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检索条件"任意字段=2nd Conference on Image Reconstruction from Incomplete Data"

共 4214 条记录，以下是121-130 订阅

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image Super Resolution reconstruction Algorithm Based on Deep Learning 2

Image Super Resolution Reconstruction Algorithm Based on Dee...

引用

2nd IEEE International conference on Information Communication and Signal Processing (ICICSP)

作者： Dou, Huijing Zhang, Wenqian Liang, Xiao Beijing Univ Technol Dept Informat Beijing Peoples R China

ISBN: (纸本)9781728151021

Super Resolution Convolutional Neural Network (SRCNN) solves the problems of poor robustness and complex calculation of traditional image super-resolution reconstruction algorithm, but its training data set and the number of layers of neural network is relatively small, and the edge and texture detail information are not handled well. For the above problems, the Maxout activation function is adopted in this paper to avoid the problems encountered by traditional activation functions such as gradient disappearance or overflow. Then the combination of Maxout and Dropout can train large data set and deepen neural network. Experimental results show that, compared with the classical algorithm, the algorithm proposed in this paper can train a large amount of data, improve the quality of reconstructed images and the generalization ability of the network model, and can enhance the robustness of the model.

关键词： super resolution reconstruction convolutional neural network maxout activation function dropout

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A practical updating background method in moving target detection

A practical updating background method in moving target dete...

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2012 2nd International conference on Consumer Electronics, Communications and Networks, CECNet 2012

作者： Song, Junfang Huang, Cao Xue, Ru School of Information Engineering Tibet Nationalities Institute Xianyang Shaanxi 712082 China

ISBN: (纸本)9781457714153

Background subtraction is a powerful mechanism typically for segmenting moving regions in image sequences taken from a data acquisition system. It compares each new image to a model of the scene background image. In this paper, we present a novel method for the reconstruction of background image in background subtraction. This method firstly calculates the difference of two neighboring images, then deals with this result to determine whether the background image needs to be updated and finally reconstructs the background image by a simple weight formula. The experiment result shows that the proposed method could update background image quickly and timely in the scene of traffic flow monitoring. Using this method we can get a more accurate background, which is conducive to the segmentation of the target. © 2012 IEEE.

关键词： image reconstruction

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CS Regularized SENSE pMRI reconstruction via Interferometric Modulation 2

CS Regularized SENSE pMRI Reconstruction via Interferometric...

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2nd IEEE International conference on Wireless Communications, Signal Processing and Networking (WiSPNET)

作者： Islam, Sheikh Rafiul Maity, Santi P. Ray, Ajoy Kumar Neotia Inst Technol Management & Sci South 24 Parganas 743368 W Bengal India Indian Inst Engn Sci & Technol Howrah 711103 W Bengal India

ISBN: (纸本)9781509044429

Compressed Sensing (CS) or Compressive Sampling offers an improved data acquisition rate for Parallel Magnetic Resonance Imaging (pMRI) systems to achieve reduced scanning time. In pMRI, the optimization of image quality is done through appropriate selection/ placement of coils according to the anatomy of the object to be imaged. This paper proposes an efficient interferometric modulation scheme for radio frequency (RF) receiver coils of parallel MRI (pMRI) that produces magnetization field over the object. The modulated magnetization field is beneficial for improving estimation accuracy of sensitivity profiles which enhance reconstruction quality at high data acquisition rate. A CS regularized sensitivity encoding approach is used as reconstruction technique in which the required MR image is provided through an iterative optimization process from the under-sampled observed k-space data. Extensive simulation results show a significant reduction in artifacts and thereby consequent visual improvement in the reconstructed MR images are achieved even when a high rate of acceleration factor is used. Simulation results also demonstrate that the proposed method outperforms some state-of-the-art pMRI methods, both in terms of subjective and objective quality assessment for the reconstructed images.

关键词： Compressed sensing interferometer parallel imaging pMRI image reconstruction SENSE

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3-D signal reconstruction from noisy projection data for stochastic objects as a generalization of Gaussian mixture parameter estimation

3-D signal reconstruction from noisy projection data for sto...

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conference on image reconstruction from incomplete data VI

作者： Zheng, Yili Doerschuk, Peter C. Univ Calif Berkeley Lawrence Berkeley Lab Computat Res Div Berkeley CA 94720 USA

A statistical estimation problem for determining 3-D reconstructions from a single 2-D projection image of each of multiple objects when the objects are heterogeneous is described. The method is based on a Gaussian mi... 详细信息

ISBN: (纸本)9780819482969

关键词： statistical inverse problem statistical signal reconstruction tomography cryo electron microscopy virus structure

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Single image Super-Resolution reconstruction Network with Dual Attention Mechanism 2

Single Image Super-Resolution Reconstruction Network with Du...

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2nd IEEE International conference on Big data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021

作者： Huang, Youwen Tang, Xin Zhou, Bin Jiangxi University of Science and Technology College of Information Engineering Ganzhou China

ISBN: (纸本)9780738131221

Aiming at the problem that the solution space of mapping function from low resolution image to high resolution image is extremely large, which makes it difficult for super-resolution reconstruction models to generate detailed textures, this paper proposes a single image super resolution reconstruction network combining dual attention mechanism. The improved U-Net network model is used as the basic structure, and the data enhancement method is introduced to increase the diversity of samples. The encoder is composed of a convolution layer and an adaptive parameter linear rectifier function (Dynamic ReLU). The image size is decreased step by step through the subsampling operation. The decoder part was composed of Residual Dual Attention Module (RDAM) and Pixelshuffle Module. The image was enlarged gradually through the up-sampling operation, and dual regression loss was introduced to enhance the network constraints. The experimental results show that the proposed method can make the reconstructed image texture more detailed and reduce the possible solution space of the mapping function effectively. © 2021 IEEE.

关键词： image texture

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Comparison of Medical image 3D reconstruction Rendering Methods for Robot-Assisted Surgery 2

Comparison of Medical Image 3D Reconstruction Rendering Meth...

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2nd International conference on Advanced Robotics and Mechatronics (ICARM)

作者： Pan, Zhaoxi Tian, Song Guo, Mengzhao Zhang, Jianxun Yu, Ningbo Xin, Yunwei Nankai Univ Coll Comp & Control Engn Tianjin 300350 Peoples R China Nankai Univ Tianjin Key Lab Intelligent Robot Tianjin 300350 Peoples R China

ISBN: (纸本)9781538632604

In modern medicine, 3D reconstruction plays an important role in improving the accuracy of disease detection and treatment especially in the process of robot-assisted surgery. Accordingly, the choice of 3D reconstruction method is of great importance, which provides real-time visualization. This study analyses and compares two types of methods in 3D medical image reconstruction and visualization: Surface Rendering and Volume Rendering. To be more specific, four algorithms including Contour Filter (CF), Marching Cubes (MC), Composite Volume Rendering (CVR) and Texture Mapping Hardware (TMH) were implemented and compared from the perspective of the rendering effect, speed and interactivity, in which the former two algorithms belong to the concept of Surface Rendering and the latter two algorithms are in the range of Volume Rendering. These algorithms were implemented by Microsoft Visual Studio with Visualization Toolkit (VTK) to reconstruct the 3D images of patients CT image data. The mechanism and realization of these algorithms were described, and the merits and shortcomings of these different rendering methods were compared. Based on the comparison results, the 3D reconstruction and rendering method can be determined according to the specific requirements of robot-assisted surgery.

关键词： 3D reconstruction VTK Surface Rendering Volume Rendering

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Simple building reconstruction from lidar data and aerial imagery

Simple building reconstruction from lidar data and aerial im...

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2012 2nd International conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012

作者： Wang, Shugen Gou, Qiuyuan Sun, Mingwei School of Remote Sensing and Information Engineering Wuhan University 129 Luoyu Road Wuhan 430079 China

ISBN: (纸本)9781467308731

This paper presents a method for simple regular building reconstruction from Lidar data and aerial images. The method includes three steps: the detection of building region from Lidar data, the extraction of building features and 3D reconstruction. In the first step, we extract initial building regions through the classification of Lidar data. In the second step, a laser point cluster is recognized as an isolated building object, and then the initial building positions are obtained with the method of tracing the outlines of points, the initial positions combine with the edges of the image to extract more reliable building' edges;In the third step, we use the edges of building and the elevation value of roof from Lidar data to reconstruct geometric model of building and display them. © 2012 IEEE.

关键词： Buildings

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Pet image reconstruction using ANN-EM method 2

Pet image reconstruction using ANN-EM method

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2nd International conference on Advanced Computing and Communication Systems, ICACCS 2015

作者： Iniyatharasi, P. Rajasekaran, M. Pallikonda Arun Prasath, T. Kannan, S. Department of ECE Kalasalingam University Virudhunagar Tamil Nadu India

ISBN: (纸本)9781479964383

Imaging is a broad field which covers all aspects of the analysis, modification, compression, visualization, and generation of images. There are at least two major areas in imaging science in which applied mathematics has a strong impact: image processing, and image reconstruction. In image processing the input is a (digital) image such as a photograph, while in image reconstruction the input is a set of data. image processing techniques treat an image and apply numerical algorithms to either improve the given image or to extract different features of it. image reconstruction refers to the technique used to create an image of the interior of a body (or region) non-invasively, from data collected on its boundary. Current imaging problems deal with the image quality and the computational tools used to create the image. The performance of ANN-EM algorithm is compared with the simultaneous version of co-ordinate descent algorithm (CD) and de-noising algorithm. Algorithms are compared in terms of prediction and parameters like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Root Mean Square Error (RMSE) and Elapsed time for the algorithms. The results shows that ANN-EM based algorithm provides better reconstructed time compared to other two techniques. © 2015 IEEE.

关键词： Mean square error

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image restoration techniques for partially coherent 2-D LADAR imaging systems

Image restoration techniques for partially coherent 2-D LADA...

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conference on image reconstruction from incomplete data III

作者： MacDonald, A Cain, S USAF Inst Technol Dept Elect Engn Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819455008

A new image reconstruction algorithm is constructed to remove the effect of atmospheric turbulence on motion-compensated frame averaged data collected by a laser illuminated 2-D imaging system. The algorithm simultaneously computes a high resolution image and Fried's seeing parameter via a MAP (Maximum a Priori) estimation technique. This blind deconvolution algorithm differs from other techniques in that it parameterizes the unknown component of the impulse response as an average short-exposure point spread function. The utility of the approach lies in its application to laser illuminated imaging where laser speckle and turbulence effects dominate other sources of error and the field of view of the sensor greatly exceeds the isoplanatic angle.

关键词： Speckle Imaging systems reconstruction algorithms image restoration Sensors Detection and tracking algorithms Coherence (optics) Optical transfer functions Signal detection LIDAR

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Fusion of Remote Sensing data of the ChangBai Mountain Area Based on the Principal Component and Wavelet Transformation

Fusion of Remote Sensing Data of the ChangBai Mountain Area ...

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2nd IEEE International conference on Advanced Computer Control

作者： Zhu, Feng ZhiMingLiu LiuYang WangMowei XuShi JiangHaiLiang NE Normal Univ Urban & Environm Sci Inst Changchun Peoples R China

ISBN: (纸本)9781424458479

The resource of remote sensing data is rich, their formats and resolution are very different, it is necessary to take some approach to fuse the data. The technique of Principal Components Transform fuses data by replacing the first principal component with the high resolution image after the principal component analysis of multi-spectrum image and then carry on the Principal Components Inverse Transformation to obtain the fusion image;The Wavelet Transformation chooses high-frequency and low-frequency to carry on inverse transformation after decomposing the panchromatic image and multi-spectra image with some wavelet. In this paper, unify the 2 ways to fuse data, the first step is to get the principal components of the IKONOS's multi-spectral image of ChingBai Mountain Area, By the way of Wavelet Decomposition, it is easy to get the high-frequency and low-frequency of the principal components and by taking the method of Wavelet reconstruction, it is useful to reconstruct the principal components with high-frequency of the panchromatic image of IKONOS and the low-frequency of Multi-spectral image;Then obtain the final fusion image by taking the method of Principal Component Inverse Transform;Combining with the way of visual interpretation and the rule of information entropy and spectral correlation coefficient, we get a good result, the amount of fusion image's information is 7.4875, and the correlation coefficient is 0.8619. Compared to a single method, the spectral information and resolution have been improved;the result shows that, the method of combining with Wavelet Transform and Principal Component Transform merge their own advantages and make up the disadvantages, the fusion image not only improves the spatial resolution of the original image, but also retains the relatively high spectral resolution, it will be propitious to the further extraction and processing of the remote sensing data.

关键词： image Fusion ChingBai Mountain IKONOS PrincipalComponentsTransformation Wavelet ransformation Fusion Appraisal

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