Search results for "Iterative reconstruction"

showing 10 items of 129 documents

Architectural Scenes Reconstruction from Uncalibrated Photos and Map Based Model Knowledge

2001

In this paper we consider the problem of reconstructing architectural scenes from multiple photographs taken from arbitrarily viewpoints. The original contribution of this work is the use of a map as a source of a priori knowledge and geometric constraints in order to obtain in a fast and simple way a detailed model of a scene. We suppose images are uncalibrated and have at least one planar structure as a facade for exploiting the planar homography induced between world plane and image to calculate a first estimation of the projection matrix. Estimations are improved by using correspondences between images and map. We show how these simple constraints can be used to calibrate the cameras, t…

Plane (geometry)business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTriangulation (social science)Triangulation (computer vision)Iterative reconstructionProjection (linear algebra)Image (mathematics)Trifocal tensorSimple (abstract algebra)Computer Science::Computer Vision and Pattern RecognitionHomographyComputer visionArtificial intelligencebusiness
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Determination of projection geometry from quantitative assessment of the distortion of spherical references in single-view projection radiography

2004

A method is introduced, inferring the three-dimensional (3-D) location from the 2-D radiographic shadow of an opaque spherical reference body of known radius by considering its elliptical distortion, the 2-D shadow location and a known source-to-receptor distance. Three noncollinear spheres fixed to a rigid object constitute all possible degrees of freedom, i.e., the entire 3-D imaging geometry. The method may be used (a) to determine the 3-D imaging geometry from a single 2-D view and (b) to correct for foreshortening of object distances coplanar with the plane defined by the sphere triplet. Apart from the mathematical background the article describes a small feasibility experiment, perfor…

Plane (geometry)business.industryImage processingGeometryGeneral MedicineIterative reconstructionRadiusSubpixel renderingOpticsProjection (mathematics)DistortionShadowbusinessMathematicsMedical Physics
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Superresolved imaging of remote moving targets.

2006

We present a superresolving approach that allows one to exceed the diffraction limit and recover highly resolved contours of moving targets from a sequence of low-resolution images. The presented approach is suitable for remote sensing applications. The resolution decoding algorithm that is used to recover the high-resolution features of the target can be run partially via optical means and that way can be used to reduce the required computational complexity.

Point spread functionComputational complexity theorybusiness.industryComputer scienceRemote sensing applicationMovementComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVideo RecordingInformation Storage and RetrievalReproducibility of ResultsImage processingIterative reconstructionImage EnhancementSensitivity and SpecificityAtomic and Molecular Physics and OpticsPattern Recognition AutomatedOpticsSubtraction TechniqueImage Interpretation Computer-AssistedPhotographyLimit (mathematics)businessImage resolutionDecoding methodsAlgorithmsOptics letters
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Iterative Regularization Techniques in Image Reconstruction

2000

In this survey we review recent developments concerning the efficient iterative regularization of image reconstruction problems in atmospheric imaging. We present a number of preconditioners for the minimization of the corresponding Tikhonov functional, and discuss the alternative of terminating the iteration early, rather than adding a stabilizing term in the Tikhonov functional. The methods are examplified for a (synthetic) model problem.

Point spread functionTikhonov regularizationMathematical optimizationConjugate gradient methodMinificationIterative reconstructionRegularization (mathematics)AlgorithmSignal subspaceMathematics
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QR-Factorization Algorithm for Computed Tomography (CT): Comparison With FDK and Conjugate Gradient (CG) Algorithms

2018

[EN] Even though QR-factorization of the system matrix for tomographic devices has been already used for medical imaging, to date, no satisfactory solution has been found for solving large linear systems, such as those used in computed tomography (CT) (in the order of 106 equations). In CT, the Feldkamp, Davis, and Kress back projection algorithm (FDK) and iterative methods like conjugate gradient (CG) are the standard methods used for image reconstruction. As the image reconstruction problem can be modeled by a large linear system of equations, QR-factorization of the system matrix could be used to solve this system. Current advances in computer science enable the use of direct methods for…

QR-factorization algorithmComputer scienceIterative methodImage qualityLinear systemDavis and Kress (FDK)Iterative reconstruction3-D images reconstructionSystem of linear equationsAtomic and Molecular Physics and OpticsConjugate gradient (CG)FeldkampQR decompositionMatrix (mathematics)Conjugate gradient methodRadiology Nuclear Medicine and imagingMedical imagingMATEMATICA APLICADAInstrumentationAlgorithmComputed tomography (CT)Reconstruction algorithmsReconstruction toolkit (RTK)
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3D Reconstruction of Dynamic Vehicles using Sparse 3D-Laser-Scanner and 2D Image Fusion

2016

International audience; Map building becomes one of the most interesting research topic in computer vision field nowadays. To acquire accurate large 3D scene reconstructions, 3D laser scanners are recently developed and widely used. They produce accurate but sparse 3D point clouds of the environments. However, 3D reconstruction of rigidly moving objects along side with the large-scale 3D scene reconstruction is still lack of interest in many researches. To achieve a detailed object-level 3D reconstruction, a single scan of point cloud is insufficient due to their sparsity. For example, traditional Iterative Closest Point (ICP) registration technique or its variances are not accurate and rob…

RegistrationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPoint cloud02 engineering and technologyIterative reconstructionRANSAC[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robustness (computer science)Point Cloud0202 electrical engineering electronic engineering information engineeringComputer visionImage fusionbusiness.industry3D reconstruction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Iterative closest point2D camera020207 software engineeringICP3D cameraMaxima and minimaGeography020201 artificial intelligence & image processingArtificial intelligencebusiness3D Reconstruction
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Computer vision-based approach for rite decryption in old societies

2015

International audience; This paper presents an approach to determine the spatial arrangement of bones of horses in an excavation site and perform the 3D reconstruction of the scene. The relative 3D positioning of the bones was computed exploiting the information in images acquired at different levels, and used to relocate provided 3D models of the bones. A novel semi-supervised approach was proposed to generate dense point clouds of the bones from sparse features. The point clouds were later matched with the given models using Iterative Closest Point (ICP).

RiteComputer sciencebusiness.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]3D reconstructionFeature extraction[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Point cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONIterative closest pointExcavationIterative reconstructionSolid modeling[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICS
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Compressive imaging in scattering media.

2015

One challenge that has long held the attention of scientists is that of clearly seeing objects hidden by turbid media, as smoke, fog or biological tissue, which has major implications in fields such as remote sensing or early diagnosis of diseases. Here, we combine structured incoherent illumination and bucket detection for imaging an absorbing object completely embedded in a scattering medium. A sequence of low-intensity microstructured light patterns is launched onto the object, whose image is accurately reconstructed through the light fluctuations measured by a single-pixel detector. Our technique is noninvasive, does not require coherent sources, raster scanning nor time-gated detection…

Scatteringbusiness.industryComputer scienceDetectorHolographyIterative reconstructionimaging systemsSample (graphics)Atomic and Molecular Physics and Opticslaw.inventionComputational photographyCompressed sensingOpticslawphoto detectionbusinessRaster scanscattering mediaOptics express
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A memetic approach to discrete tomography from noisy projections

2010

Discrete tomography deals with the reconstruction of images from very few projections, which is, in the general case, an NP-hard problem. This paper describes a new memetic reconstruction algorithm. It generates a set of initial images by network flows, related to two of the input projections, and lets them evolve towards a possible solution, by using crossover and mutation. Switch and compactness operators improve the quality of the reconstructed images during each generation, while the selection of the best images addresses the evolution to an optimal result. One of the most important issues in discrete tomography is known as the stability problem and it is tackled here, in the case of no…

Settore INF/01 - InformaticaCrossoverComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONEvolutionary algorithmDiscrete tomographyReconstruction algorithmImage processingIterative reconstructionStability problemArtificial IntelligenceRobustness (computer science)Signal ProcessingMemetic algorithmComputer Vision and Pattern RecognitionDiscrete tomographyAlgorithmSoftwareEvolutionary reconstruction.MathematicsPattern Recognition
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Restoration of Digitized Damaged Photos using Bit-Plane Slicing

2007

Digital image restoration aims to recover damaged zones of a digital image, using surrounding information. In this paper we propose a novel approach, based on bit-plane slicing decomposition, with the purpose to make information analysis and reconstruction process easy, fast and effective. Tests have been made on digitized damaged old photos to restore several classes of typical defects in old photographic prints.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONProcess (computing)Image processingIterative reconstructionDigital imageImage restorationComputer graphics (images)Computer visionArtificial intelligenceBit plane slicingbusinessImage restorationBit-plane slicing Digital inpainting Image restoration
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