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

共 623 条记录，以下是421-430 订阅

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image demosaic via Nevatia-Babu edge detection

Image demosaic via Nevatia-Babu edge detection

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conference on Digital Photography iii

作者： Reinhart, Craig Bodie, James California Lutheran Univ 60 W Olsen Rd Thousand Oaks CA 93021 USA

ISBN: (纸本)9780819466150

A template matching approach is used to demosaic (reconstruct) a full color image from the sparse pixel data captured by a CMOS imager. The proposed method is based on the Nevatia-Babu template-based linear feature extraction algorithm. This approach provides the color accuracy of gradient based algorithms yet reaps the benefit of regularity of processing of bilinear interpolation. In this paper we describe the algorithm (gradient estimation and color interpolation), compare results to other approaches, and present a hardware implementation. The consideration of hardware implementation is especially important as CMOS imagers find their way into low cost devices such as cell phones and other novelty camera applications.

关键词： image demosiac image reconstruction sparse data edge detection linear feature extraction

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Photoacoustic image reconstruction - A quantitative analysis

Photoacoustic image reconstruction - A quantitative analysis

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conference on Novel Optical Instrumentation for Biomedical Applications iii

作者： Sperl, Jonathan I. Zell, Karin Menzenbach, Peter Haisch, Christoph Ketzer, Stephan Marquart, Markus Koenig, Hartmut Vogel, Mika W. GE Global Res Freisinger Landstr 50 Munich Germany Tech Univ Munich Chair Analyt Chem Munich Germany Innolas GmbH Krailling Germany

ISBN: (纸本)9780819467751

Photoacoustic imaging is a promising new way to generate unprecedented contrast in ultrasound diagnostic imaging. It differs from other medical imaging approaches, in that it provides spatially resolved information about optical absorption of targeted tissue structures. Because the data acquisition process deviates from standard clinical ultrasound, choice of the proper image reconstruction method is crucial for successful application of the technique. In the literature, multiple approaches have been advocated, and the purpose of this paper is to compare four reconstruction techniques. Thereby, we focused on resolution limits, stability, reconstruction speed, and SNR. We generated experimental and simulated data and reconstructed images of the pressure distribution using four different methods: delay-and-sum (DnS), circular backprojection (CBP), generalized 2D Hough transform (HTA), and Fourier transform (FTA). All methods were able to depict the point sources properly. DnS and CBP produce blurred images containing typical superposition artifacts. The HTA provides excellent SNR and allows a good point source separation. The FTA is the fastest and shows the best FWHM. In our study, we found the FTA to show the best overall performance. It allows a very fast and theoretically exact reconstruction. Only a hardware-implemented DnS might be faster and enable real-time imaging. A commercial system may also perform several methods to fully utilize the new contrast mechanism and guarantee optimal resolution and fidelity.

关键词： photoacoustic optoacoustic image reconstruction delay-and-sum circular backprojection Hough transform Fourier transform

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Global optimization for shape fitting

Global optimization for shape fitting

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IEEE conference on Computer Vision and Pattern Recognition

作者： Lempitsky, Victor Boykov, Yuri Moscow MV Lomonosov State Univ Dept Math & Mech Moscow Russia Univ Western Ontario Dept Comp Sci London ON N6A 3K7 Canada

ISBN: (纸本)9781424411795

We propose a global optimization framework for 3D shape reconstruction from sparse noisy 3D measurements frequently encountered in range scanning, sparse feature-based stereo, and shape-from-X. In contrast to earlier local or banded optimization methods for shape fitting, we compute global optimum in the whole volume removing dependence on initial guess and sensitivity to numerous local minima. Our global method is based on two main ideas. First, we suggest a new regularization functional with a data alignment term that maximizes the number of (weakly-oriented) data points contained by a surface while allowing for some measurement errors. Second, we propose a touch-expand algorithm for finding a minimum cut on a huge 3D grid using an automatically adjusted band This overcomes prohibitively high memory cost of graph cuts when computing globally optimal surfaces at high-resolution. Our results for sparse or incomplete 3D data from laser scanning and passive multi-view stereo are robust to noise, outliers, missing parts, and varying sampling density.

关键词： image reconstruction

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Fusion of 3D line features and 2D image line features for building roof reconstruction

Fusion of 3D line features and 2D image line features for bu...

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28th Asian conference on Remote Sensing 2007, ACRS 2007

作者： Jaw, Jen-Jer Cheng, Chieh-Chung Department of Civil Engineering National Taiwan University No. 1 Roosevelt Road Taipei 10617 Taiwan

ISBN: (纸本)9781615673650

The objective of this study is to present an efficient algorithm of building roof reconstruction by fusing 3D line features and 2D image line features through CSR (Construct-Shape-Refine) procedures. The proposed algorithm starts by inputting 3D line features and performs the following geometric inferences: (1) constructing the topological relationship of 3D line features that belong to the same building;(2) shaping the building roof by means of adjustments, compensating missing parts, if any, and reporting whether or not the investigated building roof is completed;(3) refining the building roof by integrating 2D line features observed, automatic image processing or manual measurements, from the images through geometric inference processes. The preliminary experiments show that the proposed CSR algorithm provides a workable platform for building roof reconstruction by fusing 3D line features and 2D image line features. An interactive operating environment is not only advisable when faced with incomplete reconstruction due to the deficiency of automatic systems or data sets but also efficient for improving the quality of building roof model with complete reconstruction, where manual measurements would make up for those insufficiency.

关键词： Roofs

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Signal reconstruction from incomplete and misplaced reasurements

Signal reconstruction from incomplete and misplaced reasurem...

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69th European Association of Geoscientists and Engineers conference and Exhibition 2007 -

作者： Challa, S.S. Hennenfent, G. Herrmann, F.J. University of British Columbia

ISBN: (纸本)9781605601557

Constrained by practical and economical considerations, one often uses seismic data with missing traces. The use of such data results in image artifacts and poor spatial resolution. Sometimes due to practical limitations, measurements may be available on a perturbed grid, instead of on the designated grid. Due to algorithmic requirements, when such measurements are viewed as those on the designated grid, the recovery procedures may result in additional artifacts. This paper interpolates incomplete data onto a regular grid via the Fourier domain, using a recently developed greedy algorithm. The basic objective is to study experimentally as to what could be the size of the perturbation in measurement coordinates that allows for the measurements on the perturbed grid to be considered as on the designated grid. Our experimental work shows that for compressible signals, a uniformly distributed perturbation can be offset with slightly more number of measurements.

关键词： Seismology

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A comparative study of algorithms for radar Imaging from gapped data

A comparative study of algorithms for radar Imaging from gap...

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conference on Unconventional Imaging iii

作者： Xu, Xiaojian Luan, Ruixue Jia, Li Huang, Ying BeiHang Univ Sch Elect & Informat Engn Beijing 100083 Peoples R China

ISBN: (纸本)9780819468604

In ultra wideband (UWB) radar imagery, there are often cases where the radar's operating bandwidth is interrupted due to various reasons, either periodically or randomly. Such interruption produces phase history data gaps, which in turn result in artifacts in the image if conventional image reconstruction techniques are used. The higher level artifacts severely degrade the radar images. In this work, several novel techniques for artifacts suppression in gapped data imaging were discussed. These include: (1) A maximum entropy based gap filling technique using a modified Burg algorithm (MEBGFT);(2) An alternative iteration deconvolution based on minimum entropy (AIDME) and its modified version, a hybrid max-min entropy procedure;(3) A windowed coherent CLEAN algorithm;and (4) Two-dimensional (2-D) periodically-gapped Capon (PG-Capon) and APES (PG-APES) algorithms. Performance of various techniques is comparatively studied.

关键词： radar imagery synthetic aperture imaging image processing deconvolution modem spectral estimation

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Evolutionary Computational approach for artifact-free image reconstruction from reduced samples: Application to Fourier EMRI

Evolutionary Computational approach for artifact-free image ...

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7th International conference on Computational Intelligence and Multimedia Applications

作者： Sumathi, M. Krishna, Murali C. Murugesan, R. Sri Meenakshi Govt Coll W Madurai Tamil Nadu India NCI Bethesda MD 20892 USA MK Univ Madurai Tamil Nadu India

ISBN: (纸本)0769530508

Electron magnetic resonance imaging (EMRI) is emerging as a potential biomedical-imaging technology for noninvasive imaging of free radicals in biological systems. EAMI by single point imaging (SPI) modality is a Fourier imaging technique. The bioclearance of the imaging agent as well as the need to minimize the radio frequency (RF) power deposition on the live animals, dictate reduced k-space sampling. This leads to ringing (Gibbs) artifacts which are severe and seen in both directions of the 2D image, because, unlike the conventional MRI SPI is phase encoding in both directions. To dampen the high frequency components, data tapering windows are multiplicatively applied to provide tolerable blurred resultant image with reduced Gibbs ringing. To find a compromise between blur and ringing artifact, in this paper a method of optimizing the window functions by using genetic algorithm (GA) is proposed. The proposed algorithm is validated, using Matlab codes, first reconstructing AM image of Shepp Logan head phantom from simulated k-space data, and next tested by reconstructing real EMR images of phantoms and live mice from experimentally acquired k-space data. image quality metrics viz. signal to noise ratio (SNR), contrast to noise ratio (CNR), peak signal to noise ratio (PSNR), root mean square error (RMSE), standard deviation (STD) and the Liu's error function F(I) are computed Our experiments suggest GA-based Kaiser window provides good optimal blur/ringing compromise in EMR tomograms.

关键词： Evolutionary algorithms

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Sub-pixel compounding from elasticity imaging data

Sub-pixel compounding from elasticity imaging data

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Medical Imaging 2007 conference

作者： Yang, Zhi Sinha, Sumedha Booi, Rebecca C. Roubidoux, Marilyn A. Ma, Bing Fowlkes, J. Brian LeCarpentier, Gerald L. Carson, Paul L. Univ Michigan Dept Radiol Basic Radiol Sci Div 3315 Kresge III 200 Zina Pitcher Pl Ann Arbor MI 48109 USA

ISBN: (纸本)9780819466280

Sub-pixel compounding is a technique that synthesizes the information of an image sequence to form a better-resolved and speckle reduced image. To avoid extra data acquisition time and patient exposure, reuse of the existing data is highly desired. In elasticity imaging, a set of images with slight changes due to deformation is produced, which provides an ideal. input for the sub-pixel compounding process. In this paper, a brief review of the resolution enhancement techniques in ultrasound imaging will be provided, and then, a diffusion-regularized, least square approach is presented for sub-pixel compounding image reconstruction. Based on the results, we suggest that (1) B-mode images from elastic imaging are suitable data for sub-pixel compounding and a speckle noise reduced higher-resolution image is a co-product of elasticity imaging;(2) for breast diagnosis, resolution improvement is of strong interest since better depiction of the interior and exterior structures of a tumor provides important detection and diagnostic information;(3) a. similar approach could be extended to elasticity imaging with other modalities.

关键词： sub-pixel compounding elasticity imaging B-mode ultrasound image resolution enhancement speckle reduction

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Compressed Sensing image reconstruction Via Recursive Spatially Adaptive Filtering

Compressed Sensing Image Reconstruction Via Recursive Spatia...

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IEEE International conference on image Processing

作者： Karen Egiazarian Alessandro Foi Vladimir Katkovnik Institute of Signal Processing Tampere University of Technology Tampere Finland

We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coefficients of an arbitrary linear transform. This reconstruction problem is the subject of intensive study in the recent field of "compressed sensing" (also known as "compressive sampling"). Our approach is based on a quite specific recursive filtering procedure. At every iteration the algorithm is excited by injection of random noise in the unobserved portion of the spectrum and a spatially adaptive image denoising filter, working in the image domain, is exploited to attenuate the noise and reveal new features and details out of the incomplete and degraded observations. This recursive algorithm can be interpreted as a special type of the Robbins-Monro stochastic approximation procedure with regularization enabled by a spatially adaptive filter. Overall, we replace the conventional parametric modeling used in CS by a nonparametric one. We illustrate the effectiveness of the proposed approach for two important inverse problems from computerized tomography: Radon inversion from sparse projections and limited-angle tomography. In particular we show that the algorithm allows to achieve exact reconstruction of synthetic phantom data even from a very small number projections. The accuracy of our reconstruction is in line with the best results in the compressed sensing field.

关键词： Compressed sensing image reconstruction Adaptive filters image coding image sampling Filtering image denoising Degradation Approximation algorithms Stochastic resonance

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Single tree detection in forest areas with high-density LIDAR data

Single tree detection in forest areas with high-density LIDA...

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Joint conference of ISPRS Working Groups I/2, iii/2, iii/4, iii/5, IV/3 on Photogrammetric image Analysis, PIA 2007

作者： Reitberger, J. Heurich, M. Krzystek, P. Stilla, U. Dept. of Geoinformatics Munich University of Applied Sciences Munich80333 Germany Dept. of Research Bavarian Forest National Park Grafenau94481 Germany Photogrammetry and Remote Sensing Technische Universität München Munich80290 Germany

The study presents a novel method for delineation of tree crowns and detection of stem positions of single trees from dense airborne LIDAR data. The core module of the method is a surface reconstruction that robustly interpolates the canopy height model (CHM) from the LIDAR data. Tree segments are found by applying the watershed algorithm to the CHM. Possible stem positions of the tallest trees in the segments are subsequently derived from the local maxima of the CHM. Additional stem positions in the segments are found in a 3-step algorithm. First, all the points between the ground and the crown base height are separated. Second, possible stem points are found by hierarchical clustering these points using their horizontal distances. Third, the stem position is estimated with a robust RANSAC-based adjustment of the stem points. We applied the method to small-footprint full waveform data that have been acquired in the Bavarian Forest National Park with a point density of approximately 25 points per m2. The results indicate that the detection rate for coniferous trees is 61 % and for deciduous trees 44 %, respectively. 7 % of the detected trees are false positives. The mean positioning error is 0.92 cm, whereas the additional stem detection improves the position on average by 22 cm.

关键词： Forestry

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