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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81-90 订阅

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Super-resolution in image restoration of wide area images viewed through atmospheric turbulence

Super-resolution in image restoration of wide area images vi...

引用

2nd conference on image reconstruction from incomplete data

作者： Lambert, A Fraser, D Jahromi, MRS Hunt, BR Univ New S Wales Univ Coll Kensington NSW 2033 Australia

ISBN: (纸本)0819445592

We postulate that under anisoplanatic imaging conditions involving imaging through turbulent media over a wide-area there exists the possibility of spatial frequency content that is normally lost outside the aperture of an imaging instrument under unperturbed viewing conditions, being aliased into the aperture. Simulation is presented that reinforces this premise. We apply restoration algorithms that were designed to correct non-uniform distortions, to a real image sequence to the effect of noticing the de-aliased super-frequency content. We claim this to be super-resolution, and that it is only possible under anisoplanatic imaging scenarios, where the point spread function of the image is position dependent as a result of the atmospheric turbulence.

关键词： wide-area image restoration super-resolution surveillance imaging astronomical imaging

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Three-dimensional surface approximation from incomplete data using distance transform

Three-dimensional surface approximation from incomplete data...

引用

2nd conference on image reconstruction from incomplete data

作者： Lee, DJ Westover, B Eifert, J Brigham Young Univ Dept Elect & Comp Engn Provo UT 84602 USA

ISBN: (纸本)0819445592

Three-dimensional (3-D) object surface reconstruction is an important step toward non-destructive measurements of surface area and volume. Laser triangulation technique has been widely used for obtaining 3-D information. However, the 3-D data obtained from triangulation are not dense enough or usually not complete for surface reconstruction, especially for objects with irregular shape. As a result of fitting surfaces with these sparse 3-D data, inaccuracy in measuring the surface area or calculating the volume of the object is inevitable. A computer vision technique combining laser triangulation and distance transform has been developed to improve the measurement accuracy for objects with irregular shape. A 3-D wire-frame model is generated first with all available 3-D data. Each pixel within the image boundary is given the distance information using distance transform. The distance information of each pixel is then used as the constraints for surface fitting and interpolation. With this additional information from distance transform, more accurate surface approximation can be achieved. The measurement accuracy of this technique is compared with other interpolation techniques for the volume measurement of oyster meats.

关键词： distance transform laser triangulation 3-D wire-frame model machine vision surface fitting surface interpolation oyster

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Semiconducting bilinear deep learning for incomplete image recognition 12

Semiconducting bilinear deep learning for incomplete image r...

引用

2nd ACM International conference on Multimedia Retrieval, ICMR 2012

作者： Zhong, Sheng-Hua Liu, Yan Chung, Fu-Lai Wu, Gangshan Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (纸本)9781450313292

image recognition with incomplete data is a well-known hard problem in multimedia content analysis. This paper proposes a novel deep learning technique called semiconducting bilinear deep belief networks (SBDBN) by referencing human's visual cortex and intelligent perception. Inheriting from deep models, SBDBN simulates the laminar structure of human's cerebral cortex and the neural loop in human's visual areas. To address the special difficulties of image recognition with incomplete data, we design a novel second-order deep architecture with semiconducting restricted boltzmann machines. Moreover, two peaks activation of human's perception is implemented by three learning stages of semiconducting bilinear discriminant initialization, greedy layer-wise reconstruction, and global finetuning. Owing to exploiting the embedding information according to the reliable features rather than any completion of missing features, the proposed SBDBN has demonstrated outstanding recognition ability on two standard datasets and one constructed dataset, comparing with both incomplete image recognition techniques and existing deep learning models. Copyright © 2012 ACM.

关键词： image recognition

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Sampling, radiometry, and image reconstruction for polar and geostationary meteorological remote sensing systems

Sampling, radiometry, and image reconstruction for polar and...

引用

2nd conference on image reconstruction from incomplete data

作者： Abrams, MC Cain, SC ITT Industries Inc. (United States) Indiana Univ.-Purdue Univ./Fort Wayne (United States)

ISBN: (纸本)0819445592

In this paper, a Bayesian-based image reconstruction scheme is utilized for estimating a high resolution temperature map of the top of the earth's atmosphere using the GOES-8 (Geostationary Operational Environmental Satellite) imager infrared channels. By simultaneously interpolating the image while estimating temperature, the proposed algorithm achieves a more accurate estimate of the sub-pixel temperatures than could be obtained by performing these operations independently of one another. The proposed algorithm differs from other Bayesian-based image interpolation schemes in that it estimates brightness temperature as opposed to image intensity and incorporates a detailed optical model of the GOES multi-channel imaging system. The temperature estimation scheme is compared to deconvolution via pseudo-inverse filtering using two metrics. One metric is the mean squared temperature error. This metric describes the radiometric accuracy of the image estimate. The second metric is the recovered Modulation Transfer Function (MTF) of the image estimate. This method has traditionally been used to evaluate the quality of image recovery techniques. It will be shown in this paper that there is an inconsistency between these two metrics in that an image with high spatial frequency content can be reconstructed with poor radiometric, accuracy. The ramifications of this are discussed in order to evaluate the two metrics for use in quantifying the performance of image reconstruction algorithms.

关键词： Imaging systems image restoration reconstruction algorithms Sensors image resolution Modulation transfer functions Radiometry data modeling Satellite imaging Satellites

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Big data simulation for surface reconstruction on CPU-GPU platform 2

Big data simulation for surface reconstruction on CPU-GPU pl...

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2nd International conference on data and Information Science (ICoDIS)

作者： Hadi, N. A. Univ Teknol Malaysia Ibnu Sina Inst Sci & Ind Res Skudai 81310 Johor Malaysia Univ Teknol MARA Fac Comp & Math Sci Shah Alam 40450 Selangor Malaysia

This paper discusses on CPU-GPU collaboration in surface reconstruction process from CT scan image, in this case human head. This type of image consists hundreds of data points and needs a powerful processor to ensure the accurateness of result. Therefore, an architecture to segment the whole process to CPU and GPU is designed. Comparison of CPU and GPU is done based on execution time and speedup for total number of the data points up to 10(5). from the analysis, it is shown that the maximum speedup is more than 15 for a process.

关键词： Graphics processing unit

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BIIR: Blind Inpainting based image Reconstructon for Texture Defect Detection 2

BIIR: Blind Inpainting based Image Reconstructon for Texture...

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2nd International conference on Big data and Artificial Intelligence and Software Engineering (ICBASE)

作者： Qiu, Yuanhong Zhou, Cong Zhang, Zefeng Li, Bin Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan Peoples R China

ISBN: (纸本)9781665427098

image reconstruction is an important method for texture defect detection, and the existing image reconstruction algorithms based on Autoencoder and GAN cannot suppress the reconstruction of defect information, which affects the detection accuracy. To solve this problem, this paper proposes a novel image reconstruction algorithm based on image inpainting, which includes two modules of defect estimation network and defect inpainting network. Firstly, the defect estimation network used the pre-training model to extract the deep features of the defect image and applied the Gaussian distance to estimate the background area. and then the image inpainting network applied the contextual attention mechanism to repair the nonbackground area of the defect image. Through the experimental analysis which compared with other state-of-the-art image reconstruction algorithms on the public Mvtec texture dataset, the superiority of the proposed algorithm is effectively verified.

关键词： defect detection image inpainting contextual attention mechanism

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An image-to-image Target reconstruction Network for Capacitively Coupled Electrical Resistance Tomography Based on Transfer Learning 2

An Image-to-image Target Reconstruction Network for Capaciti...

引用

2nd International conference on Computer Vision and Intelligent Technology

作者： Luo, Chunfen Jiang, Yandan Vivo Mobile Commun Co Ltd Hangzhou Peoples R China Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou Peoples R China

ISBN: (纸本)9798331540050;9798331540043

This work develops an image-to-image target reconstruction network for capacitively coupled electrical resistance tomography. The novel target reconstruction network is constructed by two Unets to extract and fuse the multi-frequency features of the coarse images reconstructed by traditional image reconstruction algorithms, and incorporated with transfer learning to improve the generalization ability of the network. Experimental results show that the developed target reconstruction network is effective. The Unet-based image-to-image framework improves the target reconstruction quality with quantitatively higher image score. The introduced transfer learning strategy fills the gap between simulation data and experimental data, and further improves the performance of the network.

关键词： Electrical resistance tomography contactless imaging target reconstruction multi-frequency image fusion transfer learning

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Inverse scattering of strongly scattering targets using redundant data sets

Inverse scattering of strongly scattering targets using redu...

引用

2nd conference on image reconstruction from incomplete data

作者： Semichaevsky, AV Ghogomu, P Al Ababneh, N Testorf, ME Fiddy, MA Univ Massachusetts Lowell Dept Elect & Comp Engn Lowell MA 01854 USA

ISBN: (纸本)0819445592

For weakly scattering permittivities, each measurement of the scattered far field can be interpreted as a sampling point of the Fourier transformation of the object. Furthermore, each sampling point can be accessed by more than one combination of wavelength, propagation direction, and polarization of the incident field. This means, a set of measurements which access the same sampling point can be regarded as being redundant. For strongly scattering objects the Fourier diffraction slice theorem does not apply. We show that measurements which are redundant in the weakly scattering case can be exploited to resolve difficulties associated with imaging of the strongly scattering objects. One dimensional geometries are investigated to estimate the potential redundant data sets offer for addressing the inverse scattering problem of strongly and multiply scattering objects. In addition, we discuss preliminary results for solving 2D imaging problems.

关键词： nonlinear inverse scattering strongly scattering objects multiple scattering polarimetric information diffraction tomography synthetic aperture radar

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Classification of Varietal Type of Philippine Rice Grains Using image Processing through Multi-View 3d reconstruction 2019

Classification of Varietal Type of Philippine Rice Grains Us...

引用

2nd International conference on Computing and Big data (ICCBD)

作者： Buenaventura, Jan Rei S. Kobayashi, Jun T. Valles, Larah Mae P. De Goma, Joel C. Balan, Ariel Kelly D. Mapua Univ Sch Informat Technol Makati Philippines

ISBN: (纸本)9781450372909

Number of previous works have been carried out to study the classification of rice in the flat 2D image. In computer vision, 3D reconstruction is a field that has great theoretical research value. This paper attempts to see the performance by using features extracted from the 3D reconstructed image of a rice grain in classifying different varieties of it. We identify 250 rice grains belonging to five (5) varietal groups of rice in the Philippines. The data gathered was in the form of a video from a camera then it was split into images. After applying image enhancement operations, the images where used to build the 3D model using Agisoft Photoscan software. After the reconstruction, 18 color features and 21 texture features were extracted from the image. After the feature selection, 32 features were selected for this study. The proposed method uses BPNN architecture to classify the rice grain's varietal type.

关键词： Rice classification Color analysis Texture analysis 3D model reconstruction BPNN classifier Computer vision image processing

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Three-Dimensional reconstruction of Vessels from Intravascular Ultrasound Sequence and X-ray Angiograms

Three-Dimensional Reconstruction of Vessels from Intravascul...

引用

2nd International conference on Biomedical Engineering and Informatics (BMEI)

作者： Zheng, Sun N China Elect Power Univ Dept Elect & Commun Engn Baoding 071003 Peoples R China

ISBN: (纸本)9781424441334

A method to reconstruct vessels from intravascular ultrasound (IVUS) image sequence and X-ray angiograms is proposed in this paper. The pullback path of IVUS catheter is tracked and reconstructed from angiographic image pair acquired during IVUS intervention. Cross-sectional borders of the vessel wall are detected from IVUS frames in a semiautomatic manner. After axial locations of IVUS frames are determined along the 3D pullback path of IVUS catheter, their spatial orientations are determined based on a Frenet-Serret frame model and global optimization. Finally, the vessel is accurately reconstructed with solid modeling technique. Experimental results with clinical data demonstrate the validity.

关键词： Intravascular Ultrasound (IVUS) X-ray angiography reconstruction image fusion

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