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International Conference on Modelling, Identification and Control (ICMIC)

作者： Shuai Dong Zhishen Wang Lei Liu Liuli Ou Yongji Wang Key Lab for Image Processing & Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan China

The H∞ approach is used for the clearance of flight control laws when some parameters in the flight control system vary in a certain range. The proposed H∞ approach is developed from general H∞ theory and is applied to the clearance of a flight control law for a missile. Based on bounded real lemma, two theorems about clearance are deduced, and the clearance problem is transformed to a general linear matrix inequality problem. A BTT missile is chosen as an example to test the proposed method. The simulation result shows that the proposed method is convenient and efficient.

关键词： Aerospace control Uncertainty Mathematical model Uncertain systems Aerodynamics Missiles Control systems

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Stereo matching algorithm based on the combination of matching costs 7

Stereo matching algorithm based on the combination of matchi...

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7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017

作者： Ende, Wang Yalong, Zhu Liangyu, Peng Yijun, Li Tianyao, Wu Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China College of Electrical Engineering Yanshan University Qinhuangdao066004 China School of Metallurgy Northeastern University Shenyang110819 China

ISBN: (纸本)9781538604892

Aiming at solving the problem of low accuracy of weak texture region and disparity discontinuous region and sensitivity to illumination caused by existing local stereo matching algorithm, a new stereo matching algorithm based on the combination of Sum of Absolute Difference algorithm and Absolute Difference of Gradient algorithm is presented here. Using the average of the pixels in the disparity range to apply adaptive weight to the SAD part. The new algorithm can adaptively adjust each part of the cost function in the proportion of the total cost function according to the different texture, illumination characteristics of image. Moreover, we use the semiglobal matching algorithm to calculate the cost of 8 directions, to carry out optimized processing on disparity image, finally a dense disparity map is obtained. The experimental results shows that the proposed method not only improve accuracy of stereo matching, but also has well results in weak texture region and disparity discontinuous region. © 2017 IEEE.

关键词： Textures

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image saliency detection method based on multi-feature maps fusion 4

Image saliency detection method based on multi-feature maps ...

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4th International Conference on Computer Graphics, image, and Virtualization, ICCGIV 2024

作者： Li, Xiaoli Liu, Yunpeng Zhao, Huaici Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Opto-Electronic Information Processing Shenyang China The Key Lab of Image Understanding and Computer Vision Shenyang China Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781510683242

In this research, we introduce an innovative saliency detection algorithm, comprising three essential steps. Firstly, leveraging fully convolutional networks with aggregation interaction modules, we generate an initial saliency map. Secondly, we extract hand-craft and deep features to express the image, then use manifold ranking method to construct saliency maps. Ultimately, by integrating the outcomes from preceding stages, we generate the final saliency map. Experimental findings demonstrate that our method surpasses twelve cutting-edge saliency detection techniques in terms of precision, recall, F-measure, and MAE value metrics." © 2024 SPIE.

关键词： Feature extraction

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A novel saliency detection model based on curvelet transform

A novel saliency detection model based on curvelet transform

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International Conference on Wireless communications and Signal processing (WCSP)

作者： Peiqing Bai Ziguan Cui Zongliang Gan Guijin Tang Feng Liu Image Processing & Image Communication Lab Nanjing University of Posts & Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts & Telecommunications Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781509028610

Visually salient object or region detection in images is an active research field in recent years. Inspired by that curvelets can provide multi-scale sparse representation of objects with edges and textures, in this paper, we propose a novel saliency detection model based on fast discrete curvelet transform (SDCT) to detect more compact salient objects in an image. First, fast discrete curvelet transform is used to acquire multi-scale representation of feature maps in CIElab color space. Then the feature maps are transformed to feature salient maps based on dissimilarity measure between patches in a global manner. Finally, the complementary feature salient maps at each scale and each color channel are merged linearly to obtain unitary saliency map. Experimental results on MSRA saliency benchmark database show that the proposed SDCT model outperforms the most state-of-the-art saliency detection models in spatial and frequency domain with higher overall performance, especially acquires more compact salient object and suppresses background saliency effectively, which is desirable for many computer vision applications.

关键词： Transforms Feature extraction image color analysis Frequency-domain analysis Computational modeling Visualization image edge detection

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Research on image compression algorithm based on the biorthogonal invariant set multiwavelet

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Journal of Computational Information Systems 2015年第16期11卷 5873-5880页

作者： Li, Yongjun Li, Yunsong Liu, Weijia State Key Lab. of Integrated Service Networks Xidian University Xi'an China Joint Laboratory of High Speed Multi-Source Image Coding and Processing Xidian University Xi'an China

On the basis of the theory of the biorthogonal invariant set multiwavelets (BISM) which is established by Micchelli and Xu, a biorthogonal invariant set multi-wavelets (BISM) filter is designed and the algorithms of decomposition and reconstruction of this filter are given in this paper, and it has many characteristics, such as symmetry, compact support, orthogonality and low complexity. In this filter, the self-affine triangle domain is as support interval, and constant function is as scaling function. Advantages such as low algorithm complexity, the energy and entropy in high concentration after transformation, no blocking effect to facilitate parallel computing are analyzed when the biorthogonal invariant sets multiwavelet (BISM) filters are used image compression. Finally, the validity of image compression algorithm based on biorthogonal invariant set multiwavelet is verified by the approximate JPEG2000 framework. © 2015 by Binary Information Press

关键词： image compression

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Adversarial semantic data augmentation for human pose estimation

arXiv

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arXiv 2020年

作者： Bin, Yanrui Cao, Xuan Chen, Xinya Ge, Yanhao Tai, Ying Wang, Chengjie Li, Jilin Huang, Feiyue Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Tencent Youtu Lab China

Human pose estimation is the task of localizing body keypoints from still images. The state-of-the-art methods suffer from insufficient examples of challenging cases such as symmetric appearance, heavy occlusion and nearby person. To enlarge the amounts of challenging cases, previous methods augmented images by cropping and pasting image patches with weak semantics, which leads to unrealistic appearance and limited diversity. We instead propose Semantic Data Augmentation (SDA), a method that augments images by pasting segmented body parts with various semantic granularity. Furthermore, we propose Adversarial Semantic Data Augmentation (ASDA), which exploits a generative network to dynamiclly predict tailored pasting configuration. Given off-the-shelf pose estimation network as discriminator, the generator seeks the most confusing transformation to increase the loss of the discriminator while the discriminator takes the generated sample as input and learns from it. The whole pipeline is optimized in an adversarial manner. State-of-the-art results are achieved on challenging benchmarks. The code has been publicly available at https://***/Binyr/ASDA. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantics

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Crowd Counting Via Multi-Level Regression With Latent Gaussian Maps

Crowd Counting Via Multi-Level Regression With Latent Gaussi...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Yukang Gao Hua Yang Institution of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai key lab of digital media processing and transmission Shanghai China

Crowd counting still confronts two primary challenges: limited ability to deal with cross density levels caused by fixed density maps and lack of fine-grained or coarse-grained guidance for density estimation. In this paper, a novel end-to-end crowd counting framework via multi-level regression with latent Gaussian maps is proposed, which is consisted of GaussianNet, EstimateNet and Discriminator. GaussianNet is composed of masked Gaussian convolutional blocks and vanillia convolutional layers, to generate latent Gaussian maps adaptively for various density levels. The latent Gaussian maps are then treated as the ground truth density maps for EstimateNet, which outputs density estimations and follows the principle of adversarial learning with Discriminator. Moreover, multi-level losses are combined for density map regression guidance. Extensive experiments on the major public datasets outperform state-of-the-art ones, illustrating the superior validity of the proposed framework.

关键词： Training Convolution Conferences Estimation Acoustics Bayes methods Task analysis

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Attentive semantic exploring for manipulated face detection

arXiv

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arXiv 2020年

作者： Chen, Zehao Yang, Hua Institution of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Degital Media Processing and Transmission Shanghai China

Face manipulation methods develop rapidly in recent years, whose potential risk to society accounts for the emerging of researches on detection methods. However, due to the diversity of manipulation methods and the high quality of fake images, detection methods suffer from a lack of generalization ability. To solve the problem, we find that segmenting images into semantic fragments could be effective, as discriminative defects and distortions are closely related to such fragments. Besides, to highlight discriminative regions in fragments and to measure contribution to the final prediction of each fragment is efficient for the improvement of generalization ability. Therefore, we propose a novel manipulated face detection method based on Multilevel Facial Semantic Segmentation and Cascade Attention Mechanism. To evaluate our method, we reconstruct two datasets: GGFI and FFMI, and also collect two open-source datasets. Experiments on four datasets verify the advantages of our approach against other state-of-the-arts, especially its generalization ability. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantics

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Blurring Length Estimation Using Ringing Artifacts in a Deblurred image

Blurring Length Estimation Using Ringing Artifacts in a Debl...

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2011 International Conference on image Analysis and Signal processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

作者： Hong Liu Shuangxue Yang Benyong Liu Xiang Liao School of Computer Science and Information Institute of Intelligent Information Processing Guizhou Key Lab of Sound-Image Material Examination and Authentication The Ministry of Public Security of PR

ISBN: (纸本)9781612848792

The restoration quality of a motion-blurred image is highly dependent on the estimation accuracy of the motion blurring parameter. This manuscript presents a novel and precise method for estimation of the motion blurring length, wherein the ringing artifact amount of a deblurred image is measured by energy proportion contained in appropriate frequency bands, and a blurring length with minimum ringing artifact amount is taken as the optimal estimation of the true blurring length. Experimental results show good performance of the proposed algorithm in motion blurring length estimation.

关键词： blurred image restoration blurring kernel motion blur ringing artifacts

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SAR image multiclass segmentation using a multiscale and multidirection triplet Markov fields model in nonsubsampled contourlet transform domain

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Information Fusion 2013年第4期14卷 441-449页

作者： Yan Wu Peng Zhang Ming Li Qiang Zhang Fan Wang Lu Jia Remote Sensing Image Processing and Fusion Group School of Electronic Engineering Xidian University P.O. Box 140 Xi’an Shaanxi 710071 China National Key Lab. of Radar Signal Processing Xidian University Xi’an 710071 China

Triplet Markov fields (TMFs) model recently proposed is to deal with nonstationary image segmentation and has achieved promising results. In this paper, we propose a multiscale and multidirection TMF model for nonstationary synthetic aperture radar (SAR) image multiclass segmentation in nonsubsampled contourlet transform (NSCT) domain, named as NSCT-TMF model. NSCT-TMF model is capable of capturing the contextual information of image content in the spatial and scale spaces effectively by the construction of multiscale energy functions. And the derived multiscale and multidirection likelihoods of NSCT-TMF model can capture the dependencies of NSCT coefficients across scale and directions. In this way, the proposed model is able to achieve multiscale information fusion in terms of image configuration and features in underlying labeling process. Experimental results demonstrate that due to the effective propagation of the contextual information, NSCT-TMF model turns out to be more robust against speckle noise and improves the performance of nonstationary SAR image segmentation.

关键词： SAR image multiclass segmentation NSCT-TMF model NSCT-HMT NSCT-TMF energy function Multiscale information fusion

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