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Radon transform-based motion blurred silkworm pupa image restoration

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International Journal of Agricultural and Biological Engineering 2019年第2期12卷 152-159页

作者： Dan Tao Zhengrong Wang Guanglin Li Guangying Qiu College of Engineering and Technology Southwest UniversityChongqing 400715China

As for machine vision-based intelligent system in the application of discriminating and sorting the sex of silkworm pupae,the tail gonad was the unique physiological ***,motion blur,resulting from the live silkworm pupa’s writhing motion at the moment of capturing image,could lose textures and structures(such as edge and tail gonad etc.)dramatically,which casted great challenges for sex *** increase the image quality and relieve the difficulty of discrimination caused by motion blur,an effective approach that including three stages was proposed in this *** the image prediction stage,first sharp edges were acquired by using filtering *** the initial blur kernel was computed with Gaussian *** coarse version latent image was deconvoluted in the Fourier *** the kernel refinement stage,the Radon transform was applied to estimate the accurate *** the final restoration step,a TV-L1 deconvolution model was carried out to obtain a better *** experimental results showed that benefiting from the prediction step and kernel refinement step,the kernel was more accurate and the recovered image contained much more *** revealed that the proposed method was useful in removing the motion ***,the method could also be applied to other fields.

关键词： silkworm pupa image restoration radon transform machine vision motion blur deblurring

Blind-restoration-based blind separation method for permuted motion blurred images

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Journal of Shanghai University(English Edition) 2011年第2期15卷 79-84页

作者：方勇王伟 Key Laboratory of Specialty Fiber Optics and Optical Access Networks School of Communication and Information Engineering Shanghai University

A novel single-channel blind separation algorithm for permuted motion blurred images is proposed by using blind restoration in this paper. Both the motion direction and the length of the point spread function （PSF） are estimated by Radon transformation and extrema a detection. Using the estimated blur parameters, the permuted image is restored by performing the L-R blind restoration method. The permutation mixing matrices can be accurately estimated by classifying the ringing effect in the restored image, thereby the source images can be separated. Simulation results show a better separation efficiency for the permuted motion blurred image with various permutation operations. The proposed algorithm indicates a better performance on the robustness against Gaussian noise and lossy JPEG compression.

关键词： permuted image blind source separation (BSS) motion blur blind restoration single-channel

motion blurred image restoration based on flight control system

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Motion blurred image restoration based on flight control sys...

Blind image deconvolution for single motion-blurred image

第37届中国控制会议

作者： Ran Zhao Dongliang Liu Feng Qu Xu Zhang Academy of Automation Hangzhou Dianzi University Wolong Electric CO. LTD

In recent years, the applications of Aerial UAV are more and more extensive. The aerial system is subject to the impact of the relative movement, posture changes and the atmosphere, which results in low clarity of the captured image. Based on the image blur phenomenon caused by UAV flight, a function is introduced as its coefficient in Lucy-Richardson（LR） image restoration algorithm, which could effectively protect edge details of the image. The results of image quality evaluation show that the improved LR algorithm can effectively suppress the noise in the image and improve the clarity of the image.

关键词： Flight control system image restoration motion blur LR algorithm Evaluation of Image quality

来源： cnki会议评论

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The Journal of China Universities of Posts and Telecommunications 2010年第3期17卷 104-109页

作者： SUN Shao-jie WU Qiong Li Guo-hui College of Information System and Management National University of Defense Technology Changsha 410073 China Airforce Training Equipment Institute Beijing 100195 China

motion blur due to camera shake during exposure is one of the most common reasons of image degradation, which usually reduces the quality of photographs seriously. Based on the statistical properties of the natural image＇s gradient and the blur kernel, a blind deconvolution algorithm is proposed to restore the motion-blurred image caused by camera shake, adopting the variational Bayesian estimation theory. In addition, the ring effect is one problem that is not avoided in the process of image deconvolution, and usually makes the visual effect of the restored image badly. So a dering method is put forward based on the sub-region detection and fuzzy filter. Tested on the real blurred photographs, the experimental results show that the proposed algorithm of blind image deconvolution can remove the camera-shake motion blur from the degraded image effectively, and can eliminate the ring effect better, while preserve the edges and details of the image well.

关键词： blind image deconvolution motion blur camera shake ring effect

Research on motion Estimation Algorithm of Star Point Based on Nonlinear Gaussian Fitting

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Journal of Shanghai Jiaotong university(Science) 2018年第4期23卷 562-567页

作者： WANG Chaoran BAO Qilian ZHENG Xunjiang SUN Shuodong School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Aerospace Control Technology Institute Shanghai 201109 China

The energy distribution model of motion blurred star point is *** distribution of the star point approximates to a two-dimensional(2 D) Gaussian distribution under *** multi-parameter nonlinear Gaussian fitting methods(GFMs) are proposed,and the relationship between fitting parameters and motion blur parameters is *** of the parameters of motion blur by fitting parameters is calculated to realize the error compensation of the motion *** simulation results show the effectiveness and accuracy.

关键词： star sensors centroid calculation Gaussian fitting method(GFM) motion blur

Single-pixel imaging of a moving object with multi-motion

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Chinese Optics Letters 2024年第10期22卷 33-38页

作者： Pengcheng Ji Qingfan Wu Shengfu Cao Huijuan Zhang Zhaohua Yang Yuanjin Yu School of Automation Beijing Institute of TechnologyBeijing 100081China School of Instrumentation Science and Optoelectronics Engineering Beijing UniversityBeijing 100191China MIIT Key Laboratory of Complex-field Intelligent Sensing Beijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314019China

motion blur restoration is essential for the imaging of moving objects,especially for single-pixel imaging(SPI),which requires multiple *** reconstruct the image of a moving object with multiple motion modes,we propose a novel motion blur restoration method of SPI using geometric moment *** design a novel localization method that uses normalized differential first-order moments and central moment patterns to determine the object's translational position and rotation angle ***,we perform motion compensation by using shifting Hadamard *** method effectively improves the detection accuracy of multiple motion modes and enhances the quality of the reconstructed *** perform simulations and experiments,and the results validate the effectiveness of the proposed method.

关键词： single-pixel imaging motion blur motion estimation and compensation

Method for predicting motion artifacts of plasma display panels

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Journal of Southeast University(English Edition) 2007年第1期23卷 43-46页

作者：张宇宁 Teunissen Kees 雷威张晓兵东南大学电子科学与工程学院南京210096 飞利浦消费电子集团创新实验室

A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based on the measured temporal light properties of the display for each gray level and each phosphor. Both the effect of subfield arrangement and phosphor decay are involved. A novel algorithm is proposed to improve the calculation speed. The simulation model manages to predict the appearance of the motion image perceived by a human with a still image. The results are validated by a set of perceptual evaluation experiments. This rapid and accurate prediction of motion artifacts enables objective characterization of the PDP performance in this aspect.

关键词： plasma display panels motion artifacts dynamic false contour motion blur

Camera Independent motion Deblurring in Videos Using Machine Learning

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Journal of Intelligent Learning Systems and Applications 2023年第4期15卷 89-107页

作者： Tyler Welander Ronald Marsh Bryce Gruber Department of Electrical Engineering and Computer Science University of North Dakota Grand Forks North Dakota USA

In this paper, we will be looking at our efforts to find a novel solution for motion deblurring in videos. In addition, our solution has the requirement of being camera-independent. This means that the solution is fully implemented in software and is not aware of any of the characteristics of the camera. We found a solution by implementing a Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) hybrid model. Our CNN-LSTM is able to deblur video without any knowledge of the camera hardware. This allows it to be implemented on any system that allows the camera to be swapped out with any camera model with any physical characteristics.

关键词： motion blur Video Convolutional Neural Network Long Short-Term Memory AirSim OpenCV

Multi-Dimension Support Vector Machine Based Crowd Detection and Localisation Framework for Varying Video Sequences

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Circuits and Systems 2016年第11期7卷 3565-3588页

作者： Manoharan Mahalakshmi Radhakrishnan Kanthavel Divakaran Thilagavathy Dinesh Velammal Engineering College Anna University Chennai India

In this paper, we propose a novel method for anomalous crowd behaviour detection and localization with divergent centers in intelligent video sequence through multiple SVM (support vector machines) based appearance model. In multi-dimension SVM crowd detection, many features are available to track the object robustly with three main features which include 1) identification of an object by gray scale value, 2) histogram of oriented gradients (HOG) and 3) local binary pattern (LBP). We propose two more powerful features namely gray level co-occurrence matrix (GLCM) and Gaber feature for more accurate and authenticate tracking result. To combine and process the corresponding SVMs obtained from each features, a new collaborative strategy is developed on the basis of the confidence distribution of the video samples which are weighted by entropy method. We have adopted subspace evolution strategy for reconstructing the image of the object by constructing an update model. Also, we determine reconstruction error from the samples and again automatically build an update model for the target which is tracked in the video sequences. Considering the movement of the targeted object, occlusion problem is considered and overcome by constructing a collaborative model from that of appearance model and update model. Also if update model is of discriminative model type, binary classification problem is taken into account and overcome by collaborative model. We run the multi-view SVM tracking method in real time with subspace evolution strategy to track and detect the moving objects in the crowded scene accurately. As shown in the result part, our method also overcomes the occlusion problem that occurs frequently while objects under rotation and illumination change due to different environmental conditions.

关键词： Multiple Support Vector Machine Crowd Detection motion blur Collaborative Model Gaber Feature