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A synthetic sensor/image simulation tool to support the landsat data continuity mission (LDCM)

A synthetic sensor/image simulation tool to support the land...

American Society for Photogrammetry and Remote Sensing Annual conference 2010: Opportunities for Emerging Geospatial Technologies

作者： Schott, John R. Raqueno, Rolando v. Raqueno, Nina G. Brown, Scott D. Digital Imaging and Remote Sensing Laboratory Chester F. Carlson Center for Imaging Science Rochester Institute of Technology Rochester NY 14623 United States

ISBN: (纸本)9781617389160

The next generation of Landsat sensors will incorporate many changes from the existing whiskbroom designs. In particular, the Operational Land imager (OLI) incorporates a multispectral pushbroom design which has different bands imaging the same spot on the Earth at slightly different angles and times. This requires more involved knowledge of the sensor and the scene, as input to more complex processing algorithms, to form spectrally registered images. In addition, the thermal data for the LDCM will come from a separate Thermal Infrared Sensing Instrument (TIRS) flown on the same platform. Thus, there are additional complexities associated with registering the OLI and TIRS data to each other and the ground. This paper presents a synthetic sensor/scene model designed to generate synthetic OLI and TIRS data sets to support development and testing of LDCM image reconstruction algorithms. This is part of a larger effort to use the synthetic sensor/scene models to support a range of LDCM development and monitoring activities. Methods for generation of a synthetic scene incorporating digital elevation models, spatial texture from high resolution satellite data, spectral variability from Hyperion satellite data, and atmospheric effects from the MODTRAN radiative transfer code are presented. Within the Digital Imaging and Remote Sensing image Generation model, OLI and TIRS sensor models are being created that can be "flown" over the synthetic scene to form synthetic images that mimic the geometric sampling of the actual sensors. The synthetic images will be used to support the Landsat image quality assessment program with an initial focus on image reconstruction algorithms.

关键词： image reconstruction

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Development and Evaluation of a vision Algorithm for 3D reconstruction of Novel Objects from Three Camera views

Development and Evaluation of a Vision Algorithm for 3D Reco...

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IEEE/RSJ International conference on Intelligent Robots and Systems

作者： Colbert, Steven C. Alqasemi, Redwan Dubey, Rajiv v. Franz, Gregor Woellhaf, Konrad Univ S Florida Dept Mech Engn Tampa FL 33620 USA Univ Appl Sci Ravensburg Weingarten Weingarten Germany

ISBN: (纸本)9781424466757

When planning robotic grasping and manipulation maneuvers, knowledge of the shape and pose of the object of interest is critical information. In order for an autonomous or semi-autonomous system to operate intelligently in an unstructured environment and interact with novel objects, it must have the ability to recover this information at run time, even when no a priori information of the object is available. In this paper, we describe the development and testing of an algorithm that can reconstruct the full 3D geometry of a novel object from just three images. A variant of shape from silhouettes, the algorithm first generates a rough surface approximation in the form of a point cloud. This approximation is then refined by fitting an eleven parameter geometric surface to the points in such a manner that the surface ignores noise and perspective projection shadows. We test the algorithm in both simulation and on several real world objects. We show that the algorithm provides accurate reconstructions that can be directly used to plan grasping maneuvers. Compared to other attempts in the literature, the proposed algorithm is faster, requires fewer images, is more accurate, and degrades gracefully in the presence of bad data. A real world test case is included that shows that the algorithm still yields usable results when the form of the object is amorphous or otherwise non-geometric.

关键词： 3D object reconstruction approximation theory autonomous system camera view cameras grippers image reconstruction image reconstruction manipulation maneuvering pose estimation robot vision robotic grasp planning rough surface approximation rough surfaces semiautonomous system solid modelling vision algorithm

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Reconstructing fluorescent parameters using time-resolved data based on experimental measurement

Reconstructing fluorescent parameters using time-resolved da...

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conference on Multimodal Biomedical Imaging v

作者： Zhang, Limin Gao, Feng Li, Jiao Zhao, Huijuan Tianjin Univ Coll Precis Instrument & Optoeletron Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9780819479532

Time-domain fluorescence diffuse optical tomography (FDOT) can provide information, not only concerning the localization of specific fluorophores, but also about the local fluorophore environment. We present a method based on linear inversion algorithm to reconstruct images of fluorescence yield and lifetime from time-resolved data. To provide efficient solutions, we convert the data type by Laplace transform and adapt normalized Born ratio for its advantages in fluorescence mode. The methodology is experimentally validated in reflection and transmittance measurements by use of time-correlation single photon counting system. We experimentally validate that the proposed scheme can achieve simultaneous three-dimensional reconstruction of the fluorescent yield and lifetime. The results show that for the positions, sizes and shapes of the targets, there are some deviation in reflection measurement, the quality in transmittance one is more satisfied.

关键词： Fluorescence diffuse optical tomography Time-domain image reconstruction algorithm

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Tomographic reconstruction of Nodular images from incomplete data

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AIP conference Proceedings 2010年第1期1301卷 167-174页

作者： G. Ambartsoumian M. Xie aDepartment of Mathematics University of Texas‐Arlington Arlington TX 76019 USA bDepartment of Statistics University of Wisconsin‐Madison Madison WI 53706 USA

In many problems of medical imaging very limited amount of tomographic data can be collected. There are well developed mathematical theories proving that unless certain a priori information is known about the image, some of these limited data sets will be insufficient to generate images of acceptable quality. While in various cases such a priori information is readily available, the translation of this knowledge into mathematical constraints and their subsequent incorporation into image reconstruction algorithms has proved to be a formidable task, and there are very few results on this matter. In this paper we introduce a method that uses the knowledge of image patterns consisting of nodules to stabilize the image reconstruction in incomplete data x‐ray tomography. The technique uses a modified expectation‐maximization algorithm to cluster singularities in Radon domain, and recover the centers and radii of a finite number of nodules in the image.

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Handling of Split-and-Merge Effects and Occlusions using Feature-Based Probabilistic data Association

Handling of Split-and-Merge Effects and Occlusions using Fea...

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27th conference on Intelligent Robots and Computer vision: Algorithms and Techniques

作者： Grinberg, Michael Ohr, Florian Fraunhofer Inst Informat & Data Proc IITB D-761313 Karlsruhe Germany

ISBN: (纸本)9780819479327

One of the big challenges in multi-target tracking is the track management and correct data association between measurements and tracks. Major reason for tracking errors are detection failures such as merged, split, incomplete or missed detections as well as clutter-based detections ( phantom objects). Those effects combined with uncertainties in existence and number of objects in the scene as well as uncertainties in their observability and dynamic object state lead to gross tracking errors. In this contribution we present an algorithm for visual detection and tracking of multiple extended targets which is capable of coping with occlusions and split and merge effects. Unlike most of the state-of-the-art approaches we utilize information about the measurements' composition gained through tracking dedicated feature points in the image and in 3D space, which allows us to reconstruct the desired object characteristics from the data even in the case of detection errors due to above-mentioned reasons. The proposed Feature-Based Probabilistic data Association approach resolves data association ambiguities in a soft threshold-free decision based not only on target state prediction but also on the existence and observability estimation modeled as two additional Markov chains. A novel measurement reconstruction scheme allows for a correct innovation in case of split, merged and incomplete measurements realizing thus a detection-by-tracking approach. This process is assisted by a grid based object representation which offers a lower abstraction level of targets extent and is used for detailed occlusion analysis.

关键词： multitarget tracking 9MTT) feature-based tracking track-before-detect detection-by-tracking probabilistic data association point tracking 6D-vision split and merge handling occlusion handling stereo video environment perception

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Spatial Resolution of the Multiple Coincidences Compton Camera

Spatial Resolution of the Multiple Coincidences Compton Came...

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IEEE Nuclear Science Symposium (NSS)/Medical Imaging conference (MIC)/17th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors

作者： Andreyev, Andriy Sitek, Arkadiusz Celler, Anna Univ British Columbia Med Imaging Res Grp Vancouver BC V5Z 1M9 Canada Brigham & Womens Hosp Harvard Med Sch Dept Radiol Boston MA USA

ISBN: (纸本)9781424491063

In this paper we investigate the limits of spatial image resolution of Multiple Coincidences Compton Camera (MCCC). This technique is based on a simultaneous acquisition of several gammas emitted in cascade from a single nucleus. Contrary to a standard Compton camera, MCCC can theoretically provide a location of a radioactive source without complicated tomographic reconstruction. The commonly mentioned disadvantage of this method is the low probability of coincident triple gamma detection, which is necessary for the source localization. In this paper we investigate an additional fundamental restriction of the multiple coincidence approach which seriously limits the image resolution that can be achieved by MCCC. Our results suggest that it is possible to get better result in terms of spatial image resolution by reconstructing the Compton camera data without multiple coincidence principle than when using the MCCC concept.

关键词： image resolution

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Proton radiography for clinical applications

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2010年第3期612卷 571-575页

作者： Talamonti, C. Reggioli, v. Bruzzi, M. Bucciolini, M. Civinini, C. Marrazzo, L. Menichelli, D. Pallotta, S. Randazzo, N. Sipala, v. Cirrone, G. A. P. Petterson, M. Blumenkrantz, N. Feldt, J. Heimann, J. Lucia, D. Seiden, A. Williams, D. C. Sadrozinski, H. F. -W. Bashkirov, v. Schulte, R. Univ Florence Dipartimento Fisiopatol Clin I-50134 Florence Italy Ist Nazl Fis Nucl Sez Firenze I-50019 Sesto Fiorentino FI Italy Univ Careggi Azienda Osped I-50134 Florence Italy Univ Florence Dipartimento Energet I-50139 Florence Italy Ist Nazl Fis Nucl Sez Catania I-95123 Catania Italy Univ Catania Dipartimento Fis I-95123 Catania Italy Ist Nazl Fis Nucl Lab Nazl Sud I-95123 Catania Italy Univ Calif Santa Cruz SCIPP Santa Cruz CA 95064 USA Loma Linda Univ Med Ctr Loma Linda CA 92354 USA

Proton imaging is not yet applied as a clinical routine, although its advantages have been demonstrated. In the context of quality assurance in proton therapy, proton images c, in be used to verify the correct positioning of the patient and to control the range of protons. Proton c, imputed tomography (pCT) is a 3D imaging method appropriate for planning and verification of proton radiation treatments, because it allows evaluating the distributions of proton stopping power within be tissues and can be directly utilized when the patient is in the actual treatment position. The aim of the PRoton IMAging experiment, supported by INFN, and the PRIN 2006 project, supported by MIUR, is to realize a proton computed radiography (pCR) prototype for reconstruction of proton images from a single projection in order to validate the technique with pre-clinical studies and, eventually, to conceive the configuration of a complete pCT system. A preliminary experiment performed at the 250 Mev proton synchrotron of Loma Linda University Medical Center (LLUMC) allowed acquisition of experimental data before the completion of PRIMA project's prototype. In this paper, the results of the LLUMC experiment are reported and the reconstruction of proton images of two phantoms is discussed. (C) 2009 Elsevier B.v. All rights reserved.

关键词： Proton radiation therapy Proton computed tomography Proton radiography image reconstruction Particle calorimetry Position sensitive particle detectors Proton beams

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Fusing image data with location and orientation sensor data streams for consumer video applications

Fusing image data with location and orientation sensor data ...

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2010 IEEE Computer Society conference on Computer vision and Pattern Recognition - Workshops, CvPRW 2010

作者： Gat, Yoram Kozintsev, Igor Nestares, Oscar Intel Labs Intel Corporation 2200 Mission College Blvd. Santa Clara CA 95054 United States

ISBN: (纸本)9781424470297

We discuss the problem of fusing the information in a video stream with synchronized streams of location and orientation data obtained from sensors attached to the video camera. We are interested in using this information for the reconstruction of camera trajectory and observed scenery from consumer videos with the objective of visualizing those in a 3D virtual environment. We review existing literature and applications and suggest application scenarios for personal video. We discuss the issues that distinguish the personal video application from similar applications and present outlines of algorithms for several consumer video application scenarios. © 2010 IEEE.

关键词： video cameras

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data classification on multiple manifolds

Data classification on multiple manifolds

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International conference on Pattern Recognition

作者： Xiao, Rui Zhao, Qijun Zhang, David Shi, Pengfei Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Department of Computer Science Hongkong Polytechnic University Hongkong Hong Kong

ISBN: (纸本)9780769541099

Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside on different manifolds of possible different dimensions. Therefore, better classification accuracy would be achieved by modeling the data by multiple manifolds each corresponding to a class. To this end, a general framework for data classification on multiple manifolds is presented. The manifolds are firstly learned for each class separately, and a stochastic optimization algorithm is then employed to get the near optimal dimensionality of each manifold from the classification viewpoint. Then, classification is performed under a newly defined minimum reconstruction error based classifier. Our method could be easily extended by involving various manifold learning methods and searching strategies. Experiments on both synthetic data and databases of facial expression images show the effectiveness of the proposed multiple manifold based approach. © 2010 IEEE.

关键词： Classification (of information)

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Learning Manifold from incomplete image Set

Learning Manifold from Incomplete Image Set

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Chinese conference on Pattern Recognition (CCPR)

作者： Liping Gao Huiyong Pan Yubin Zhan School of Computer Zhongyuan University of Technology Zhengzhou Zhengzhou China Computer School National University of Defense Technology Changsha China

Recently, there have been several advances for developing manifold learning algorithms to learn the nonlinear manifold of collected data. To our best knowledge, however, learning manifold from incomplete data set, wherein some features of samples are missing, is still an untouched problem so far. In context of incomplete image set, an improved LTSA algorithm is proposed to learn manifold from corrupted image set. The proposed algorithm exploits an extended EM-based PCA algorithm, which can learn the principal components of incomplete image set only using the known pixels, to obtain the local tangent space coordinates instead of standard SvD technique. Experiments on benchmark data sets demonstrate the effectiveness of the proposed approach.

关键词： Pixel Manifolds image reconstruction Principal component analysis data mining Redundancy Euclidean distance

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