Search results for "Iterative reconstruction"
showing 10 items of 129 documents
Estimating Missing Information by Cluster Analysis and Normalized Convolution
2018
International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.
Quality Assessment of Reconstruction and Relighting from RTI Images: Application to Manufactured Surfaces
2019
In this paper, we propose to evaluate the quality of the reconstruction and relighting from images acquired by a Reflectance Transformation Imaging (RTI) device. Three relighting models, namely the PTM, HSH and DMD, are evaluated using PSNR and SSIM. A visual assessment of how the reconstructed surfaces are perceived is also carried out through a sensory experiment. This study allows to estimate the relevance of these models to reproduce the appearance of the manufactured surfaces. It also shows that DMD reproduces the most accurate reconstruction/relighting to an acquired measurement and that a higher sampling density don't mean necessarily a higher perceptual quality.
Tunable-frequency three-dimensional structured illumination microscopy with reduced data-acquisition
2018
The performance of a tunable three-dimensional (3D) structured illumination microscope (SIM) system and its ability to provide simultaneously super-resolution (SR) and optical-sectioning (OS) capabilities are investigated. Numerical results show that the performance of our 3D-SIM system is comparable with the one provided by a three-wave interference SIM, while requiring 40% fewer images for the reconstruction and providing frequency tunability in a cost-effective implementation. The performance of the system has been validated experimentally with images from test samples, which were also imaged with a commercial SIM based on incoherent-grid projection for comparison. Restored images from d…
High Quality Reconstruction of Dynamic Objects using 2D-3D Camera Fusion
2017
International audience; In this paper, we propose a complete pipeline for high quality reconstruction of dynamic objects using 2D-3D camera setup attached to a moving vehicle. Starting from the segmented motion trajectories of individual objects, we compute their precise motion parameters, register multiple sparse point clouds to increase the density, and develop a smooth and textured surface from the dense (but scattered) point cloud. The success of our method relies on the proposed optimization framework for accurate motion estimation between two sparse point clouds. Our formulation for fusing it closest-point and it consensus based motion estimations, respectively in the absence and pres…
Localization of 2D Cameras in a Known Environment Using Direct 2D-3D Registration
2014
International audience; In this paper we propose a robust and direct 2D-to- 3D registration method for localizing 2D cameras in a known 3D environment. Although the 3D environment is known, localizing the cameras remains a challenging problem that is particularly undermined by the unknown 2D-3D correspondences, outliers, scale ambiguities and occlusions. Once the cameras are localized, the Structure-from-Motion reconstruction obtained from image correspondences is refined by means of a constrained nonlinear optimization that benefits from the knowledge of the scene. We also propose a common optimization framework for both localization and refinement steps in which projection errors in one v…
A naive approach to compose aerial images in a mosaic fashion
2002
There is growing interest in multiple sequence image analysis to represent those data in a new landscape, for instance reconstruction of old films, mosaicing of images. This paper focuses attention on the mosaic problem; it introduces a naive method to link together images where a common part of the scene is present among two images. An application has been developed to test the method on aerial sequences of images. Given the long distance of aircraft from the scene, the method assumes images without distortions and without problems of prospective. Moreover, the application does not need any additional parameters coming from human experience and for this reason it can be thought of as a ful…
Computed tomography-based tracheobronchial image reconstruction allows selection of the individually appropriate double-lumen tube size
1999
Objectives: To determine whether individualized selection of double-lumen tubes or alternatives based on three-dimensional reconstruction of the tracheobronchial image from routine preoperative computed tomography (CT) scans leads to clinically appropriate choices. Design: Prospective observational study; comparison to historic controls. Setting: Anesthesia and radiology facilities of a university medical center. Participants: Forty-nine patients undergoing thoracic surgery requiring one-lung ventilation. Interventions: Three-dimensional image reconstruction of individual tracheobronchial anatomy was performed from routine preoperative spiral CT scans as well as from scans of five left-side…
An adaptive-PCA algorithm for reflectance estimation from color images
2008
This paper deals with the problem of spectral reflectance estimation from color camera outputs. Because the reconstruction of such functions is an inverse problem, stabilizing the reconstruction process is highly desirable. One way to do this is to decompose reflectance function on a basis functions like PCA. The present work proposes an algorithm making PCA adaptive in reflectance estimation from a color camera output. We propose to adapt the PCA basis derivation by selecting, for each sample, the more relevant elements from the training set elements. The adaptivity criterion is achieved by a likelihood measurement. Finally, the spectral reflectance estimation results are evaluated with th…
Reflectance-based surface saliency
2017
In this paper, we propose an original methodology allowing the computation of the saliency maps for high dimensional RTI data (Reflectance Transformation Imaging). Unlike most of the classical methods, our approach aims at devising an intrinsic visual saliency of the surface, independent of the sensor (image) and the geometry of the scene (light-object-camera). From RTI data, we use the DMD (Discrete Modal Decomposition) technique for the angular reflectance reconstruction, which we extend by a new transformation on the modal basis enabling a rotation-invariant representation of reconstructed reflectances. This orientation-invariance of the resulting reflectance shapes fosters a robust esti…
Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE …
2021
Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between O…