blurred *** blind deconvolution algorithms have made significant ***,the restoration of blurred images with little scale edges and periodic textures is still a hard *** solve this problem,this paper proposes a new normalized sparse regularization blind deconvolution algorithm,which uses a gradient saliency map to prohibit the image small structures on image blurry kernel ***,salient detection is performed to select the important area which conforms with the human vision system and generates a binary mask to screen out useful ***,the normalized sparse regularization blind deconvolution method is applied to obtain accurate blur kernel and recover the sharp ***,the experiment results show that the algorithm can effectively deblur the degraded image on different scenarios.

关键词： blind deconvolution sparse regularization salient detection gradient map

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Predicting Exploitation Success on Compressed imagery through Common image Quality Metrics: An Initial Look 6

Predicting Exploitation Success on Compressed Imagery throug...

引用

conference on Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI

作者： McGuinness, Christopher D. Hytla, Patrick C. Priddy, Kevin L. Univ Dayton Res Inst Dayton OH 45469 USA Air Force Life Cycle Management Ctr Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9781628415803

imagery from unmanned aerial systems (UAS) needs compression prior to transmission to a receiver for further processing. Once received, automated image exploitation algorithms, such as frame-to-frame registration, target tracking, and target identification, are performed to extract actionable information from the data. Unfortunately, in a compress-then-analyze system, exploitation algorithms must contend with artifacts introduced by lossy compression and transmission. Identifying metrics that enable compression engines to predict exploitation degradation could allow encoders the ability of tailoring compression for specific exploitation algorithms. This study investigates the impact of H.264 and JPEG2000 compression on target tracking through the use of a multi-hypothesis blob tracker. Used quality metrics include PSNR, VIF, and IW-SSIM.

关键词： Compression blob detection H.264 JPEG2000 quality tracking

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S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning 36

S-Prompts Learning with Pre-trained Transformers: An Occam's...

引用

36th conference on Neural Information processing systems (NeurIPS)

作者： Wang, Yabin Huang, Zhiwu Hong, xiaopeng Xi An Jiao Tong Univ Xian Peoples R China Singapore Management Univ Singapore Singapore Harbin Inst Technol Harbin Peoples R China Pengcheng Lab Shenzhen Peoples R China

ISBN: (纸本)9781713871088

State-of-the-art deep neural networks are still struggling to address the catastrophic forgetting problem in continual learning. In this paper, we propose one simple paradigm (named as S-Prompting) and two concrete approaches to highly reduce the forgetting degree in one of the most typical continual learning scenarios, i.e., domain increment learning (DIL). The key idea of the paradigm is to learn prompts independently across domains with pre-trained transformers, avoiding the use of exemplars that commonly appear in conventional methods. This results in a win-win game where the prompting can achieve the best for each domain. The independent prompting across domains only requests one single cross-entropy loss for training and one simple K-NN operation as a domain identifier for inference. The learning paradigm derives an image prompt learning approach and a novel language-image prompt learning approach. Owning an excellent scalability (0.03% parameter increase per domain), the best of our approaches achieves a remarkable relative improvement (an average of about 30%) over the best of the state-of-the-art exemplar-free methods for three standard DIL tasks, and even surpasses the best of them relatively by about 6% in average when they use exemplars. Source code is available at https://***/iamwangyabin/S-Prompts.

关键词： Deep neural networks

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The influence of image gamuts on cross-media colour image reproduction

The influence of image gamuts on cross-media colour image re...

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Final Program and Proceedings of the 8th IS and T/SID Color Imaging conference: Color Science, systems and Applications

作者： Morovic, Ján Sun, Pei-Li Colour and Imaging Institute University of Derby Derby United Kingdom

The present paper aims to investigate the influence of image gamuts on cross-media colour image reproduction by creating a set of images that have this image characteristic perturbed in a known way. This is done using the following two approaches: First, by selecting a single image and obtaining variations of it which have different colour gamuts. Second, by creating a pair of image sets whereby the images in the first set differ in colour gamut and the images of the second set are transformations of the first set of images so that all the images have the same gamut. Reproducing these images using a range of gamut mapping algorithms (GMAs), it can be seen whether variations in gamut and the difference between multi- and equi-gamut sets result in difference of performance. The results of these experiments then show that image gamuts have no significant effect on colour gamut mapping.

关键词： Color image processing

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Automatic Safety Helmet Wearing Detection 7

Automatic Safety Helmet Wearing Detection

引用

7th IEEE Annual International conference on CYBER Technology in Automation, Control, and Intelligent systems (CYBER)

作者： Li, Kang Zhao, xiaoguang Bian, Jiang Tan, Min Univ Chinese Acad Sci Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China

ISBN: (纸本)9781538604908

Surveillance is very essential for the safety of power substation. The detection of whether wearing safety helmets or not for perambulatory workers is the key component of overall intelligent surveillance system in power substation. In this paper, a novel and practical safety helmet detection framework based on computer vision, machine learning and image processing is proposed. In order to ascertain motion objects in power substation, the ViBe background modelling algorithm is employed. Moreover, based on the result of motion objects segmentation, real-time human classification framework C4 is applied to locate pedestrian in power substation accurately and quickly. Finally, according to the result of pedestrian detection, the safety helmet wearing detection is implemented using the head location, the color space transformation and the color feature discrimination. Extensive compelling experimental results in power substation illustrate the efficiency and effectiveness of the proposed framework.

关键词： Safety Substations Feature extraction image color analysis Support vector machines Surveillance Classification algorithms"

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Meta-image Navigation Augmenters for Unmanned Aircraft systems (MINA for UAS)

Meta-Image Navigation Augmenters for Unmanned Aircraft Syste...

引用

conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) systems and Applications X

作者： Celik, Koray Somani, Arun K. Schnaufer, Bernard Hwang, Patrick Y. McGraw, Gary A. Nadke, Jeremy Iowa State Univ Elect & Comp Engn Ames IA USA Rockwell Collins Adv Technol Ctr Cedar Rapids IA 52227 USA

ISBN: (纸本)9780819495044

GPS is a critical sensor for Unmanned Aircraft systems (UASs) due to its accuracy, global coverage and small hardware footprint, but is subject to denial due to signal blockage or RF interference. When GPS is unavailable, position, velocity and attitude (PVA) performance from other inertial and air data sensors is not sufficient, especially for small UASs. Recently, image-based navigation algorithms have been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. Performing absolute navigation with real-time aerial images requires georeferenced data, either images or landmarks, as a reference. Georeferenced imagery is readily available today, but requires a large amount of storage, whereas collections of discrete landmarks are compact but must be generated by pre-processing. An alternative, compact source of georeferenced data having large coverage area is open source vector maps from which meta-objects can be extracted for matching against real-time acquired imagery. We have developed a novel, automated approach called MINA (Meta image Navigation Augmenters), which is a synergy of machine-vision and machine-learning algorithms for map aided navigation. As opposed to existing image map matching algorithms, MINA utilizes publicly available open-source geo-referenced vector map data, such as OpenStreetMap, in conjunction with real-time optical imagery from an on-board, monocular camera to augment the UAS navigation computer when GPS is not available. The MINA approach has been experimentally validated with both actual flight data and flight simulation data and results are presented in the paper.

关键词： Map-Aided Georeferenced Vector Map image Navigation GPS Denied Machine Learning UAS OpenStreetMap Monocular

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Computational Imaging Method in MIMO Radar With Nonideal Orthogonal Waveforms 3

Computational Imaging Method in MIMO Radar With Nonideal Ort...

引用

3rd International conference on Signal image processing and Communication, ICSIPC 2023

作者： Yu, xiaohan Hu, xiaowei Air and Missile Defense College Air Force Engineering University Shaanxi Xi’an710051 China

ISBN: (纸本)9781510670945

Most of the existing imaging methods in MIMO radar require that the transmitting waveforms are orthogonal, the array architecture is regular and the sampling is uniform. In this paper, a computational imaging method for MIMO radar is proposed. The new imaging method is suitable for the case of nonideal orthogonal waveforms, irregular array architecture and nonuniform samplings. What is more, through the process of truncated singular value, the proposed method is robust even though the sensing matrix is ill-conditioned. The effectiveness of the proposed method is demonstrated by using the simulated data and the electromagnetic computation data. © 2023 SPIE.

关键词： MIMO systems

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Automatic target recognition of millimeter-wave radar based on deep learning 2

Automatic target recognition of millimeter-wave radar based ...

引用

2021 2nd International conference on Signal processing and Computer Science, SPCS 2021

作者： Wang, Chen xi Chen, xin Zou, Han Yu He, Song Tang, xiao Air Force Early Warning Academy Hu Bei Wu Han430014 China

All-day, all-weather wide-area search discovery target capability makes radar become a key piece of equipment in many military and civilian fields, and plays an indispensable role in tasks such as identification and positioning. However, at the same time, the current radar equipment generally relies on complex signal processing systems, and designing artificial feature extraction algorithms based on prior knowledge is both difficult and time-consuming, and it is difficult to fine-grained identify the target. In recent years, deep learning has been widely used in the radar field with its strong adaptability and strong self-learning ability. The paper presents a radar Doppler image based on YOLO v3 algorithm. With Millimeter-Wave radar distance-doppler reflectance image as input and darknet-53 as the feature extraction network, the automatic detection of vehicle millimeter wave radar cars, bicycles, pedestrians and trucks was realized, and the average detection accuracy reached 84.3%, providing new ideas and technical support for the development of intelligent radar and radar target detection. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Millimeter waves

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Strategies to model complex architectural objects using Unmanned Aerial systems (UAS) 6

Strategies to model complex architectural objects using Unma...

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6th CSCE-CRC International Construction Specialty conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual conference and General Meeting 2017

作者： Wang, xi Dadi, Gabriel B. University of Kentucky United States

ISBN: (纸本)9781510878419

The use of Unmanned Aerial systems (UAS) and photogrammetry are becoming attractive for creating three-dimensional (3D) models in many surveying applications of construction engineering. Although several researchers have introduced and evaluated UAS and photogrammetry technologies' potential in various applications such as earthwork surveying and building components modeling, there is still a lack of a comprehensive investigation of the UAS and photogrammetry applications from the perspective of practice. This paper aims at identifying and summarizing the optimal strategies of 3D mapping and modeling for existing buildings regarding the efficiency and accuracy from field experiments at a facility in Kentucky. The strategies discussed in this paper involve the development of the UAS images acquisition plans and the selection of data processing options for point cloud model using the Pix4D software program. For a complex structure, the efficiency relates to the number of image locations needed to model the object with its geometrically complex components and the number of subprojects that will be merged for faster processing. The accuracy is evaluated through the measurements comparisons and the effect of visualizations. The experiment results and illustrations are useful as a reference for researchers and practitioners in need of guidance to efficiently implement UAS and photogrammetry technology for their applications. © CSCE-CRC International Construction Specialty conference 2017 - Held as Part of the Canadian Society for Civil Engineering Annual conference and General Meeting *** rights reserved.

关键词： Efficiency

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Augmenting graph cut with TV-L1 approach for robust stereo matching

Augmenting graph cut with TV-L1 approach for robust stereo m...

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2011 International conference on image Information processing, ICIIP 2011

作者： Jama, Arshad Rakshit, Subrata Centre for AI and Robotics Bangalore India

ISBN: (纸本)9781612848617

Stereo matching plays a significant role in various vision based systems including 3D reconstruction, robot localization, mapping and navigation and it has been an intense area of research for many years. In the last decade, with the increase in processing power and reduction in the camera cost, the stereo systems have found many new applications. In this paper, we present a stereo matching algorithm which computes the disparities with sub-pixel accuracy. The proposed method combines graph cut based stereo matching method with total variation approach to achieve improved accuracy. We demonstrate the robust performance of the algorithm on the large scale Middlebury benchmark. The algorithm has also been tested on real data and the results compare favorably with the similar category state-of-the-art algorithms. © 2011 IEEE.

关键词： Stereo image processing

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