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conference on image reconstruction from incomplete data vIII

作者： Xu, Nan Gong, Yunye Wang, Qiu Zheng, Yili Doerschuk, Peter C. Cornell Univ Elect & Comp Engn Ithaca NY 14850 USA Univ Calif Berkeley Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Cornell Univ Meinig Sch Biomed Engn Ithaca NY USA

ISBN: (纸本)9781628417661

In single-particle cryo electron microscopy, many electron microscope images each of a single instance of a biological particle such as a virus or a ribosome are measured and the 3-D electron scattering intensity of the particle is reconstructed by computation. Because each instance of the particle is imaged separately, it should be possible to characterize the heterogeneity of the different instances of the particle as well as a nominal reconstruction of the particle. In this paper, such an algorithm is described and demonstrated on the bacteriophage Hong Kong 97. The algorithm is a statistical maximum likelihood estimator computed by an expectation maximization algorithm implemented in Mat lab software.

关键词： 3-D image reconstruction statistical image processing maximum likelihood estimation expectation maximization algorithm structural biology virus Hong Kong 97

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Just look at the image: viewpoint-specific surface normal prediction for improved multi-view reconstruction

Just look at the image: viewpoint-specific surface normal pr...

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IEEE conference on Computer vision and Pattern Recognition

作者： Silvano Galliani Konrad Schindler Photogrammetry and Remote Sensing ETH Zurich

ISBN: (纸本)9781467388528

We present a multi-view reconstruction method that combines conventional multi-view stereo (MvS) with appearance-based normal prediction, to obtain dense and accurate 3D surface models. Reliable surface normals reconstructed from multi-view correspondence serve as training data for a convolutional neural network (CNN), which predicts continuous normal vectors from raw image patches. By training from known points in the same image, the prediction is specifically tailored to the materials and lighting conditions of the particular scene, as well as to the precise camera viewpoint. It is therefore a lot easier to learn than generic single-view normal estimation. The estimated normal maps, together with the known depth values from MvS, are integrated to dense depth maps, which in turn are fused into a 3D model. Experiments on the DTU dataset show that our method delivers 3D reconstructions with the same accuracy as MvS, but with significantly higher completeness.

关键词： Multiple virtual Storage surface normal Reconstructive Surgical Procedures three-dimensional surface Dense imagery (Psychotherapy) image images Normal

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Restoration of defocused images using quasi-point sources which are detected with coherent light 8

Restoration of defocused images using quasi-point sources wh...

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conference on image reconstruction from incomplete data vIII

作者： Ortiz-Sosa, R. Berriel-valdos, L. R. Felix Aguilar, J. INAOE Sta Ma Tonantzintla 72840 Pue Mexico

ISBN: (纸本)9781628417661

In this work, the concept of quasi-point source (qps) is used for the restoration of defocused images of extended objects detected with incoherent light. The method consists of the characterization of the optical system by a qps illuminated with coherent light, its defocused image is then introduced in the restoration process, which is a deconvolution performed with a Wiener filter. The results of the restored images are shown and compared with those images restored when the qps is illuminated with incoherent light. Finally, a numerical evaluation using the RMSD (root mean square deviation method) about the quality of the restoration was made for both cases.

关键词： defocused images image restoration quasi-point source microscopy deconvolution

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Feasibility study for image reconstruction in circular digital tomosynthesis (CDTS) from limited-scan angle data based on compressed-sensing theory

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2015年 777卷 161-166页

作者： Park, Yeonok Je, Uikyu Cho, Hyosung Hong, Daeki Park, Chulkyu Cho, Heemoon Choi, Sungil Woo, Taeho Yonsei Univ Dept Radiol Sci iTOMO Wonju 220710 South Korea Yonsei Univ VYSION Res Ctr Wonju 220710 South Korea

In this work, we performed a feasibility study for image reconstruction in a circular digital tomosynthesis (CDTS) from limited-scan angle data based on compressed-sensing (CS) theory. Here, the X-ray source moves along an arc within a limited scan angle (<= 180 degrees on a circular path set perpendicularly to the axial direction during the image acquisition. This geometry, compared to full angle (3601 scan geometry, allows imaging system to be designed more compactly and gives better tomographic quality than conventional linear digital tomosynthesis (DTS). We implemented an efficient CS based reconstruction algorithm for the proposed geomeny and performed systematic simulations to investigate the image characteristics. We successfully reconstructed CDTS images with incomplete projections acquired at several selected limited scan angles of 45 degrees, 90 degrees, 135 degrees, and 180 degrees for a given tomographic angle of 80 degrees and evaluated the reconstruction quality. Our simulation results indicate that the proposed method can provide superior tomographic quality for axial view and even for the other views (i.e., sagittal and coronal), as in computed tomography, to conventional DTS. (C) 2015 Elsevier B.v. All rights reserved,

关键词： Circular digital tomosynthesis Limited-scan angle Compressed-sensing

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Indoor Scene reconstruction for Through-the-Wall Radar Imaging using Low-Rank and Sparsity Constraints

Indoor Scene Reconstruction for Through-the-Wall Radar Imagi...

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Radar conference

作者： v. H. Tang A. Bouzerdoum S. L. Phung F. H. C. Tivive School of Electrical Computer and Telecommunications Engineering University of Wollongong NSW 2522 Australia

ISBN: (纸本)9781509008643

This paper addresses the problem of indoor scene reconstruction in compressed sensing through-the-wall radar imaging. The proposed method is motivated by two observations that wall reflections reside in a low-rank subspace and the imaged scene tends to be sparse. The task of mitigating the wall reflections and reconstructing an image of the scene behind-the-wall is cast as a joint low-rank and sparsity constrained optimization problem, where a low-rank matrix captures the wall returns and a sparse matrix represents the formed image. An iterative algorithm is developed to estimate the low-rank matrix and the sparse scene vector from a reduced measurement set. Experimental results using real radar data show that the proposed model is very effective at reconstructing the indoor image and removing wall clutter.

关键词： developed estimate proposed

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FPGA acceleration by asynchronous parallelization for simultaneous image reconstruction and segmentation based on the Mumford-Shah regularization 8

FPGA acceleration by asynchronous parallelization for simult...

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conference on image reconstruction from incomplete data vIII

作者： Zhang, Wentai Luo, Guojie Shen, Li Page, Thomas Li, Peng Jiang, Ming Maass, Peter Cong, Jason Peking Univ Beijing Peoples R China PKU UCLA Joint Res Inst Sci & Engn Los Angeles CA USA NUDT Collaborat Innovat Ctr High Performance Comp Changsha Hunan Peoples R China Univ Bremen D-28359 Bremen Germany Univ Calif Los Angeles Los Angeles CA USA

ISBN: (纸本)9781628417661

X-ray computed tomography (CT) is an important technique for noninvasive clinical diagnosis and nondestructive testing. In many applications a number of image processing steps are needed before the image features are available. One of these processing steps is image segmentation, which generates the edge and the structural features of the regions of interest. The conventional flow is to first reconstruct images and then apply image segmentation methods on reconstructed images. In contrast, an emerging technique obtains the tomographic image and segmentation simultaneously, which is especially useful in the case of limited data. An iterative method for simultaneous reconstruction and segmentation (SRS) with Mumford-Shah model has been proposed, which not only regularizes the ill-posed tomographic reconstruction problem, but also produces the image segmentation at the same time. The Mumford-Shah model is both mathematically and computationally chanllenging. In this paper, we propose an asynchronous ray-parallel algorithm of the SRS method and accelerate it using field-programmable gate array (FPGA) devices, which drastically improves the energy efficiency. Experimental results show that the FPGA implementation achieves a 1.2x speedup with an energy efficiency as great as 58x, over the GPU implementation.

关键词： image reconstruction image segmentation Mumford-Shah regularization gamma-convergence asynchronous parallelization FPGA acceleration hardware pipelining

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Phase retrieval for multiple objects 8

Phase retrieval for multiple objects

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conference on image reconstruction from incomplete data vIII

作者： Millane, Rick P. Arnal, Romain D. Chen, Joe P. J. Univ Canterbury Dept Elect & Comp Engn Computat Imaging Grp Christchurch 1 New Zealand Arizona State Univ Dept Phys Tempe AZ 85287 USA

ISBN: (纸本)9781628417661

The problem of reconstructing multiple objects from the average of their diffracted intensities is considered. Three cases of technical interest are studied. The first is where the incoherent average is measured over a single object that adopts a number of positions described by a symmetry group. The second is where the average is over a small number of distinct objects. The third is where the average is over a set of unit cells that can occur in an ensemble of nanocrystals as a result of different edge terminations. As a result of some redundancy in the multi-dimensional phase problem, a unique solution can be obtained for these problems under some circumstances. Uniqueness is characterised using the constraint ratio. Iterative projection algorithms can be adapted to accommodate these cases and example simulated reconstructions are presented.

关键词： Phase retrieval image reconstruction techniques computational imaging nanocrystallography

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On Compressed Sensing image reconstruction using Multichannel Fusion and Adaptive Filtering 5

On Compressed Sensing Image Reconstruction using Multichanne...

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International conference on image Processing Theory Tools and Applications

作者： Islam, Sheikh Rafiul Maity, Santi P. Ray, Ajoy Kumar Neotia Inst Technol Management & Sci 24 Pgs S Amira 743368 WB India Indian Inst Engn Sci & Tech Howrah 711103 WB India

ISBN: (纸本)9781479986378

Compressed sensing (CS) in imaging is essential in many practical situations and does need suitable algorithm for reconstruction from this highly incomplete observations/measurements. Measurements are also noisy in majority of the cases. This paper addresses CS-reconstruction of images from multiple channel data acquisition with under sampling measurements. An adaptive filtering based stochastic approximation through a recursive system is explored to reconstruct images from CS-multichannel noisy measurements using fusion technique. A simple weighted averaging is done in fusion process where the weights are calculated based on estimation of noise level. A spatial domain adaptive Wiener filter is then used to diminish the noise and reveals new features from the degraded observations. Experimental results show that the proposed multichannel fusion based CS reconstruction scheme outperforms individual channels both in subjective and objective quality measures.

关键词： Compressed sensing multichannel CS-fusion image fusion adaptive filtering image reconstruction

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Towards an omnidirectional catadioptric RGB-D camera

Towards an omnidirectional catadioptric RGB-D camera

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IEEE/RSJ International conference on Intelligent Robots and Systems

作者： Jose Iglesias Pedro Mirado Rodrigo ventura "Instituto de Sistemas e Robotica" "Instituto Superior Tecnico Universidade de Lisboa" Portugal

ISBN: (纸本)9781509037636

In this paper we address the 3D reconstruction of points, on a non-central catadioptric system, composed by a mirror, a projector, and a perspective camera. The goal of the paper is to propose a framework to build an omnidirectional depth camera, towards an omnidirectional RGB-D camera system. The main contributions are: an efficient technique to project 3D points from the world to an image of a general non-central catadioptric camera;the definition of the template pattern (for both the projector and camera's images);and the matching between the projection of these features to the world and its respective images. The 3D depth is directly recovered using the template matching approach. In conclusion, we apply some filtering techniques to improve the results. To evaluate the proposed framework, we test the method using synthetic data, under different levels and types of noises, proving that the framework is robust to noise and, thus, can be put into practice.

关键词： Cameras Mirrors Three-dimensional displays image reconstruction Robot vision systems Light sources three-dimensional displays Cameras robot vision system Mirrors LIGHT SOURCES image reconstruction catadioptric Noise Frameworks noncentral

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3-D UNDERSTANDING OF ELECTRON MICROSCOPY imageS OF NANO BIO OBJECTS BY COMPUTING GENERATIvE MECHANICAL MODELS

3-D UNDERSTANDING OF ELECTRON MICROSCOPY IMAGES OF NANO BIO ...

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IEEE International conference on image Processing

作者： Yunye Gong Peter C. Doerschuk Cornell University Electrical and Computer Engineering

ISBN: (纸本)9781467399623

Cryo electron microscopy records essentially projection images of each of many instances of a nano bio object. This data allows reconstruction of a stochastic model of the object, i.e., the mean and covariance functions of the electron scattering intensity of the object. Understanding the covariance function, which characterizes the heterogeneity of the instances of the object, is challenging because the covariance function is not wide-sense stationary but instead depends separately on the two three-dimensional positions. This paper describes a method, qualitatively motivated by fluctuation-dissipation theory, for estimating a spring-and-mass mechanical model of the object. Then, from the model, a wide range of properties of the object can be understood, such as normal modes of vibration.

关键词： image understanding Computational imaging Electron microscopy Tomography

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