Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

Science.gov (United States)

Awumah, Anna; Mahanti, Prasun; Robinson, Mark

2016-10-01

Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

KAUST Repository

Zhu, Xiaofeng

2015-05-28

This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple visual features, the MMKR first maps them into a high-dimensional space, e.g., a reproducing kernel Hilbert space (RKHS), where test images are then linearly reconstructed by some representative training images, rather than all of them. Furthermore a classification rule is proposed to classify test images. Experimental results on real datasets show the effectiveness of the proposed MMKR while comparing to state-of-the-art algorithms.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

Directory of Open Access Journals (Sweden)

Yuanqiang Ren

2017-05-01

Full Text Available Structural health monitoring (SHM of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

Fall speed measurement and high-resolution multi-angle photography of hydrometeors in free fall

OpenAIRE

T. J. Garrett; C. Fallgatter; K. Shkurko; D. Howlett

2012-01-01

We describe here a new instrument for imaging hydrometeors in free fall. The Multi-Angle Snowflake Camera (MASC) captures high-resolution photographs of hydrometeors from three angles while simultaneously measuring their fall speed. Based on the stereoscopic photographs captured over the two months of continuous measurements obtained at a high altitude location within the Wasatch Front in Utah, we derive statistics for fall speed, hydrometeor size, shape, orientation and asp...

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

Science.gov (United States)

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

Kinematics of reflections in subsurface offset and angle-domain image gathers

Science.gov (United States)

Dafni, Raanan; Symes, William W.

2018-05-01

Seismic migration in the angle-domain generates multiple images of the earth's interior in which reflection takes place at different scattering-angles. Mechanically, the angle-dependent reflection is restricted to happen instantaneously and at a fixed point in space: Incident wave hits a discontinuity in the subsurface media and instantly generates a scattered wave at the same common point of interaction. Alternatively, the angle-domain image may be associated with space-shift (regarded as subsurface offset) extended migration that artificially splits the reflection geometry. Meaning that, incident and scattered waves interact at some offset distance. The geometric differences between the two approaches amount to a contradictory angle-domain behaviour, and unlike kinematic description. We present a phase space depiction of migration methods extended by the peculiar subsurface offset split and stress its profound dissimilarity. In spite of being in radical contradiction with the general physics, the subsurface offset reveals a link to some valuable angle-domain quantities, via post-migration transformations. The angle quantities are indicated by the direction normal to the subsurface offset extended image. They specifically define the local dip and scattering angles if the velocity at the split reflection coordinates is the same for incident and scattered wave pairs. Otherwise, the reflector normal is not a bisector of the opening angle, but of the corresponding slowness vectors. This evidence, together with the distinguished geometry configuration, fundamentally differentiates the angle-domain decomposition based on the subsurface offset split from the conventional decomposition at a common reflection point. An asymptotic simulation of angle-domain moveout curves in layered media exposes the notion of split versus common reflection point geometry. Traveltime inversion methods that involve the subsurface offset extended migration must accommodate the split geometry

Limited-angle tomography for analyzer-based phase-contrast x-ray imaging

International Nuclear Information System (INIS)

Majidi, Keivan; Wernick, Miles N; Brankov, Jovan G; Li, Jun; Muehleman, Carol

2014-01-01

Multiple-image radiography (MIR) is an analyzer-based phase-contrast x-ray imaging method, which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT

Limited-angle tomography for analyzer-based phase-contrast x-ray imaging

Science.gov (United States)

Majidi, Keivan; Wernick, Miles N.; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-07-01

Multiple-image radiography (MIR) is an analyzer-based phase-contrast x-ray imaging method, which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT

MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

Science.gov (United States)

Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

2016-12-01

Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and

Wide-azimuth angle-domain imaging for anisotropic reverse-time migration

KAUST Repository

Sava, Paul C.; Alkhalifah, Tariq Ali

2011-01-01

Extended common-image-point gathers (CIP) constructed by wide-azimuth TI wave-equation migration contain all the necessary information for angle decomposition as a function of the reflection and azimuth angles at selected locations in the subsurface. The reflection and azimuth angles are derived from the extended images using analytic relations between the space-lag and time-lag extensions. This post-imaging decomposition requires only information which is already available at the time of migration, i.e. the model parameters and the tilt angles of the TI medium. The transformation amounts to a linear Radon transform applied to the CIPs obtained after the application of the extended imaging condition. If information about the reflector dip is available at the CIP locations, then only two components of the space-lag vectors are required, thus reducing computational cost and increasing the affordability of the method. This efficient angle decomposition method is suitable for wide-azimuth imaging in anisotropic media with arbitrary orientation of the symmetry plane. © 2011 Society of Exploration Geophysicists.

Enhanced iris recognition method based on multi-unit iris images

Science.gov (United States)

Shin, Kwang Yong; Kim, Yeong Gon; Park, Kang Ryoung

2013-04-01

For the purpose of biometric person identification, iris recognition uses the unique characteristics of the patterns of the iris; that is, the eye region between the pupil and the sclera. When obtaining an iris image, the iris's image is frequently rotated because of the user's head roll toward the left or right shoulder. As the rotation of the iris image leads to circular shifting of the iris features, the accuracy of iris recognition is degraded. To solve this problem, conventional iris recognition methods use shifting of the iris feature codes to perform the matching. However, this increases the computational complexity and level of false acceptance error. To solve these problems, we propose a novel iris recognition method based on multi-unit iris images. Our method is novel in the following five ways compared with previous methods. First, to detect both eyes, we use Adaboost and a rapid eye detector (RED) based on the iris shape feature and integral imaging. Both eyes are detected using RED in the approximate candidate region that consists of the binocular region, which is determined by the Adaboost detector. Second, we classify the detected eyes into the left and right eyes, because the iris patterns in the left and right eyes in the same person are different, and they are therefore considered as different classes. We can improve the accuracy of iris recognition using this pre-classification of the left and right eyes. Third, by measuring the angle of head roll using the two center positions of the left and right pupils, detected by two circular edge detectors, we obtain the information of the iris rotation angle. Fourth, in order to reduce the error and processing time of iris recognition, adaptive bit-shifting based on the measured iris rotation angle is used in feature matching. Fifth, the recognition accuracy is enhanced by the score fusion of the left and right irises. Experimental results on the iris open database of low-resolution images showed that the

The Establishment of the SAR images database System Based on Oracle and ArcSDE

International Nuclear Information System (INIS)

Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

2014-01-01

Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

Automated analysis of angle closure from anterior chamber angle images.

Science.gov (United States)

Baskaran, Mani; Cheng, Jun; Perera, Shamira A; Tun, Tin A; Liu, Jiang; Aung, Tin

2014-10-21

To evaluate a novel software capable of automatically grading angle closure on EyeCam angle images in comparison with manual grading of images, with gonioscopy as the reference standard. In this hospital-based, prospective study, subjects underwent gonioscopy by a single observer, and EyeCam imaging by a different operator. The anterior chamber angle in a quadrant was classified as closed if the posterior trabecular meshwork could not be seen. An eye was classified as having angle closure if there were two or more quadrants of closure. Automated grading of the angle images was performed using customized software. Agreement between the methods was ascertained by κ statistic and comparison of area under receiver operating characteristic curves (AUC). One hundred forty subjects (140 eyes) were included, most of whom were Chinese (102/140, 72.9%) and women (72/140, 51.5%). Angle closure was detected in 61 eyes (43.6%) with gonioscopy in comparison with 59 eyes (42.1%, P = 0.73) using manual grading, and 67 eyes (47.9%, P = 0.24) with automated grading of EyeCam images. The agreement for angle closure diagnosis between gonioscopy and both manual (κ = 0.88; 95% confidence interval [CI), 0.81-0.96) and automated grading of EyeCam images was good (κ = 0.74; 95% CI, 0.63-0.85). The AUC for detecting eyes with gonioscopic angle closure was comparable for manual and automated grading (AUC 0.974 vs. 0.954, P = 0.31) of EyeCam images. Customized software for automated grading of EyeCam angle images was found to have good agreement with gonioscopy. Human observation of the EyeCam images may still be needed to avoid gross misclassification, especially in eyes with extensive angle closure. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Multi-angled Façade System for Office Building Renovation

DEFF Research Database (Denmark)

Hannoudi, Loay Akram; Christensen, Jørgen Erik; Lauring, Michael

renovating office buildings. The architectural potential is presented with the help of AutoCAD software. The energy efficiency and indoor climate are investigated and evaluated by using correlational research and simulation research methods with the software IDA ICE. From a functional perspective, the multi......-angled façade increases the area of the office room and provides more space. There are many potential aesthetic benefits provided by multi-angled façades such as improved optical and visual quality from inside the office room and the possibility for daylight penetration and a view to outside from one part...... compared to a renovated flat façade varies between 4.9 and 6.5 kWh/(m2.year), depending on the orientation of the façade. The increase in the office room area, when renovated with a multi-angled façade, is by 19%, while the increase of the yearly primary energy consumption (not area weighted), is by 4...

A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space

Directory of Open Access Journals (Sweden)

Jinjun Li

2011-01-01

Full Text Available A stereo similarity function based on local multi-model monogenic image feature descriptors (LMFD is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color monogenic signal framework. The gray monogenic signal, which is the extension of analytic signal to gray level image using Dirac operator and Laplace equation, consists of local amplitude, local orientation, and instantaneous phase of 2D image signal. The color monogenic signal is the extension of monogenic signal to color image based on Clifford algebras. The local color phase can be estimated by computing geometric product between the color monogenic signal and a unit reference vector in RGB color space. Experiment results on the synthetic and natural stereo images show the performance of the proposed approach.

A single camera photogrammetry system for multi-angle fast localization of EEG electrodes.

Science.gov (United States)

Qian, Shuo; Sheng, Yang

2011-11-01

Photogrammetry has become an effective method for the determination of electroencephalography (EEG) electrode positions in three dimensions (3D). Capturing multi-angle images of the electrodes on the head is a fundamental objective in the design of photogrammetry system for EEG localization. Methods in previous studies are all based on the use of either a rotating camera or multiple cameras, which are time-consuming or not cost-effective. This study aims to present a novel photogrammetry system that can realize simultaneous acquisition of multi-angle head images in a single camera position. Aligning two planar mirrors with the angle of 51.4°, seven views of the head with 25 electrodes are captured simultaneously by the digital camera placed in front of them. A complete set of algorithms for electrode recognition, matching, and 3D reconstruction is developed. It is found that the elapsed time of the whole localization procedure is about 3 min, and camera calibration computation takes about 1 min, after the measurement of calibration points. The positioning accuracy with the maximum error of 1.19 mm is acceptable. Experimental results demonstrate that the proposed system provides a fast and cost-effective method for the EEG positioning.

A calibrated iterative reconstruction for quantitative photoacoustic tomography using multi-angle light-sheet illuminations

Science.gov (United States)

Wang, Yihan; Lu, Tong; Zhang, Songhe; Song, Shaoze; Wang, Bingyuan; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

Quantitative photoacoustic tomography (q-PAT) is a nontrivial technique can be used to reconstruct the absorption image with a high spatial resolution. Several attempts have been investigated by setting point sources or fixed-angle illuminations. However, in practical applications, these schemes normally suffer from low signal-to-noise ratio (SNR) or poor quantification especially for large-size domains, due to the limitation of the ANSI-safety incidence and incompleteness in the data acquisition. We herein present a q-PAT implementation that uses multi-angle light-sheet illuminations and a calibrated iterative multi-angle reconstruction. The approach can acquire more complete information on the intrinsic absorption and SNR-boosted photoacoustic signals at selected planes from the multi-angle wide-field excitations of light-sheet. Therefore, the sliced absorption maps over whole body can be recovered in a measurementflexible, noise-robust and computation-economic way. The proposed approach is validated by the phantom experiment, exhibiting promising performances in image fidelity and quantitative accuracy.

Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement

Directory of Open Access Journals (Sweden)

Xi Chen

2017-02-01

Full Text Available Aerosol scattering is an important source of error in CO2 retrievals from satellite. This paper presents an analysis of aerosol information content from the Cloud and Aerosol Polarimetric Imager (CAPI onboard the Chinese Carbon Dioxide Observation Satellite (TanSat to be launched in 2016. Based on optimal estimation theory, aerosol information content is quantified from radiance and polarization observed by CAPI in terms of the degrees of freedom for the signal (DFS. A linearized vector radiative transfer model is used with a linearized Mie code to simulate observation and sensitivity (or Jacobians with respect to aerosol parameters. In satellite nadir mode, the DFS for aerosol optical depth is the largest, but for mode radius, it is only 0.55. Observation geometry is found to affect aerosol DFS based on the aerosol scattering phase function from the comparison between different viewing zenith angles or solar zenith angles. When TanSat is operated in target mode, we note that multi-angle retrieval represented by three along-track measurements provides additional 0.31 DFS on average, mainly from mode radius. When adding another two measurements, the a posteriori error decreases by another 2%–6%. The correlation coefficients between retrieved parameters show that aerosol is strongly correlated with surface reflectance, but multi-angle retrieval can weaken this correlation.

Azimuth and angle gathers from wave equation imaging in VTI media

KAUST Repository

Alkhalifah, Tariq Ali

2009-01-01

Angles in common-image angle domain gathers refer to the scattering angle at the reflector and provide a natural access to analyzing migration velocities and amplitudes. In the case of anisotropic media, the importance of angle gathers is enhanced by the need to properly estimate multiple anisotropic parameters for a proper representation of the medium. We extract angle gathers for each downward-continuation step from converting offset-space-frequency planes into angle-space planes simultaneously with applying the imaging condition in a transversely isotropic (VTI) medium. The analytic equations, though cumbersome, are exact within the framework of the acoustic approximation. They are also easily programmable and show that angle gather mapping in the case anisotropic media differs from its isotropic counterpart, difference depending mainly on the strength of anisotropy.

Refining the Concept of Combining Hyperspectral and Multi-Angle Sensors for Land Surface Applications

Science.gov (United States)

Simic, Anita

reflectances. It has been successfully demonstrated that the off-nadir hyperspectral simulations could be closely reconstructed based on the nadir hyperspectral reflectance and off-nadir multi-spectral reflectance in the red and NIR bands. This is shown using the Compact High-resolution Imaging Spectrometer (CHRIS) and Compact Airborne Spectrographic Imager (CASI) data acquired over a forested area in the Sudbury region (Ontario, Canada). Through intensive validation using field data, it is demonstrated that the combination of reflectances at two angles, the hotspot and darkspot, through the Normalized Difference between Hotspot and Darkspot (NDHD) index has the strongest response to changes in vegetation clumping, an important structural component of canopy. Clumping index (O) and Leaf Area Index (LAI) maps are generated based on previous algorithms as well as empirical relationships developed in this study. To retrieve chlorophyll content, inversion of the 5-Scale model is performed by developing Look-Up Tables (LUTs) that are based on the improved structural characteristics developed using multi-angle data. The generated clumping index and LAI maps are used in the LUTs to estimate leaf reflectance. Inversion of the leaf reflectance model, PROSPECT, is further employed to estimate chlorophyll content per unit leaf area. The estimated leaf chlorophyll contents are in good agreement with field-measured values. The refined measurement concept of combining hyperspectral with multispectral multi-angle data provides the opportunity for simultaneous retrieval of vegetation structural and biochemical parameters.

Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

Directory of Open Access Journals (Sweden)

Xiangguang Leng

2017-08-01

Full Text Available Synthetic aperture radar (SAR is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI. Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA. Both Interferometric Wide Swath (IW and Stripmap (SM mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH

Data.gov (United States)

National Aeronautics and Space Administration — MULTI-TEMPORAL REMOTE SENSING IMAGE CLASSIFICATION - A MULTI-VIEW APPROACH VARUN CHANDOLA AND RANGA RAJU VATSAVAI Abstract. Multispectral remote sensing images have...

3D Cloud Tomography, Followed by Mean Optical and Microphysical Properties, with Multi-Angle/Multi-Pixel Data

Science.gov (United States)

Davis, A. B.; von Allmen, P. A.; Marshak, A.; Bal, G.

2010-12-01

The geometrical assumption in all operational cloud remote sensing algorithms is that clouds are plane-parallel slabs, which applies relatively well to the most uniform stratus layers. Its benefit is to justify using classic 1D radiative transfer (RT) theory, where angular details (solar, viewing, azimuthal) are fully accounted for and precise phase functions can be used, to generate the look-up tables used in the retrievals. Unsurprisingly, these algorithms catastrophically fail when applied to cumulus-type clouds, which are highly 3D. This is unfortunate for the cloud-process modeling community that may thrive on in situ airborne data, but would very much like to use satellite data for more than illustrations in their presentations and publications. So, how can we obtain quantitative information from space-based observations of finite aspect ratio clouds? Cloud base/top heights, vertically projected area, mean liquid water content (LWC), and volume-averaged droplet size would be a good start. Motivated by this science need, we present a new approach suitable for sparse cumulus fields where we turn the tables on the standard procedure in cloud remote sensing. We make no a priori assumption about cloud shape, save an approximately flat base, but use brutal approximations about the RT that is necessarily 3D. Indeed, the first order of business is to roughly determine the cloud's outer shape in one of two ways, which we will frame as competing initial guesses for the next phase of shape refinement and volume-averaged microphysical parameter estimation. Both steps use multi-pixel/multi-angle techniques amenable to MISR data, the latter adding a bi-spectral dimension using collocated MODIS data. One approach to rough cloud shape determination is to fit the multi-pixel/multi-angle data with a geometric primitive such as a scalene hemi-ellipsoid with 7 parameters (translation in 3D space, 3 semi-axes, 1 azimuthal orientation); for the radiometry, a simple radiosity

Multi-granularity synthesis segmentation for high spatial resolution Remote sensing images

International Nuclear Information System (INIS)

Yi, Lina; Liu, Pengfei; Qiao, Xiaojun; Zhang, Xiaoning; Gao, Yuan; Feng, Boyan

2014-01-01

Traditional segmentation method can only partition an image in a single granularity space, with segmentation accuracy limited to the single granularity space. This paper proposes a multi-granularity synthesis segmentation method for high spatial resolution remote sensing images based on a quotient space model. Firstly, we divide the whole image area into multiple granules (regions), each region is consisted of ground objects that have similar optimal segmentation scale, and then select and synthesize the sub-optimal segmentations of each region to get the final segmentation result. To validate this method, the land cover category map is used to guide the scale synthesis of multi-scale image segmentations for Quickbird image land use classification. Firstly, the image is coarsely divided into multiple regions, each region belongs to a certain land cover category. Then multi-scale segmentation results are generated by the Mumford-Shah function based region merging method. For each land cover category, the optimal segmentation scale is selected by the supervised segmentation accuracy assessment method. Finally, the optimal scales of segmentation results are synthesized under the guide of land cover category. Experiments show that the multi-granularity synthesis segmentation can produce more accurate segmentation than that of a single granularity space and benefit the classification

Space-Time Quantum Imaging

Directory of Open Access Journals (Sweden)

Ronald E. Meyers

2015-03-01

Full Text Available We report on an experimental and theoretical investigation of quantum imaging where the images are stored in both space and time. Ghost images of remote objects are produced with either one or two beams of chaotic laser light generated by a rotating ground glass and two sensors measuring the reference field and bucket field at different space-time points. We further observe that the ghost images translate depending on the time delay between the sensor measurements. The ghost imaging experiments are performed both with and without turbulence. A discussion of the physics of the space-time imaging is presented in terms of quantum nonlocal two-photon analysis to support the experimental results. The theoretical model includes certain phase factors of the rotating ground glass. These experiments demonstrated a means to investigate the time and space aspects of ghost imaging and showed that ghost imaging contains more information per measured photon than was previously recognized where multiple ghost images are stored within the same ghost imaging data sets. This suggests new pathways to explore quantum information stored not only in multi-photon coincidence information but also in time delayed multi-photon interference. The research is applicable to making enhanced space-time quantum images and videos of moving objects where the images are stored in both space and time.

Discriminative Multi-View Interactive Image Re-Ranking.

Science.gov (United States)

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Multi-Angle Snowflake Camera Value-Added Product

Energy Technology Data Exchange (ETDEWEB)

Shkurko, Konstantin [Univ. of Utah, Salt Lake City, UT (United States); Garrett, T. [Univ. of Utah, Salt Lake City, UT (United States); Gaustad, K [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2016-12-01

The Multi-Angle Snowflake Camera (MASC) addresses a need for high-resolution multi-angle imaging of hydrometeors in freefall with simultaneous measurement of fallspeed. As illustrated in Figure 1, the MASC consists of three cameras, separated by 36°, each pointing at an identical focal point approximately 10 cm away. Located immediately above each camera, a light aims directly at the center of depth of field for its corresponding camera. The focal point at which the cameras are aimed lies within a ring through which hydrometeors fall. The ring houses a system of near-infrared emitter-detector pairs, arranged in two arrays separated vertically by 32 mm. When hydrometeors pass through the lower array, they simultaneously trigger all cameras and lights. Fallspeed is calculated from the time it takes to traverse the distance between the upper and lower triggering arrays. The trigger electronics filter out ambient light fluctuations associated with varying sunlight and shadows. The microprocessor onboard the MASC controls the camera system and communicates with the personal computer (PC). The image data is sent via FireWire 800 line, and fallspeed (and camera control) is sent via a Universal Serial Bus (USB) line that relies on RS232-over-USB serial conversion. See Table 1 for specific details on the MASC located at the Oliktok Point Mobile Facility on the North Slope of Alaska. The value-added product (VAP) detailed in this documentation analyzes the raw data (Section 2.0) using Python: images rely on OpenCV image processing library and derived aggregated statistics rely on some clever averaging. See Sections 4.1 and 4.2 for more details on what variables are computed.

Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

Science.gov (United States)

Li, Dengwang; Li, Hongsheng; Wan, Honglin; Chen, Jinhu; Gong, Guanzhong; Wang, Hongjun; Wang, Liming; Yin, Yong

2012-08-01

Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5-8% for mono-modality and 10-14% for multi-modality registration under the same condition. Furthermore, clinical application by adaptive

Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

International Nuclear Information System (INIS)

Li Dengwang; Wan Honglin; Li Hongsheng; Chen Jinhu; Gong Guanzhong; Yin Yong; Wang Hongjun; Wang Liming

2012-01-01

Mutual information (MI) is a well-accepted similarity measure for image registration in medical systems. However, MI-based registration faces the challenges of high computational complexity and a high likelihood of being trapped into local optima due to an absence of spatial information. In order to solve these problems, multi-scale frameworks can be used to accelerate registration and improve robustness. Traditional Gaussian pyramid representation is one such technique but it suffers from contour diffusion at coarse levels which may lead to unsatisfactory registration results. In this work, a new multi-scale registration framework called edge preserving multiscale registration (EPMR) was proposed based upon an edge preserving total variation L1 norm (TV-L1) scale space representation. TV-L1 scale space is constructed by selecting edges and contours of images according to their size rather than the intensity values of the image features. This ensures more meaningful spatial information with an EPMR framework for MI-based registration. Furthermore, we design an optimal estimation of the TV-L1 parameter in the EPMR framework by training and minimizing the transformation offset between the registered pairs for automated registration in medical systems. We validated our EPMR method on both simulated mono- and multi-modal medical datasets with ground truth and clinical studies from a combined positron emission tomography/computed tomography (PET/CT) scanner. We compared our registration framework with other traditional registration approaches. Our experimental results demonstrated that our method outperformed other methods in terms of the accuracy and robustness for medical images. EPMR can always achieve a small offset value, which is closer to the ground truth both for mono-modality and multi-modality, and the speed can be increased 5–8% for mono-modality and 10–14% for multi-modality registration under the same condition. Furthermore, clinical application by

Space-based infrared sensors of space target imaging effect analysis

Science.gov (United States)

Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang

2018-02-01

Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.

Feature-based Alignment of Volumetric Multi-modal Images

Science.gov (United States)

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Image degradation characteristics and restoration based on regularization for diffractive imaging

Science.gov (United States)

Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

2017-11-01

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

Science.gov (United States)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Development of the algorithm of measurement data and tomographic section reconstruction results processing for evaluating the respiratory activity of the lungs using the multi-angle electric impedance tomography

Science.gov (United States)

Aleksanyan, Grayr; Shcherbakov, Ivan; Kucher, Artem; Sulyz, Andrew

2018-04-01

Continuous monitoring of the patient's breathing by the method of multi-angle electric impedance tomography allows to obtain images of conduction change in the chest cavity during the monitoring. Direct analysis of images is difficult due to the large amount of information and low resolution images obtained by multi-angle electrical impedance tomography. This work presents a method for obtaining a graph of respiratory activity of the lungs based on the results of continuous lung monitoring using the multi-angle electrical impedance tomography method. The method makes it possible to obtain a graph of the respiratory activity of the left and right lungs separately, as well as a summary graph, to which it is possible to apply methods of processing the results of spirography.

T2 image contrast evaluation using three dimension sampling perfection with application optimized contrasts using different flip angle evolution (3D-SPACE)

International Nuclear Information System (INIS)

Yamazaki, Ryo; Hiura, Yukikazu; Tsuji, Akio; Nishiki, Shigeo; Uchikoshi, Masato

2011-01-01

Sampling perfection with application optimized contrasts using different flip angle evolution (3D-SPACE) sequence enables one to decrease specific absorption rate (SAR) by using variable flip angle refocusing pulse. Therefore, it is expected that the contrast obtained with 3D-SPACE sequences is different from that of spin echo (SE) images and turbo spin echo (TSE) images. The purpose of this study was to evaluate the characteristics of the signal intensity and central nervous system (CNS) image contrast in T 2 weighted 3D-SPACE. Using 3 different sequences (SE, 3D-TSE and 3D-SPACE) with repetition time (TR)/ echo time (TE)=3500/70, 90 and 115 ms, we obtained T 2 weighted magnetic resonance (MR) images of inhouse phantom and five healthy volunteers' brain. Signal intensity of the phantom which contains various T 1 and T 2 value was evaluated. Tissue contrasts of white/gray matter, cerebrospinal fluid (CSF)/subcutaneous fat and gray matter/subcutaneous fat were evaluated for a clinical image study. The phantom study showed that signal intensity in 3D-SPACE significantly decreased under a T 1 value of 250 ms. It was markedly decreased in comparison to other sequences, as effective echo time (TE) was extended. White/gray matter contrast of 3D-SPACE was the highest in all sequences. On the other hand, CSF/fat and gray matter/fat contrast of 3D-SPACE was higher than TSE but lower than SE. CNS image contrasts of 3D-SPACE were comparable to that of SE. Signal intensity had decreased in the range where T 1 and T 2 values were extremely short. (author)

Monitoring of desert dune topography by multi angle sensors

Science.gov (United States)

Yun, J.; Kim, J.; Choi, Y.; Yun, H.

2011-12-01

Nowadays, the sandy desert is rapidly expanding world widely and results in a lot of risks in the socio-econimical aspects as well as the anthropogenic activities. For example, the increasing occurrences of mineral dust storm which presumably originated from the sandy deserts in northwest China become a serious threat in human activities as well as public health over Far East Asian area as the interpretation by the MODIS analysis (Zhang et al., 2007) and the particle trajectory simulation with HYSPLYT (HYbrid Single-Particle Lagrangian Integrated Trajectory) (Kim et al., 2011) identified. Since the sand dune activity has been recognized as an essential indicator of the progressive desertification, it is important to establish the monitoring method for the variations of topographic properties by the dune activities such as local roughness. Thus it will provide the crucial data about the extent and the transition of sandy desert. For example, it is well known the aerodynamic roughness lengths Zo which can be driven from the specialized sensor such as POLDER (POLarization and Directionality of the Earth's Reflectances) is essential to understand desert dune characteristics. However, for the multi temporal observation of dune fields, the availability of data set to extract Zo is limited. Therefore, we employed MISR (Multi angle imaging Spectro Radiometer) image sequence to extract multi angle topographic parameters such as NDAI (Normalized Difference Angular Index) or the variation of radiance with the viewing geometry which are representing the characteristics of target desert topography instead of Zo. In our approach, NDAI were expanded to the all viewing angles and then compared over the target sandy desert and the surrounding land covers. It showed very strong consistencies according to the land cover type and especially over the dynamic dune fields. On the other hands, the variation of NDAIs of sandy desert combining with the metrological observations were

A method of directly extracting multiwave angle-domain common-image gathers

Science.gov (United States)

Han, Jianguang; Wang, Yun

2017-10-01

Angle-domain common-image gathers (ADCIGs) can provide an effective way for migration velocity analysis and amplitude versus angle analysis in oil-gas seismic exploration. On the basis of multi-component Gaussian beam prestack depth migration (GB-PSDM), an alternative method of directly extracting multiwave ADCIGs is presented in this paper. We first introduce multi-component GB-PSDM, where a wavefield separation is proceeded to obtain the separated PP- and PS-wave seismic records before migration imaging for multiwave seismic data. Then, the principle of extracting PP- and PS-ADCIGs using GB-PSDM is presented. The propagation angle can be obtained using the real-value travel time of Gaussian beam in the course of GB-PSDM, which can be used to calculate the incidence and reflection angles. Two kinds of ADCIGs can be extracted for the PS-wave, one of which is P-wave incidence ADCIGs and the other one is S-wave reflection ADCIGs. In this paper, we use the incident angle to plot the ADCIGs for both PP- and PS-waves. Finally, tests of synthetic examples show that the method introduced here is accurate and effective.

Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

Directory of Open Access Journals (Sweden)

Myung-Ho Ju

2013-10-01

Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

Angle-of-arrival-based gesture recognition using ultrasonic multi-frequency signals

KAUST Repository

Chen, Hui

2017-11-02

Hand gestures are tools for conveying information, expressing emotion, interacting with electronic devices or even serving disabled people as a second language. A gesture can be recognized by capturing the movement of the hand, in real time, and classifying the collected data. Several commercial products such as Microsoft Kinect, Leap Motion Sensor, Synertial Gloves and HTC Vive have been released and new solutions have been proposed by researchers to handle this task. These systems are mainly based on optical measurements, inertial measurements, ultrasound signals and radio signals. This paper proposes an ultrasonic-based gesture recognition system using AOA (Angle of Arrival) information of ultrasonic signals emitted from a wearable ultrasound transducer. The 2-D angles of the moving hand are estimated using multi-frequency signals captured by a fixed receiver array. A simple redundant dictionary matching classifier is designed to recognize gestures representing the numbers from `0\\' to `9\\' and compared with a neural network classifier. Average classification accuracies of 95.5% and 94.4% are obtained, respectively, using the two classification methods.

Two wide-angle imaging neutral-atom spectrometers

Energy Technology Data Exchange (ETDEWEB)

McComas, D.J.

1997-12-31

The Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) mission provides a new capability for stereoscopically imaging the magnetosphere. By imaging the charge exchange neutral atoms over a broad energy range (1 < E , {approximately} 100 keV) using two identical instruments on two widely-spaced high-altitude, high-inclination spacecraft, TWINS will enable the 3-dimensional visualization and the resolution of large scale structures and dynamics within the magnetosphere for the first time. These observations will provide a leap ahead in the understanding of the global aspects of the terrestrial magnetosphere and directly address a number of critical issues in the ``Sun-Earth Connections`` science theme of the NASA Office of Space Science.

Two wide-angle imaging neutral-atom spectrometers

International Nuclear Information System (INIS)

McComas, D.J.

1997-01-01

The Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) mission provides a new capability for stereoscopically imaging the magnetosphere. By imaging the charge exchange neutral atoms over a broad energy range (1 < E , ∼ 100 keV) using two identical instruments on two widely-spaced high-altitude, high-inclination spacecraft, TWINS will enable the 3-dimensional visualization and the resolution of large scale structures and dynamics within the magnetosphere for the first time. These observations will provide a leap ahead in the understanding of the global aspects of the terrestrial magnetosphere and directly address a number of critical issues in the ''Sun-Earth Connections'' science theme of the NASA Office of Space Science

ℓ0 Gradient Minimization Based Image Reconstruction for Limited-Angle Computed Tomography.

Directory of Open Access Journals (Sweden)

Wei Yu

Full Text Available In medical and industrial applications of computed tomography (CT imaging, limited by the scanning environment and the risk of excessive X-ray radiation exposure imposed to the patients, reconstructing high quality CT images from limited projection data has become a hot topic. X-ray imaging in limited scanning angular range is an effective imaging modality to reduce the radiation dose to the patients. As the projection data available in this modality are incomplete, limited-angle CT image reconstruction is actually an ill-posed inverse problem. To solve the problem, image reconstructed by conventional filtered back projection (FBP algorithm frequently results in conspicuous streak artifacts and gradual changed artifacts nearby edges. Image reconstruction based on total variation minimization (TVM can significantly reduce streak artifacts in few-view CT, but it suffers from the gradual changed artifacts nearby edges in limited-angle CT. To suppress this kind of artifacts, we develop an image reconstruction algorithm based on ℓ0 gradient minimization for limited-angle CT in this paper. The ℓ0-norm of the image gradient is taken as the regularization function in the framework of developed reconstruction model. We transformed the optimization problem into a few optimization sub-problems and then, solved these sub-problems in the manner of alternating iteration. Numerical experiments are performed to validate the efficiency and the feasibility of the developed algorithm. From the statistical analysis results of the performance evaluations peak signal-to-noise ratio (PSNR and normalized root mean square distance (NRMSD, it shows that there are significant statistical differences between different algorithms from different scanning angular ranges (p<0.0001. From the experimental results, it also indicates that the developed algorithm outperforms classical reconstruction algorithms in suppressing the streak artifacts and the gradual changed

Attenuation of multiples in image space

Science.gov (United States)

Alvarez, Gabriel F.

In complex subsurface areas, attenuation of 3D specular and diffracted multiples in data space is difficult and inaccurate. In those areas, image space is an attractive alternative. There are several reasons: (1) migration increases the signal-to-noise ratio of the data; (2) primaries are mapped to coherent events in Subsurface Offset Domain Common Image Gathers (SODCIGs) or Angle Domain Common Image Gathers (ADCIGs); (3) image space is regular and smaller; (4) attenuating the multiples in data space leaves holes in the frequency-Wavenumber space that generate artifacts after migration. I develop a new equation for the residual moveout of specular multiples in ADCIGs and use it for the kernel of an apex-shifted Radon transform to focus and separate the primaries from specular and diffracted multiples. Because of small amplitude, phase and kinematic errors in the multiple estimate, we need adaptive matching and subtraction to estimate the primaries. I pose this problem as an iterative least-squares inversion that simultaneously matches the estimates of primaries and multiples to the data. Standard methods match only the estimate of the multiples. I demonstrate with real and synthetic data that the method produces primaries and multiples with little cross-talk. In 3D, the multiples exhibit residual moveout in SODCIGs in in-line and cross-line offsets. They map away from zero subsurface offsets when migrated with the faster velocity of the primaries. In ADCIGs the residual moveout of the primaries as a function of the aperture angle, for a given azimuth, is flat for those angles that illuminate the reflector. The multiples have residual moveout towards increasing depth for increasing aperture angles at all azimuths. As a function of azimuth, the primaries have better azimuth resolution than the multiples at larger aperture angles. I show, with a real 3D dataset, that even below salt, where illumination is poor, the multiples are well attenuated in ADCIGs with the new

Multi-Angle Imager for Aerosols (MAIA) Investigation of Airborne Particle Health Impacts

Science.gov (United States)

Diner, D. J.

2016-12-01

Airborne particulate matter (PM) is a well-known cause of heart disease, cardiovascular and respiratory illness, low birth weight, and lung cancer. The Global Burden of Disease (GBD) Study ranks PM as a major environmental risk factor worldwide. Global maps of PM2.5concentrations derived from satellite instruments, including MISR and MODIS, have provided key contributions to the GBD and many other health-related investigations. Although it is well established that PM exposure increases the risks of mortality and morbidity, our understanding of the relative toxicity of specific PM types is relatively poor. To address this, the Multi-Angle Imager for Aerosols (MAIA) investigation was proposed to NASA's third Earth Venture Instrument (EVI-3) solicitation. The satellite instrument that is part of the investigation is a multiangle, multispectral, and polarimetric camera system based on the first and second generation Airborne Multiangle SpectroPolarimetric Imagers, AirMSPI and AirMSPI-2. MAIA was selected for funding in March 2016. Estimates of the abundances of different aerosol types from the WRF-Chem model will be combined with MAIA instrument data. Geostatistical models derived from collocated surface and MAIA retrievals will then be used to relate retrieved fractional column aerosol optical depths to near-surface concentrations of major PM constituents, including sulfate, nitrate, organic carbon, black carbon, and dust. Epidemiological analyses of geocoded birth, death, and hospital records will be used to associate exposure to PM types with adverse health outcomes. MAIA launch is planned for early in the next decade. The MAIA instrument incorporates a pair of cameras on a two-axis gimbal to provide regional multiangle observations of selected, globally distributed target areas. Primary Target Areas (PTAs) on five continents are chosen to include major population centers covering a range of PM concentrations and particle types, surface-based aerosol sunphotometers

Uniting Satellite Data With Health Records to Address the Societal Impacts of Particulate Air Pollution: NASA's Multi-Angle Imager for Aerosols

Science.gov (United States)

Nastan, A.; Diner, D. J.

2017-12-01

Epidemiological studies have demonstrated convincingly that airborne particulate matter has a major impact on human health, particularly in urban areas. However, providing an accurate picture of the health effects of various particle mixtures — distinguished by size, shape, and composition — is difficult due to the constraints of currently available measurement tools and the heterogeneity of atmospheric chemistry and human activities over space and time. The Multi-Angle Imager for Aerosols (MAIA) investigation, currently in development as part of NASA's Earth Venture Instrument Program, will address this issue through a powerful combination of technologies and informatics. Atmospheric measurements collected by the MAIA satellite instrument featuring multiangle and innovative polarimetric imaging capabilities will be combined with available ground monitor data and a chemical transport model to produce maps of speciated particulate matter at 1 km spatial resolution for a selected set of globally distributed cities. The MAIA investigation is also original in integrating data providers (atmospheric scientists), data users (epidemiologists), and stakeholders (public health experts) into a multidisciplinary science team that will tailor the observation and analysis strategy within each target area to improve our understanding of the linkages between different particle types and adverse human health outcomes.

Angle-of-arrival-based gesture recognition using ultrasonic multi-frequency signals

KAUST Repository

Chen, Hui; Ballal, Tarig; Saad, Mohamed; Al-Naffouri, Tareq Y.

2017-01-01

transducer. The 2-D angles of the moving hand are estimated using multi-frequency signals captured by a fixed receiver array. A simple redundant dictionary matching classifier is designed to recognize gestures representing the numbers from `0' to `9

IoSiS: a radar system for imaging of satellites in space

Science.gov (United States)

Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.

2017-05-01

Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.

Multi-band Image Registration Method Based on Fourier Transform

Institute of Scientific and Technical Information of China (English)

庹红娅; 刘允才

2004-01-01

This paper presented a registration method based on Fourier transform for multi-band images which is involved in translation and small rotation. Although different band images differ a lot in the intensity and features,they contain certain common information which we can exploit. A model was given that the multi-band images have linear correlations under the least-square sense. It is proved that the coefficients have no effect on the registration progress if two images have linear correlations. Finally, the steps of the registration method were proposed. The experiments show that the model is reasonable and the results are satisfying.

A kernel-based multi-feature image representation for histopathology image classification

International Nuclear Information System (INIS)

Moreno J; Caicedo J Gonzalez F

2010-01-01

This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

J Carlos Moreno

2010-09-01

Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

A diagnostic imaging approach for online characterization of multi-impact in aircraft composite structures based on a scanning spatial-wavenumber filter of guided wave

Science.gov (United States)

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Su, Zhongqing

2017-06-01

Monitoring of impact and multi-impact in particular in aircraft composite structures has been an intensive research topic in the field of guided-wave-based structural health monitoring (SHM). Compared with the majority of existing methods such as those using signal features in the time-, frequency- or joint time-frequency domain, the approach based on spatial-wavenumber filter of guided wave shows superb advantage in effectively distinguishing particular wave modes and identifying their propagation direction relative to the sensor array. However, there exist two major issues when conducting online characterization of multi-impact event. Firstly, the spatial-wavenumber filter should be realized in the situation that the wavenumber of high spatial resolution of the complicated multi-impact signal cannot be measured or modeled. Secondly, it's difficult to identify the multiple impacts and realize multi-impact localization due to the overlapping of wavenumbers. To address these issues, a scanning spatial-wavenumber filter based diagnostic imaging method for online characterization of multi-impact event is proposed to conduct multi-impact imaging and localization in this paper. The principle of the scanning filter for multi-impact is developed first to conduct spatial-wavenumber filtering and to achieve wavenumber-time imaging of the multiple impacts. Then, a feature identification method of multi-impact based on eigenvalue decomposition and wavenumber searching is presented to estimate the number of impacts and calculate the wavenumber of the multi-impact signal, and an image mapping method is proposed as well to convert the wavenumber-time image to an angle-distance image to distinguish and locate the multiple impacts. A series of multi-impact events are applied to a carbon fiber laminate plate to validate the proposed methods. The validation results show that the localization of the multiple impacts are well achieved.

A target field design of open multi-purpose RF coil for musculoskeletal MR imaging at 3T.

Science.gov (United States)

Gao, Fei; Zhang, Rui; Zhou, Diange; Wang, Xiaoying; Huang, Kefu; Zhang, Jue

2016-10-01

Musculoskeletal MR imaging under multi-angle situations plays an increasingly important role in assessing joint and muscle tissues system. However, there are still limitations due to the closed structures of most conventional RF coils. In this study, a time-harmonic target-field method was employed to design open multi-purpose coil (OMC) for multi-angle musculoskeletal MR imaging. The phantom imaging results suggested that the proposed OMC could achieve homogeneously distributed magnetic field and high signal-to-noise ratio (SNR) of 239.04±0.83 in the region of interest (ROI). The maximum temperature in the heating hazard test was 16°C lower than the standard regulation, which indicated the security of the designed OMC. Furthermore, to demonstrate the effectiveness of the proposed OMC for musculoskeletal MR imaging, especially for multi-angle imaging, a healthy volunteer was examined for MR imaging of elbow, ankle and knee using OMC. The in vivo imaging results showed that the proposed OMC is effective for MR imaging of musculoskeletal tissues at different body parts, with satisfied B1 field homogeneity and SNR. Moreover, the open structure of the OMC could provide a large joint movement region. The proposed open multi-purpose coil is feasible for musculoskeletal MR imaging, and potentially, it is more suitable for the evaluation of musculoskeletal tissues under multi-angle conditions. Copyright © 2016. Published by Elsevier Inc.

MODTRAN Radiance Modeling of Multi-Angle Worldview-2 Imagery

Science.gov (United States)

2013-09-01

listed below. a. MISR NASA’s Multi-angle Imaging Spectro-radiometer (MISR) was launched in 1999 aboard the Terra EOS AM-1 satellite at a 705 km sun...expected for green vegetation , the albedo values for GRASS are generally dark up until the IR ledge (~700 nm), at which point they increase quickly to...http://calhoun.nps.edu/public/bitstream/handle/10945/5102/10Dec_McConnon.pd f?sequence=1 NASA JPL. (2013). MISR: EOS and Terra . Retrieved from MISR

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

International Nuclear Information System (INIS)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

2015-01-01

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

Energy Technology Data Exchange (ETDEWEB)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr [Department of Electrical Engineering, KAIST, Daejeon 305-701 (Korea, Republic of)

2015-05-15

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of

Angle-independent measure of motion for image-based gating in 3D coronary angiography

International Nuclear Information System (INIS)

Lehmann, Glen C.; Holdsworth, David W.; Drangova, Maria

2006-01-01

The role of three-dimensional (3D) image guidance for interventional procedures and minimally invasive surgeries is increasing for the treatment of vascular disease. Currently, most interventional procedures are guided by two-dimensional x-ray angiography, but computed rotational angiography has the potential to provide 3D geometric information about the coronary arteries. The creation of 3D angiographic images of the coronary arteries requires synchronization of data acquisition with respect to the cardiac cycle, in order to minimize motion artifacts. This can be achieved by inferring the extent of motion from a patient's electrocardiogram (ECG) signal. However, a direct measurement of motion (from the 2D angiograms) has the potential to improve the 3D angiographic images by ensuring that only projections acquired during periods of minimal motion are included in the reconstruction. This paper presents an image-based metric for measuring the extent of motion in 2D x-ray angiographic images. Adaptive histogram equalization was applied to projection images to increase the sharpness of coronary arteries and the superior-inferior component of the weighted centroid (SIC) was measured. The SIC constitutes an image-based metric that can be used to track vessel motion, independent of apparent motion induced by the rotational acquisition. To evaluate the technique, six consecutive patients scheduled for routine coronary angiography procedures were studied. We compared the end of the SIC rest period (ρ) to R-waves (R) detected in the patient's ECG and found a mean difference of 14±80 ms. Two simultaneous angular positions were acquired and ρ was detected for each position. There was no statistically significant difference (P=0.79) between ρ in the two simultaneously acquired angular positions. Thus we have shown the SIC to be independent of view angle, which is critical for rotational angiography. A preliminary image-based gating strategy that employed the SIC was

Fall speed measurement and high-resolution multi-angle photography of hydrometeors in free fall

Directory of Open Access Journals (Sweden)

T. J. Garrett

2012-11-01

Full Text Available We describe here a new instrument for imaging hydrometeors in free fall. The Multi-Angle Snowflake Camera (MASC captures high-resolution photographs of hydrometeors from three angles while simultaneously measuring their fall speed. Based on the stereoscopic photographs captured over the two months of continuous measurements obtained at a high altitude location within the Wasatch Front in Utah, we derive statistics for fall speed, hydrometeor size, shape, orientation and aspect ratio. From a selection of the photographed hydrometeors, an illustration is provided for how the instrument might be used for making improved microwave scattering calculations. Complex, aggregated snowflake shapes appear to be more strongly forward scattering, at the expense of reduced back-scatter, than heavily rimed graupel particles of similar size.

TU-CD-BRA-05: Atlas Selection for Multi-Atlas-Based Image Segmentation Using Surrogate Modeling

International Nuclear Information System (INIS)

Zhao, T; Ruan, D

2015-01-01

Purpose: The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi-atlas-based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi-atlas-based image segmentation. Methods: We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non-decreasing function with additive random perturbations. Subsequently, a surrogate’s ability to prognosticate the oracle order for atlas subset selection is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images. Results: The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly-used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation. Conclusion: This work has developed an efficacious probabilistic model to characterize the image-based surrogate metric on atlas selection

Dynamic measurement of pennation angle of gastrocnemius muscles during contractions based on ultrasound imaging

Directory of Open Access Journals (Sweden)

Zhou Yongjin

2012-09-01

Full Text Available Abstract Background Muscle fascicle pennation angle (PA is an important parameter related to musculoskeletal functions, and ultrasound imaging has been widely used for measuring PA, but manually and frame by frame in most cases. We have earlier reported an automatic method to estimate aponeurosis orientation based on Gabor transform and Revoting Hough Transform (RVHT. Methods In this paper, we proposed a method to estimate the overall orientation of muscle fascicles in a region of interest, in order to complete computing the orientation of the other side of the pennation angle, but the side found by RVHT. The measurements for orientations of both fascicles and aponeurosis were conducted in each frame of ultrasound images, and then the dynamic change of pennation angle during muscle contraction was obtained automatically. The method for fascicle orientation estimation was evaluated using synthetic images with different noise levels and later on 500 ultrasound images of human gastrocnemius muscles during isometric plantarflexion. Results The muscle fascicle orientations were also estimated manually by two operators. From the results it’s found that the proposed automatic method demonstrated a comparable performance to the manual method. Conclusions With the proposed methods, ultrasound measurement for muscle pennation angles can be more widely used for functional assessment of muscles.

The Zeldovich approximation and wide-angle redshift-space distortions

Science.gov (United States)

Castorina, Emanuele; White, Martin

2018-06-01

The contribution of line-of-sight peculiar velocities to the observed redshift of objects breaks the translational symmetry of the underlying theory, modifying the predicted 2-point functions. These `wide angle effects' have mostly been studied using linear perturbation theory in the context of the multipoles of the correlation function and power spectrum . In this work we present the first calculation of wide angle terms in the Zeldovich approximation, which is known to be more accurate than linear theory on scales probed by the next generation of galaxy surveys. We present the exact result for dark matter and perturbatively biased tracers as well as the small angle expansion of the configuration- and Fourier-space two-point functions and the connection to the multi-frequency angular power spectrum. We compare different definitions of the line-of-sight direction and discuss how to translate between them. We show that wide angle terms can reach tens of percent of the total signal in a measurement at low redshift in some approximations, and that a generic feature of wide angle effects is to slightly shift the Baryon Acoustic Oscillation scale.

METHOD OF IMAGE QUALITY ENHANCEMENT FOR SPACE OBJECTS

Directory of Open Access Journals (Sweden)

D. S. Korshunov

2014-07-01

Full Text Available The paper deals with an approach for image quality improvement of the space objects in the visible range of electromagnetic wave spectrum. The proposed method is based on the joint taking into account of both the motion velocity of the space supervisory apparatus and a space object observed in the near-earth space when the time of photo-detector exposure is chosen. The timing of exposure is carried out by light-signal characteristics, which determines the optimal value of the charge package formed in the charge-coupled device being irradiated. Thus, the parameters of onboard observation equipment can be selected, which provides space images suitable for interpretation. The linear resolving capacity is used as quality indicator for space images, giving a complete picture for the image contrast and geometric properties of the object on the photo. Observation scenario modeling of the space object, done by sputnik-inspector, has shown the possibility of increasing the linear resolution up to10% - 20% or up to 40% - 50% depending on the non-complanarity angle at the movement along orbits. The proposed approach to the increase of photographs quality provides getting sharp and highcontrast images of space objects by the optical-electronic equipment of the space-based remote sensing. The usage of these images makes it possible to detect in time the space technology failures, which are the result of its exploitation in the nearearth space. The proposed method can be also applied at the stage of space systems design for optical-electronic surveillance in computer models used for facilities assessment of the shooting equipment information tract.

Network based multi-channel digital flash X-ray imaging system

International Nuclear Information System (INIS)

Wang Jingjin; Yuan Jie; Liu Yaqiang; Lin Yong; Song Zheng; Liu Keyin; Zhang Qi; Zheng Futang

2000-01-01

A network based multi-channel digital flash X-ray imaging system has been developed. It can be used to acquire and digitize orthogonal flash X-ray images in multi-interval, and to distribute the images on the network. There is no need of films and chemical process, no anxiety of waiting and no trouble of film archiving. This system is useful for testing ballistics, jet, explode, armour-piercing and fast running machines. The system composing and acquired images are presented. The software for object separating, mass calculating, 3D positioning, speed determining and cavity reconstruction are described

Network based multi-channel digital flash X-ray imaging system

International Nuclear Information System (INIS)

Wang Jingjin; Yuan Jie; Liu Yaqiang; Lin Yong; Song Zheng; Liu Keyin

2003-01-01

A network based multi-channel digital flash X-ray imaging system has been developed. It can be used to acquire and digitize orthogonal flash X-ray images in multi-interval, and to distribute the images on the network. There is no need of films and chemical process, no anxiety of waiting and no trouble of film archiving. This system is useful for testing ballistics, jet, explode, armour-piercing and fast running machines. The system composing and acquired images of terminal ballistics are presented. The software for object separating, profile calculating and 3D cavity reconstruction are described

Path integral of the angular momentum eigenstates evolving with the parameter linked with rotation angle under the space rotation transformation

International Nuclear Information System (INIS)

Zhang Zhongcan; Hu Chenguo; Fang Zhenyun

1998-01-01

The authors study the method which directly adopts the azimuthal angles and the rotation angle of the axis to describe the evolving process of the angular momentum eigenstates under the space rotation transformation. The authors obtain the angular momentum rotation and multi-rotation matrix elements' path integral which evolves with the parameter λ(0→θ,θ the rotation angle), and establish the general method of treating the functional (path) integral as a normal multi-integrals

Use of EyeCam for imaging the anterior chamber angle.

Science.gov (United States)

Perera, Shamira A; Baskaran, Mani; Friedman, David S; Tun, Tin A; Htoon, Hla M; Kumar, Rajesh S; Aung, Tin

2010-06-01

To compare EyeCam (Clarity Medical Systems, Pleasanton, CA) imaging with gonioscopy for detecting angle closure. In this prospective, hospital-based study, subjects underwent gonioscopy by a single observer and EyeCam imaging by a different operator. EyeCam images were graded by two masked observers. The anterior chamber angle in a quadrant was classified as closed if the trabecular meshwork could not be seen. The eye was classified as having angle closure if two or more quadrants were closed. One hundred fifty-two subjects were studied. The mean age was 57.4 years (SD 12.9) and there were 82 (54%) men. Of the 152 eyes, 21 (13.8%) had angle closure. The EyeCam provided clear images of the angles in 98.8% of subjects. The agreement between the EyeCam and gonioscopy for detecting angle closure in the superior, inferior, nasal, and temporal quadrants based on agreement coefficient (AC1) statistics was 0.73, 0.75, 0.76, and 0.72, respectively. EyeCam detected more closed angles than did gonioscopy in all quadrants (P gonioscopy, 21/152 (13.8%) eyes were diagnosed as angle closure compared to 41 (27.0%) of 152 with EyeCam (P gonioscopy for detecting angle closure. However, it detected more closed angles than did gonioscopy in all quadrants.

Variable-flip-angle spin-echo imaging (VFSE)

International Nuclear Information System (INIS)

Kasai, Toshifumi; Sugimura, Kazuro; Kawamitsu, Hideaki; Yasui, Kiyoshi; Ishida, Tetsuya; Tsukamoto, Tetsuji.

1990-01-01

T 2 weighted imaging provides images with high object contrast for pathologic conditions in which the water content of tissues is increased. The authors predicted theoretical analysis of the effects of changing flip angle, and analyzed the effects in MR imaging of both phantoms and humans. Variable flip angle spin echo MR imaging (VFSE) with a 1,000/80 (repetition time msec/echo time msec) can obtain T 2 weighted image when flip angle is smaller than 80 degrees. VFSE with 40 to 60 degrees flip angle have higher contrast than other flip angle images. Signal to noise ratio (S/N) of VFSE are 55% at a 30 degree, 76% at a 45 degree, 92% at a 60 degree respectively as compared with conventional spin echo image (2000/80, flip angle 90 degree). VFSE is applicable to obtain T 2 weighted image reduced imaging time. (author)

Binary-space-partitioned images for resolving image-based visibility.

Science.gov (United States)

Fu, Chi-Wing; Wong, Tien-Tsin; Tong, Wai-Shun; Tang, Chi-Keung; Hanson, Andrew J

2004-01-01

We propose a novel 2D representation for 3D visibility sorting, the Binary-Space-Partitioned Image (BSPI), to accelerate real-time image-based rendering. BSPI is an efficient 2D realization of a 3D BSP tree, which is commonly used in computer graphics for time-critical visibility sorting. Since the overall structure of a BSP tree is encoded in a BSPI, traversing a BSPI is comparable to traversing the corresponding BSP tree. BSPI performs visibility sorting efficiently and accurately in the 2D image space by warping the reference image triangle-by-triangle instead of pixel-by-pixel. Multiple BSPIs can be combined to solve "disocclusion," when an occluded portion of the scene becomes visible at a novel viewpoint. Our method is highly automatic, including a tensor voting preprocessing step that generates candidate image partition lines for BSPIs, filters the noisy input data by rejecting outliers, and interpolates missing information. Our system has been applied to a variety of real data, including stereo, motion, and range images.

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

Energy Technology Data Exchange (ETDEWEB)

Park, Yeonok; Je, Uikyu; Cho, Hyosung, E-mail: hscho1@yonsei.ac.kr; Hong, Daeki; Park, Chulkyu; Cho, Heemoon; Choi, Sungil; Woo, Taeho

2015-03-21

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°) on a circular path set perpendicularly to the axial direction during the image acquisition. This geometry, compared to full-angle (360°) 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 geometry 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°, 90°, 135°, and 180° for a given tomographic angle of 80° 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. - Highlights: • Image reconstruction is done in circular digital tomosynthesis (CDTS). • The designed geometry allows imaging system to be the better image. • An efficient compressed-sensing (CS)-based reconstruction algorithm is performed. • Proposed method can provide superior tomographic quality for the axial view.

Intracranial cerebrospinal fluid spaces imaging using a pulse-triggered three-dimensional turbo spin echo MR sequence with variable flip-angle distribution

International Nuclear Information System (INIS)

Hodel, Jerome; Silvera, Jonathan; Bekaert, Olivier; Decq, Philippe; Rahmouni, Alain; Bastuji-Garin, Sylvie; Vignaud, Alexandre; Petit, Eric; Durning, Bruno

2011-01-01

To assess the three-dimensional turbo spin echo with variable flip-angle distribution magnetic resonance sequence (SPACE: Sampling Perfection with Application optimised Contrast using different flip-angle Evolution) for the imaging of intracranial cerebrospinal fluid (CSF) spaces. We prospectively investigated 18 healthy volunteers and 25 patients, 20 with communicating hydrocephalus (CH), five with non-communicating hydrocephalus (NCH), using the SPACE sequence at 1.5T. Volume rendering views of both intracranial and ventricular CSF were obtained for all patients and volunteers. The subarachnoid CSF distribution was qualitatively evaluated on volume rendering views using a four-point scale. The CSF volumes within total, ventricular and subarachnoid spaces were calculated as well as the ratio between ventricular and subarachnoid CSF volumes. Three different patterns of subarachnoid CSF distribution were observed. In healthy volunteers we found narrowed CSF spaces within the occipital aera. A diffuse narrowing of the subarachnoid CSF spaces was observed in patients with NCH whereas patients with CH exhibited narrowed CSF spaces within the high midline convexity. The ratios between ventricular and subarachnoid CSF volumes were significantly different among the volunteers, patients with CH and patients with NCH. The assessment of CSF spaces volume and distribution may help to characterise hydrocephalus. (orig.)

Intracranial cerebrospinal fluid spaces imaging using a pulse-triggered three-dimensional turbo spin echo MR sequence with variable flip-angle distribution

Energy Technology Data Exchange (ETDEWEB)

Hodel, Jerome [Unite Analyse et Restauration du Mouvement, UMR-CNRS, 8005 LBM ParisTech Ensam, Paris (France); University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Neuroradiology, Creteil (France); Hopital Henri Mondor, Creteil (France); Silvera, Jonathan [University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Neuroradiology, Creteil (France); Bekaert, Olivier; Decq, Philippe [Unite Analyse et Restauration du Mouvement, UMR-CNRS, 8005 LBM ParisTech Ensam, Paris (France); University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Neurosurgery, Creteil (France); Rahmouni, Alain [University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Radiology, Creteil (France); Bastuji-Garin, Sylvie [University Paris Est Creteil (UPEC), Creteil (France); Assistance Publique-Hopitaux de Paris, Paris (France); Hopital Henri Mondor, Department of Public Health, Creteil (France); Vignaud, Alexandre [Siemens Healthcare, Saint Denis (France); Petit, Eric; Durning, Bruno [Laboratoire Images Signaux et Systemes Intelligents, UPEC, Creteil (France)

2011-02-15

To assess the three-dimensional turbo spin echo with variable flip-angle distribution magnetic resonance sequence (SPACE: Sampling Perfection with Application optimised Contrast using different flip-angle Evolution) for the imaging of intracranial cerebrospinal fluid (CSF) spaces. We prospectively investigated 18 healthy volunteers and 25 patients, 20 with communicating hydrocephalus (CH), five with non-communicating hydrocephalus (NCH), using the SPACE sequence at 1.5T. Volume rendering views of both intracranial and ventricular CSF were obtained for all patients and volunteers. The subarachnoid CSF distribution was qualitatively evaluated on volume rendering views using a four-point scale. The CSF volumes within total, ventricular and subarachnoid spaces were calculated as well as the ratio between ventricular and subarachnoid CSF volumes. Three different patterns of subarachnoid CSF distribution were observed. In healthy volunteers we found narrowed CSF spaces within the occipital aera. A diffuse narrowing of the subarachnoid CSF spaces was observed in patients with NCH whereas patients with CH exhibited narrowed CSF spaces within the high midline convexity. The ratios between ventricular and subarachnoid CSF volumes were significantly different among the volunteers, patients with CH and patients with NCH. The assessment of CSF spaces volume and distribution may help to characterise hydrocephalus. (orig.)

Design and implementation of space physics multi-model application integration based on web

Science.gov (United States)

Jiang, Wenping; Zou, Ziming

With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into

Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

Multi-modality medical image fusion has more and more important applications in medical image analysisand understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fusemedical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusionresults when applying different selection rules and obtain optimum combination of fusion parameters.

Cloud-based processing of multi-spectral imaging data

Science.gov (United States)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

MULTI-TEMPORAL AND MULTI-SENSOR IMAGE MATCHING BASED ON LOCAL FREQUENCY INFORMATION

Directory of Open Access Journals (Sweden)

X. Liu

2012-08-01

Full Text Available Image Matching is often one of the first tasks in many Photogrammetry and Remote Sensing applications. This paper presents an efficient approach to automated multi-temporal and multi-sensor image matching based on local frequency information. Two new independent image representations, Local Average Phase (LAP and Local Weighted Amplitude (LWA, are presented to emphasize the common scene information, while suppressing the non-common illumination and sensor-dependent information. In order to get the two representations, local frequency information is firstly obtained from Log-Gabor wavelet transformation, which is similar to that of the human visual system; then the outputs of odd and even symmetric filters are used to construct the LAP and LWA. The LAP and LWA emphasize on the phase and amplitude information respectively. As these two representations are both derivative-free and threshold-free, they are robust to noise and can keep as much of the image details as possible. A new Compositional Similarity Measure (CSM is also presented to combine the LAP and LWA with the same weight for measuring the similarity of multi-temporal and multi-sensor images. The CSM can make the LAP and LWA compensate for each other and can make full use of the amplitude and phase of local frequency information. In many image matching applications, the template is usually selected without consideration of its matching robustness and accuracy. In order to overcome this problem, a local best matching point detection is presented to detect the best matching template. In the detection method, we employ self-similarity analysis to identify the template with the highest matching robustness and accuracy. Experimental results using some real images and simulation images demonstrate that the presented approach is effective for matching image pairs with significant scene and illumination changes and that it has advantages over other state-of-the-art approaches, which include: the

Research on segmentation based on multi-atlas in brain MR image

Science.gov (United States)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

Science.gov (United States)

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

2017-03-03

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

A 2 x 2 imaging MIMO system based on LED Visible Light Communications employing space balanced coding and integrated PIN array reception

DEFF Research Database (Denmark)

Li, Jiehui; Xu, Yinfan; Shi, Jianyang

2016-01-01

In this paper, we proposed a 2 x 2 imaging Multi-Input Multi-Output (MIMO)-Visible Light Communication (VLC) system by employing Space Balanced Coding (SBC) based on two RGB LEDs and integrated PIN array reception. We experimentally demonstrated 1.4-Gbit/s VLC transmission at a distance of 2.5 m...

The development of a specialized processor for a space-based multispectral earth imager

Science.gov (United States)

Khedr, Mostafa E.

2008-10-01

This work was done in the Department of Computer Engineering, Lvov Polytechnic National University, Lvov, Ukraine, as a thesis entitled "Space Imager Computer System for Raw Video Data Processing" [1]. This work describes the synthesis and practical implementation of a specialized computer system for raw data control and processing onboard a satellite MultiSpectral earth imager. This computer system is intended for satellites with resolution in the range of one meter with 12-bit precession. The design is based mostly on general off-the-shelf components such as (FPGAs) plus custom designed software for interfacing with PC and test equipment. The designed system was successfully manufactured and now fully functioning in orbit.

Improved estimation of leaf area index and leaf chlorophyll content of a potato crop using multi-angle spectral data - potential of unmanned aerial vehicle imagery

Science.gov (United States)

Roosjen, Peter P. J.; Brede, Benjamin; Suomalainen, Juha M.; Bartholomeus, Harm M.; Kooistra, Lammert; Clevers, Jan G. P. W.

2018-04-01

In addition to single-angle reflectance data, multi-angular observations can be used as an additional information source for the retrieval of properties of an observed target surface. In this paper, we studied the potential of multi-angular reflectance data for the improvement of leaf area index (LAI) and leaf chlorophyll content (LCC) estimation by numerical inversion of the PROSAIL model. The potential for improvement of LAI and LCC was evaluated for both measured data and simulated data. The measured data was collected on 19 July 2016 by a frame-camera mounted on an unmanned aerial vehicle (UAV) over a potato field, where eight experimental plots of 30 × 30 m were designed with different fertilization levels. Dozens of viewing angles, covering the hemisphere up to around 30° from nadir, were obtained by a large forward and sideways overlap of collected images. Simultaneously to the UAV flight, in situ measurements of LAI and LCC were performed. Inversion of the PROSAIL model was done based on nadir data and based on multi-angular data collected by the UAV. Inversion based on the multi-angular data performed slightly better than inversion based on nadir data, indicated by the decrease in RMSE from 0.70 to 0.65 m2/m2 for the estimation of LAI, and from 17.35 to 17.29 μg/cm2 for the estimation of LCC, when nadir data were used and when multi-angular data were used, respectively. In addition to inversions based on measured data, we simulated several datasets at different multi-angular configurations and compared the accuracy of the inversions of these datasets with the inversion based on data simulated at nadir position. In general, the results based on simulated (synthetic) data indicated that when more viewing angles, more well distributed viewing angles, and viewing angles up to larger zenith angles were available for inversion, the most accurate estimations were obtained. Interestingly, when using spectra simulated at multi-angular sampling configurations as

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

Directory of Open Access Journals (Sweden)

Anthony Hoak

2017-03-01

Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Polarimetric analysis of a CdZnTe spectro-imager under multi-pixel irradiation conditions

Energy Technology Data Exchange (ETDEWEB)

Pinto, M. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Coimbra, Coimbra (Portugal); Curado da Silva, R.M., E-mail: rui.silva@coimbra.lip.pt [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Coimbra, Coimbra (Portugal); Maia, J.M. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Beira-Interior, Covilhã (Portugal); Simões, N. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Physics Department, University of Coimbra, Coimbra (Portugal); Marques, J. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); Centro de Astrofísica, Universidade do Porto, Porto (Portugal); Pereira, L.; Trindade, A.M.F. [LIP-Laboratório de Instrumentação e Física Experimental de Partículas (Portugal); and others

2016-12-21

So far, polarimetry in high-energy astrophysics has been insufficiently explored due to the complexity of the required detection, electronic and signal processing systems. However, its importance is today largely recognized by the astrophysical community, therefore the next generation of high-energy space instruments will certainly provide polarimetric observations, contemporaneously with spectroscopy and imaging. We have been participating in high-energy observatory proposals submitted to ESA Cosmic Vision calls, such as GRI (Gamma-Ray Imager), DUAL and ASTROGAM, where the main instrument was a spectro-imager with polarimetric capabilities. More recently, the H2020 AHEAD project was launched with the objective to promote more coherent and mature future high-energy space mission proposals. In this context of high-energy proposal development, we have tested a CdZnTe detection plane prototype polarimeter under a partially polarized gamma-ray beam generated from an aluminum target irradiated by a {sup 22}Na (511 keV) radioactive source. The polarized beam cross section was 1 cm{sup 2}, allowing the irradiation of a wide multi-pixelated area where all the pixels operate simultaneously as a scatterer and as an absorber. The methods implemented to analyze such multi-pixel irradiation are similar to those required to analyze a spectro-imager polarimeter operating in space, since celestial source photons should irradiate its full pixilated area. Correction methods to mitigate systematic errors inherent to CdZnTe and to the experimental conditions were also implemented. The polarization level (~40%) and the polarization angle (precision of ±5° up to ±9°) obtained under multi-pixel irradiation conditions are presented and compared with simulated data.

Improved space bandwidth product in image upconversion

DEFF Research Database (Denmark)

Dam, Jeppe Seidelin; Pedersen, Christian; Tidemand-Lichtenberg, Peter

2012-01-01

We present a technique increasing the space bandwidth product of a nonlinear image upconversion process used for spectral imaging. The technique exploits the strong dependency of the phase-matching condition in sum frequency generation (SFG) on the angle of propagation of the interacting fields...

Two wide-angle imaging neutral-atom spectrometers (TWINS)

International Nuclear Information System (INIS)

McComas, D.J.; Blake, B.; Burch, J.

1998-01-01

Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) is a revolutionary new mission designed to stereoscopically image the magnetosphere in charge exchange neutral atoms for the first time. The authors propose to fly two identical TWINS instruments as a mission of opportunity on two widely-spaced high-altitude, high-inclination US Government spacecraft. Because the spacecraft are funded independently, TWINS can provide a vast quantity of high priority science observations (as identified in an ongoing new missions concept study and the Sun-Earth Connections Roadmap) at a small fraction of the cost of a dedicated mission. Because stereo observations of the near-Earth space environs will provide a particularly graphic means for visualizing the magnetosphere in action, and because of the dedication and commitment of the investigator team to the principles of carrying space science to the broader audience, TWINS will also be an outstanding tool for public education and outreach

Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Biao Wang

2017-08-01

Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

Evaluation of cardiac function using multi-shot echo planar imaging

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, Tadashi; Tanitame, Nobuko; Hata, Ryoichiro; Hirai, Nobuhiko; Ikeda, Midori; Ono, Chiaki; Fukuoka, Haruhito; Ito, Katsuhide [Hiroshima Univ. (Japan). School of Medicine

1998-01-01

In this study, we performed multi-shot echo planar imaging (8 shot, TR/TE/FL=55 ms/18 ms/60 degrees) and k-space segmented fast gradient echo sequence (8 views per segment, TR/TE/FL=9.9 ms/1.8 ms/30 degrees) to assess cardiac function in healthy volunteers. Transaxial sections of the entire heart were obtained with both sequences in ECG triggered, breath hold, and with a 256 x 128 matrix. Resulting temporal resolution was 55 ms for echo planar imaging, and 71 ms for k-space segmented fast gradient echo sequence, respectively. Ventricular volume and ejection fraction of both ventricles and left ventricular mass obtained with multi-shot echo planar imaging were assessed in comparison with k-space segmented fast gradient echo sequence. Measurements of left ventricular volume, ejection fraction and mass obtained with multi-shot echo planar imaging demonstrated close correlation with those obtained with k-space segmented fast gradient echo sequence. Right ventricular volumes obtained with echo planar imaging were significantly higher than those obtained with k-space segmented fast gradient echo sequence. This tendency is considered to be due to differing contrast between right ventricular myocardium and fat tissue observed with echo planar imaging relative to that observed with fast gradient echo sequence, because fat suppression is always performed in echo planar images. Multi-shot echo planar imaging can be a reliable tool for measurement of cardiac functional parameters, although wall motion analysis of the left ventricle requires higher temporal resolution and a short axial section. (K.H.)

Limited-angle multi-energy CT using joint clustering prior and sparsity regularization

Science.gov (United States)

Zhang, Huayu; Xing, Yuxiang

2016-03-01

In this article, we present an easy-to-implement Multi-energy CT scanning strategy and a corresponding reconstruction method, which facilitate spectral CT imaging by improving the data efficiency the number-of-energy- channel fold without introducing visible limited-angle artifacts caused by reducing projection views. Leveraging the structure coherence at different energies, we first pre-reconstruct a prior structure information image using projection data from all energy channels. Then, we perform a k-means clustering on the prior image to generate a sparse dictionary representation for the image, which severs as a structure information constraint. We com- bine this constraint with conventional compressed sensing method and proposed a new model which we referred as Joint Clustering Prior and Sparsity Regularization (CPSR). CPSR is a convex problem and we solve it by Alternating Direction Method of Multipliers (ADMM). We verify our CPSR reconstruction method with a numerical simulation experiment. A dental phantom with complicate structures of teeth and soft tissues is used. X-ray beams from three spectra of different peak energies (120kVp, 90kVp, 60kVp) irradiate the phantom to form tri-energy projections. Projection data covering only 75◦ from each energy spectrum are collected for reconstruction. Independent reconstruction for each energy will cause severe limited-angle artifacts even with the help of compressed sensing approaches. Our CPSR provides us with images free of the limited-angle artifact. All edge details are well preserved in our experimental study.

Multi-disciplinary techniques for understanding time-varying space-based imagery

Science.gov (United States)

Casasent, D.; Sanderson, A.; Kanade, T.

1984-06-01

A multidisciplinary program for space-based image processing is reported. This project combines optical and digital processing techniques and pattern recognition, image understanding and artificial intelligence methodologies. Time change image processing was recognized as the key issue to be addressed. Three time change scenarios were defined based on the frame rate of the data change. This report details the recent research on: various statistical and deterministic image features, recognition of sub-pixel targets in time varying imagery, and 3-D object modeling and recognition.

Evaluation of the resolving power of different angles in MPR images of 16DAS-MDCT

International Nuclear Information System (INIS)

Kimura, Mikio; Usui, Junshi; Nozawa, Takeo

2007-01-01

In this study, we evaluated the resolving power of three-dimensional (3D) multiplanar reformation (MPR) images with various angles by using 16 data acquisition system multi detector row computed tomography (16DAS-MDCT). We reconstructed the MPR images using data with a 0.75 mm slice thickness of the axial image in this examination. To evaluate resolving power, we used an original new phantom (RC phantom) that can be positioned at any slice angle in MPR images. We measured the modulation transfer function (MTF) by using the methods of measuring pre-sampling MTF, and used Fourier transform of image data of the square wave chart. The scan condition and image reconstruction condition that were adopted in this study correspond to the condition that we use for three-dimensional computed tomographic angiography(3D-CTA) examination of the head in our hospital. The MTF of MPR images showed minimum values at slice angles in parallel with the axial slice, and showed maximum values at the sagittal slice and coronal slice angles that are parallel to the Z-axis. With an oblique MPR image, MTF did not change with angle changes in the oblique sagittal slice plane, but in the oblique coronal slice plane, MTF increased as the tilt angle increased from the axial plane to the Z plane. As a result, we could evaluate the resolving power of a head 3D image by measuring the MTF of the axial image and sagittal image or the coronal image. (author)

[Evaluation of the resolving power of different angles in MPR images of 16DAS-MDCT].

Science.gov (United States)

Kimura, Mikio; Usui, Junshi; Nozawa, Takeo

2007-03-20

In this study, we evaluated the resolving power of three-dimensional (3D) multiplanar reformation (MPR) images with various angles by using 16 data acquisition system multi detector row computed tomography (16DAS-MDCT) . We reconstructed the MPR images using data with a 0.75 mm slice thickness of the axial image in this examination. To evaluate resolving power, we used an original new phantom (RC phantom) that can be positioned at any slice angle in MPR images. We measured the modulation transfer function (MTF) by using the methods of measuring pre-sampling MTF, and used Fourier transform of image data of the square wave chart. The scan condition and image reconstruction condition that were adopted in this study correspond to the condition that we use for three-dimensional computed tomographic angiography (3D-CTA) examination of the head in our hospital. The MTF of MPR images showed minimum values at slice angles in parallel with the axial slice, and showed maximum values at the sagittal slice and coronal slice angles that are parallel to the Z-axis. With an oblique MPR image, MTF did not change with angle changes in the oblique sagittal slice plane, but in the oblique coronal slice plane, MTF increased as the tilt angle increased from the axial plane to the Z plane. As a result, we could evaluate the resolving power of a head 3D image by measuring the MTF of the axial image and sagittal image or the coronal image.

Winter precipitation particle size distribution measurement by Multi-Angle Snowflake Camera

Science.gov (United States)

Huang, Gwo-Jong; Kleinkort, Cameron; Bringi, V. N.; Notaroš, Branislav M.

2017-12-01

From the radar meteorology viewpoint, the most important properties for quantitative precipitation estimation of winter events are 3D shape, size, and mass of precipitation particles, as well as the particle size distribution (PSD). In order to measure these properties precisely, optical instruments may be the best choice. The Multi-Angle Snowflake Camera (MASC) is a relatively new instrument equipped with three high-resolution cameras to capture the winter precipitation particle images from three non-parallel angles, in addition to measuring the particle fall speed using two pairs of infrared motion sensors. However, the results from the MASC so far are usually presented as monthly or seasonally, and particle sizes are given as histograms, no previous studies have used the MASC for a single storm study, and no researchers use MASC to measure the PSD. We propose the methodology for obtaining the winter precipitation PSD measured by the MASC, and present and discuss the development, implementation, and application of the new technique for PSD computation based on MASC images. Overall, this is the first study of the MASC-based PSD. We present PSD MASC experiments and results for segments of two snow events to demonstrate the performance of our PSD algorithm. The results show that the self-consistency of the MASC measured single-camera PSDs is good. To cross-validate PSD measurements, we compare MASC mean PSD (averaged over three cameras) with the collocated 2D Video Disdrometer, and observe good agreements of the two sets of results.

EFFECTS OF X-RAY BEAM ANGLE AND GEOMETRIC DISTORTION ON WIDTH OF EQUINE THORACOLUMBAR INTERSPINOUS SPACES USING RADIOGRAPHY AND COMPUTED TOMOGRAPHY

DEFF Research Database (Denmark)

Djernaes, Julie D.; Nielsen, Jon V.; Berg, Lise C.

2017-01-01

The widths of spaces between the thoracolumbar processi spinosi (interspinous spaces) are frequently assessed using radiography in sports horses; however effects of varying X-ray beam angles and geometric distortion have not been previously described. The aim of this prospective, observational...... study was to determine whether X-ray beam angle has an effect on apparent widths of interspinous spaces. Thoracolumbar spine specimens were collected from six equine cadavers and left-right lateral radiographs and sagittal and dorsal reconstructed computed tomographic (CT) images were acquired...... measurements. Effect of geometric distortion was evaluated by comparing the interspinous space in radiographs with sagittal and dorsal reconstructed CT images. A total of 49 interspinous spaces were sampled, yielding 274 measurements. X-ray beam angle significantly affected measured width of interspinous...

EAGLE 2006 – Multi-purpose, multi-angle and multi-sensor in-situ and airborne campaigns over grassland and forest

Directory of Open Access Journals (Sweden)

Z. Su

2009-06-01

Full Text Available EAGLE2006 – an intensive field campaign for the advances in land surface hydrometeorological processes – was carried out in the Netherlands from 8th to 18th June 2006, involving 16 institutions with in total 67 people from 16 different countries. In addition to the acquisition of multi-angle and multi-sensor satellite data, several airborne instruments – an optical imaging sensor, an imaging microwave radiometer, and a flux airplane – were deployed and extensive ground measurements were conducted over one grassland site at Cabauw and two forest sites at Loobos and Speulderbos in the central part of the Netherlands. The generated data set is both unique and urgently needed for the development and validation of models and inversion algorithms for quantitative land surface parameter estimation and land surface hydrometeorological process studies. EAGLE2006 was led by the Department of Water Resources of the International Institute for Geo-Information Science and Earth Observation (ITC and originated from the combination of a number of initiatives supported by different funding agencies. The objectives of the EAGLE2006 campaign were closely related to the objectives of other European Space Agency (ESA campaign activities (SPARC2004, SEN2FLEX2005 and especially AGRISAR2006. However, one important objective of the EAGLE2006 campaign is to build up a data base for the investigation and validation of the retrieval of bio-geophysical parameters, obtained at different radar frequencies (X-, C- and L-Band and at hyperspectral optical and thermal bands acquired simultaneously over contrasting vegetated fields (forest and grassland. As such, all activities were related to algorithm development for future satellite missions such as the Sentinels and for validation of retrievals of land surface parameters with optical and thermal and microwave sensors onboard current and future satellite missions. This contribution describes the campaign objectives and

Anthropometric body measurements based on multi-view stereo image reconstruction.

Science.gov (United States)

Li, Zhaoxin; Jia, Wenyan; Mao, Zhi-Hong; Li, Jie; Chen, Hsin-Chen; Zuo, Wangmeng; Wang, Kuanquan; Sun, Mingui

2013-01-01

Anthropometric measurements, such as the circumferences of the hip, arm, leg and waist, waist-to-hip ratio, and body mass index, are of high significance in obesity and fitness evaluation. In this paper, we present a home based imaging system capable of conducting anthropometric measurements. Body images are acquired at different angles using a home camera and a simple rotating disk. Advanced image processing algorithms are utilized for 3D body surface reconstruction. A coarse body shape model is first established from segmented body silhouettes. Then, this model is refined through an inter-image consistency maximization process based on an energy function. Our experimental results using both a mannequin surrogate and a real human body validate the feasibility of the proposed system.

Multi-angle polarimeter inter-comparison: the PODEX and ACEPOL field campaigns

Science.gov (United States)

Knobelspiesse, K. D.; Tan, Q.; Redemann, J.; Cairns, B.; Diner, D. J.; Ferrare, R. A.; van Harten, G.; Hasekamp, O. P.; Kalashnikova, O. V.; Martins, J. V.; Yorks, J. E.; Seidel, F. C.

2017-12-01

A multi-angle polarimeter has been proposed for the NASA Aerosol-Cloud-Ecosystem (ACE) mission, recommended by the National Research Council's Decadal Survey. Such instruments are uncommon in orbit, and there is a great diversity of prototype instrument characteristics. For that reason, NASA funded two field campaigns where airborne polarimeter prototypes were deployed on the high altitude ER-2 aircraft. The first field campaign, POlarimeter DEfinition EXperiment (PODEX), was carried out in southern California in early 2013. Three polarimeters participated: the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), the Passive Aerosol and Cloud Suite (PACS) and the Research Scanning Polarimeter (RSP). PACS, on its first deployment, suffered detector problems, while AirMSPI and RSP performed within expectations. Initial comparisons of AirMSPI and RSP observations found Degree of Linear Polarization (DoLP) biases. Following corrections to both instrument's calibration and/or geolocation techniques, these issues have improved. We will present the details of this comparison. The recent ACEPOL mission returned to southern California in October-November with a larger compliment of multi-angle polarimeters. This included AirMSPI and RSP, like in PODEX. Additional polarimetric instruments included AirHARP (Airborne HyperAngular Rainbow Polarimeter, a successor to PACS) and SPEX Airborne (SPectropolarimeter for Planetary Exploration). Two Lidars were also deployed: The High Spectral Resolution Lidar -2 (HSRL-2) and the Cloud Physics Lidar (CPL). While data processing is still underway, we will describe the objectives of this campaign and give a preview of what to expect in subsequent analysis.

Image reconstruction in k-space from MR data encoded with ambiguous gradient fields.

Science.gov (United States)

Schultz, Gerrit; Gallichan, Daniel; Weber, Hans; Witschey, Walter R T; Honal, Matthias; Hennig, Jürgen; Zaitsev, Maxim

2015-02-01

In this work, the limits of image reconstruction in k-space are explored when non-bijective gradient fields are used for spatial encoding. The image space analogy between parallel imaging and imaging with non-bijective encoding fields is partially broken in k-space. As a consequence, it is hypothesized and proven that ambiguities can only be resolved partially in k-space, and not completely as is the case in image space. Image-space and k-space based reconstruction algorithms for multi-channel radiofrequency data acquisitions are programmed and tested using numerical simulations as well as in vivo measurement data. The hypothesis is verified based on an analysis of reconstructed images. It is found that non-bijective gradient fields have the effect that densely sampled autocalibration data, used for k-space reconstruction, provide less information than a separate scan of the receiver coil sensitivity maps, used for image space reconstruction. Consequently, in k-space only the undersampling artifact can be unfolded, whereas in image space, it is also possible to resolve aliasing that is caused by the non-bijectivity of the gradient fields. For standard imaging, reconstruction in image space and in k-space is nearly equivalent, whereas there is a fundamental difference with practical consequences for the selection of image reconstruction algorithms when non-bijective encoding fields are involved. © 2014 Wiley Periodicals, Inc.

Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

Science.gov (United States)

Fuerst, Bernhard; Tateno, Keisuke; Johnson, Alex; Fotouhi, Javad; Osgood, Greg; Tombari, Federico; Navab, Nassir

2017-01-01

Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red–green–blue–depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion. PMID:29184659

Determining Plane-Sweep Sampling Points in Image Space Using the Cross-Ratio for Image-Based Depth Estimation

Science.gov (United States)

Ruf, B.; Erdnuess, B.; Weinmann, M.

2017-08-01

With the emergence of small consumer Unmanned Aerial Vehicles (UAVs), the importance and interest of image-based depth estimation and model generation from aerial images has greatly increased in the photogrammetric society. In our work, we focus on algorithms that allow an online image-based dense depth estimation from video sequences, which enables the direct and live structural analysis of the depicted scene. Therefore, we use a multi-view plane-sweep algorithm with a semi-global matching (SGM) optimization which is parallelized for general purpose computation on a GPU (GPGPU), reaching sufficient performance to keep up with the key-frames of input sequences. One important aspect to reach good performance is the way to sample the scene space, creating plane hypotheses. A small step size between consecutive planes, which is needed to reconstruct details in the near vicinity of the camera may lead to ambiguities in distant regions, due to the perspective projection of the camera. Furthermore, an equidistant sampling with a small step size produces a large number of plane hypotheses, leading to high computational effort. To overcome these problems, we present a novel methodology to directly determine the sampling points of plane-sweep algorithms in image space. The use of the perspective invariant cross-ratio allows us to derive the location of the sampling planes directly from the image data. With this, we efficiently sample the scene space, achieving higher sampling density in areas which are close to the camera and a lower density in distant regions. We evaluate our approach on a synthetic benchmark dataset for quantitative evaluation and on a real-image dataset consisting of aerial imagery. The experiments reveal that an inverse sampling achieves equal and better results than a linear sampling, with less sampling points and thus less runtime. Our algorithm allows an online computation of depth maps for subsequences of five frames, provided that the relative

DETERMINING PLANE-SWEEP SAMPLING POINTS IN IMAGE SPACE USING THE CROSS-RATIO FOR IMAGE-BASED DEPTH ESTIMATION

Directory of Open Access Journals (Sweden)

B. Ruf

2017-08-01

Full Text Available With the emergence of small consumer Unmanned Aerial Vehicles (UAVs, the importance and interest of image-based depth estimation and model generation from aerial images has greatly increased in the photogrammetric society. In our work, we focus on algorithms that allow an online image-based dense depth estimation from video sequences, which enables the direct and live structural analysis of the depicted scene. Therefore, we use a multi-view plane-sweep algorithm with a semi-global matching (SGM optimization which is parallelized for general purpose computation on a GPU (GPGPU, reaching sufficient performance to keep up with the key-frames of input sequences. One important aspect to reach good performance is the way to sample the scene space, creating plane hypotheses. A small step size between consecutive planes, which is needed to reconstruct details in the near vicinity of the camera may lead to ambiguities in distant regions, due to the perspective projection of the camera. Furthermore, an equidistant sampling with a small step size produces a large number of plane hypotheses, leading to high computational effort. To overcome these problems, we present a novel methodology to directly determine the sampling points of plane-sweep algorithms in image space. The use of the perspective invariant cross-ratio allows us to derive the location of the sampling planes directly from the image data. With this, we efficiently sample the scene space, achieving higher sampling density in areas which are close to the camera and a lower density in distant regions. We evaluate our approach on a synthetic benchmark dataset for quantitative evaluation and on a real-image dataset consisting of aerial imagery. The experiments reveal that an inverse sampling achieves equal and better results than a linear sampling, with less sampling points and thus less runtime. Our algorithm allows an online computation of depth maps for subsequences of five frames, provided that

An improved feature extraction algorithm based on KAZE for multi-spectral image

Science.gov (United States)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Characterization of Angle Dependent Color Travel of Printed Multi-Color Effect Pigment on Different Color Substrates

Directory of Open Access Journals (Sweden)

Mirica Karlovits

2015-03-01

Full Text Available Color-travel pigments, which exhibit much more extensive color change as well provide angle-dependent optical effect can be used in many industrial products. In present paper the multi-color effect pigment printed on three different foils with different background color (black, silver and transparent was investigated. The pigment was based on synthetically produced transparent silicon dioxide platelets coated with titanium dioxide. CIEL*a*b* values and reflection of prints were measured by multi-angle spectrophotometer at constant illumination at an angle of 45º and different viewing angles (-15º, 15°, 25º, 45º, 75º and 110º were used. The measurements of printed multi-color pigment showed that CIEL*a*b* color coordinates varied to great extents, depending on detection angles as well on color of the printing substrate. The study revealed that pigmnet printed on black background obtained significant change in color. The study has also shown that when viewing angle increases, the reflection curves decreases.

Development of an Operational System for the Retrieval of Aerosol and Land Surface Properties from the Terra Multi-Angle Imaging SpectroRadiometer

Science.gov (United States)

Crean, Kathleen A.

2003-01-01

An operational system to retrieve atmospheric aerosol and land surface properties using data from the Multi-angle Imaging SpectroRadiometer (MISR) instrument, currently flying onboard NASA's Terra spacecraft, has been deployed. The system is in full operation, with new data products generated daily and distributed to science users worldwide. This paper describes the evolution of the system, from initial requirements definition and prototyping through design, implementation, testing, operational deployment, checkout and maintenance activities. The current status of the system and future plans for enhancement are described. Major challenges encountered during implementation are detailed.

A study of images of Projective Angles of pulmonary veins

Energy Technology Data Exchange (ETDEWEB)

Wang Jue [Beijing Anzhen Hospital, Beijing (China); Zhaoqi, Zhang [Beijing Anzhen Hospital, Beijing (China)], E-mail: zhaoqi5000@vip.sohu.com; Yu Wei; Miao Cuilian; Yan Zixu; Zhao Yike [Beijing Anzhen Hospital, Beijing (China)

2009-09-15

Aims: In images of magnetic resonance and computed tomography (CT) there are visible angles between pulmonary veins and the coronary, transversal or sagittal section of body. In this study these angles are measured and defined as Projective Angles of pulmonary veins. Several possible influential factors and characters of distribution are studied and analyzed for a better understanding of this imaging anatomic character of pulmonary veins. And it could be the anatomic base of adjusting correctly the angle of the central X-ray of the angiography of pulmonary veins undergoing the catheter ablation of atrial fibrillation (AF). Method: Images of contrast enhanced magnetic resonance angiography (CEMRA) and contrast enhanced computer tomography (CECT) of the left atrium and pulmonary veins of 137 health objects and patients with atrial fibrillation (AF) are processed with the technique of post-processing, and Projective Angles to the coronary and transversal sections are measured and analyzed statistically. Result: Project Angles of pulmonary veins are one of real and steady imaging anatomic characteristics of pulmonary veins. The statistical distribution of variables is relatively concentrated, with a fairly good representation of average value. It is possible to improve the angle of the central X-ray according to the average value in the selective angiography of pulmonary veins undergoing the catheter ablation of AF.

Multi-shelled q-ball imaging. Moment-based orientation distribution function

International Nuclear Information System (INIS)

Umezawa, Eizou; Yamaguchi, Kojiro; Yoshikawa, Mayo; Ohno, Kana; Yoshikawa, Emi

2010-01-01

q-ball imaging (QBI) reconstructs the orientation distribution function (ODF) that describes the probability for a spin to diffuse in a given direction, and it is capable of identifying intravoxel multiple fiber orientations. The local maxima of ODF are assumed to indicate fiber orientations, but there is a mismatch between the orientation of a fiber crossing and the local maxima. We propose a novel method, multi-shelled QBI (MS-QBI), that gives a new ODF based on the moment of the probability density function of diffusion displacement. We test the accuracy of the fiber orientation indicated by the new ODF and test fiber tracking using the new ODF. We performed tests using numerical simulation. To test the accuracy of fiber orientation, we assumed that 2 fibers cross and evaluated the deviation of the measured crossing angle from the actual angle. To test the fiber tracking, we used a numerical phantom of the cerebral hemisphere containing the corpus callosum, projection fibers, and superior longitudinal fasciculus. In the tests, we compared the results between MS-QBI and conventional QBI under the condition of approximately equal total numbers of diffusion signal samplings between the 2 methods and chose the interpolation parameter such that the stabilities of the results of the angular deviation for the 2 methods were the same. The absolute value of the mean angular deviation was smaller in MS-QBI than in conventional QBI. Using the moment-based ODF improved the accuracy of fiber pathways in fiber tracking but maintained the stability of the results. MS-QBI can more accurately identify intravoxel multiple fiber orientations than can QBI, without increasing sampling number. The high accuracy of MS-QBI will contribute to the improved tractography. (author)

Adjoint Methods for Adjusting Three-Dimensional Atmosphere and Surface Properties to Fit Multi-Angle Multi-Pixel Polarimetric Measurements

Science.gov (United States)

Martin, William G.; Cairns, Brian; Bal, Guillaume

2014-01-01

This paper derives an efficient procedure for using the three-dimensional (3D) vector radiative transfer equation (VRTE) to adjust atmosphere and surface properties and improve their fit with multi-angle/multi-pixel radiometric and polarimetric measurements of scattered sunlight. The proposed adjoint method uses the 3D VRTE to compute the measurement misfit function and the adjoint 3D VRTE to compute its gradient with respect to all unknown parameters. In the remote sensing problems of interest, the scalar-valued misfit function quantifies agreement with data as a function of atmosphere and surface properties, and its gradient guides the search through this parameter space. Remote sensing of the atmosphere and surface in a three-dimensional region may require thousands of unknown parameters and millions of data points. Many approaches would require calls to the 3D VRTE solver in proportion to the number of unknown parameters or measurements. To avoid this issue of scale, we focus on computing the gradient of the misfit function as an alternative to the Jacobian of the measurement operator. The resulting adjoint method provides a way to adjust 3D atmosphere and surface properties with only two calls to the 3D VRTE solver for each spectral channel, regardless of the number of retrieval parameters, measurement view angles or pixels. This gives a procedure for adjusting atmosphere and surface parameters that will scale to the large problems of 3D remote sensing. For certain types of multi-angle/multi-pixel polarimetric measurements, this encourages the development of a new class of three-dimensional retrieval algorithms with more flexible parametrizations of spatial heterogeneity, less reliance on data screening procedures, and improved coverage in terms of the resolved physical processes in the Earth?s atmosphere.

Design of a space-based infrared imaging interferometer

Science.gov (United States)

Hart, Michael; Hope, Douglas; Romeo, Robert

2017-07-01

Present space-based optical imaging sensors are expensive. Launch costs are dictated by weight and size, and system design must take into account the low fault tolerance of a system that cannot be readily accessed once deployed. We describe the design and first prototype of the space-based infrared imaging interferometer (SIRII) that aims to mitigate several aspects of the cost challenge. SIRII is a six-element Fizeau interferometer intended to operate in the short-wave and midwave IR spectral regions over a 6×6 mrad field of view. The volume is smaller by a factor of three than a filled-aperture telescope with equivalent resolving power. The structure and primary optics are fabricated from light-weight space-qualified carbon fiber reinforced polymer; they are easy to replicate and inexpensive. The design is intended to permit one-time alignment during assembly, with no need for further adjustment once on orbit. A three-element prototype of the SIRII imager has been constructed with a unit telescope primary mirror diameter of 165 mm and edge-to-edge baseline of 540 mm. The optics, structure, and interferometric signal processing principles draw on experience developed in ground-based astronomical applications designed to yield the highest sensitivity and resolution with cost-effective optical solutions. The initial motivation for the development of SIRII was the long-term collection of technical intelligence from geosynchronous orbit, but the scalable nature of the design will likely make it suitable for a range of IR imaging scenarios.

Multi-technology Integration Based on Low-contrast Microscopic Image Enhancement

Directory of Open Access Journals (Sweden)

Haoge Ma

2014-01-01

Full Text Available Microscopic image enhancement is an important issue of image processing technique, which is used to improve the visual quality of image. This paper describes a novel multi resolution image segmentation algorithm for low DOF images. The algorithm is designed to separate a sharply focused object of interest from other foreground or background objects. The algorithm is fully automatic in that all parameters are image in dependent. A multiscale-approach based on high frequency wavelet coefficients and their statistics is used to perform context dependent classification of individual blocks of the image. Compared with the state of the art algorithms, this new algorithm provides better accuracy at higher speed.

Learning-based compressed sensing for infrared image super resolution

Science.gov (United States)

Zhao, Yao; Sui, Xiubao; Chen, Qian; Wu, Shaochi

2016-05-01

This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.

Color Image Evaluation for Small Space Based on FA and GEP

Directory of Open Access Journals (Sweden)

Li Deng

2014-01-01

Full Text Available Aiming at the problem that color image is difficult to quantify, this paper proposes an evaluation method of color image for small space based on factor analysis (FA and gene expression programming (GEP and constructs a correlation model between color image factors and comprehensive color image. The basic color samples of small space and color images are evaluated by semantic differential method (SD method, color image factors are selected via dimension reduction in FA, factor score function is established, and by combining the entropy weight method to determine each factor weights then the comprehensive color image score is calculated finally. The best fitting function between color image factors and comprehensive color image is obtained by GEP algorithm, which can predict the users’ color image values. A color image evaluation system for small space is developed based on this model. The color evaluation of a control room on AC frequency conversion rig is taken as an example, verifying the effectiveness of the proposed method. It also can assist the designers in other color designs and provide a fast evaluation tool for testing users’ color image.

A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

Directory of Open Access Journals (Sweden)

T. Kavzoglu

2016-06-01

Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

Wide-angle imaging LIDAR (WAIL): a ground-based instrument for monitoring the thickness and density of optically thick clouds

International Nuclear Information System (INIS)

Love, Steven P.; Davis, A.B.; Rohde, C.A.; Ho, Cheng

2001-01-01

Traditional lidar provides little information on dense clouds beyond the range to their base (ceilometry), due to their extreme opacity. At most optical wavelengths, however, laser photons are not absorbed but merely scattered out of the beam, and thus eventually escape the cloud via multiple scattering, producing distinctive extended space- and time-dependent patterns which are, in essence, the cloud's radiative Green functions. These Green functions, essentially 'movies' of the time evolution of the spatial distribution of escaping light, are the primary data products of a new type of lidar: Wide Angle Imaging Lidar (WAIL). WAIL data can be used to infer both optical depth and physical thickness of clouds, and hence the cloud liquid water content. The instrumental challenge is to accommodate a radiance field varying over many orders of magnitude and changing over widely varying time-scales. Our implementation uses a high-speed microchannel plate/crossed delay line imaging detector system with a 60-degree full-angle field of view, and a 532 nm doubled Nd:YAG laser. Nighttime field experiments testing various solutions to this problem show excellent agreement with diffusion theory, and retrievals yield plausible values for the optical and geometrical parameters of the observed cloud decks.

Multimodal image registration based on binary gradient angle descriptor.

Science.gov (United States)

Jiang, Dongsheng; Shi, Yonghong; Yao, Demin; Fan, Yifeng; Wang, Manning; Song, Zhijian

2017-12-01

Multimodal image registration plays an important role in image-guided interventions/therapy and atlas building, and it is still a challenging task due to the complex intensity variations in different modalities. The paper addresses the problem and proposes a simple, compact, fast and generally applicable modality-independent binary gradient angle descriptor (BGA) based on the rationale of gradient orientation alignment. The BGA can be easily calculated at each voxel by coding the quadrant in which a local gradient vector falls, and it has an extremely low computational complexity, requiring only three convolutions, two multiplication operations and two comparison operations. Meanwhile, the binarized encoding of the gradient orientation makes the BGA more resistant to image degradations compared with conventional gradient orientation methods. The BGA can extract similar feature descriptors for different modalities and enable the use of simple similarity measures, which makes it applicable within a wide range of optimization frameworks. The results for pairwise multimodal and monomodal registrations between various images (T1, T2, PD, T1c, Flair) consistently show that the BGA significantly outperforms localized mutual information. The experimental results also confirm that the BGA can be a reliable alternative to the sum of absolute difference in monomodal image registration. The BGA can also achieve an accuracy of [Formula: see text], similar to that of the SSC, for the deformable registration of inhale and exhale CT scans. Specifically, for the highly challenging deformable registration of preoperative MRI and 3D intraoperative ultrasound images, the BGA achieves a similar registration accuracy of [Formula: see text] compared with state-of-the-art approaches, with a computation time of 18.3 s per case. The BGA improves the registration performance in terms of both accuracy and time efficiency. With further acceleration, the framework has the potential for

Automatic Cobb Angle Determination From Radiographic Images

NARCIS (Netherlands)

Sardjono, Tri Arief; Wilkinson, Michael H. F.; Veldhuizen, Albert G.; van Ooijen, Peter M. A.; Purnama, Ketut E.; Verkerke, Gijsbertus J.

2013-01-01

Study Design. Automatic measurement of Cobb angle in patients with scoliosis. Objective. To test the accuracy of an automatic Cobb angle determination method from frontal radiographical images. Summary of Background Data. Thirty-six frontal radiographical images of patients with scoliosis. Methods.

Anatomical based registration of multi-sector x-ray images for panorama reconstruction

Science.gov (United States)

Ben-Zikri, Yehuda Kfir; Mendez, Stacy; Linte, Cristian A.

2017-03-01

Accurate measurement of long limb alignment is an essential stage of the pre-operative planning of realignment surgery. This alignment is quantified according to the hip-knee-ankle (HKA) angle of the mechanical axis of the lower extremity and is measured based on a full-length weight-bearing X-ray or standard computed radiography (CR) image of the patient in standing position. Due to the limited field-of-view of the traditionally employed digital X-ray imaging systems, several sector images are required to capture the posture of a standing individual. These sector images need to then be "stitched" together to reconstruct the standing posture. To eliminate user-induced variability and time constraints associated with the traditional manual "stitching" protocol, we have created an image processing application to automate the stitching process, when there are no reliable external markers available in the images, by only relying on the most reliable anatomical content of the image. The application starts with a rough segmentation of the tibia and the sector images are then registered by evaluating the DICE coefficient between the edges of these corresponding bones along the medial edge. The identified translations are then used to register the original sector images into the standing panorama image. To test the robustness of our method, we randomly selected 40 datasets from a variant database consisting of nearly 100 patient X-ray images acquired for patient screening as part of a multi-site clinical trial. The resulting horizontal and vertical translation values from the automated registration were compared to the homologous translations recorded during the manual panorama generation conducted by a knowledgeable X-ray imaging technician. The mean and standard deviation of the differences for the horizontal translation parameters was -0:27+/-1:14 mm and 0:31+/-1:86 mm for the left and right tibia, respectively. The vertical translation differences for the left and

A multi-function low solide angle system

International Nuclear Information System (INIS)

Yan Sujuan; Yao Linong

2001-01-01

A multi-function low solid angle system for direct and indirect measurement of radioactivity or emission rate of most α, β and EC emitting nuclides are described in this paper. The measurement result of 241 Am and 90 Sr- 90 Y are given

Improving parallel imaging by jointly reconstructing multi-contrast data.

Science.gov (United States)

Bilgic, Berkin; Kim, Tae Hyung; Liao, Congyu; Manhard, Mary Kate; Wald, Lawrence L; Haldar, Justin P; Setsompop, Kawin

2018-08-01

To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition. We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction. We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error. JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Magnetic resonance imaging of lumbar spine. Comparison of multiple spin echo and low flip angle gradient echo imaging

Energy Technology Data Exchange (ETDEWEB)

Murakami, Takamichi; Fujita, Norihiko; Harada, Koushi; Kozuka, Takahiro (Osaka Univ. (Japan). Faculty of Medicine)

1989-07-01

Sixteen patients including 13 cases with disk herniation and 3 cases with spondylosis of lumbar spine were examined on a resistive MRI system operating at 0.1 T. All lesions were studied with both multiple spin echo (MSE) and low flip angle gradient echo (LF) techniques to evaluate which technique is more effective in detecting the disk degeneration and the indentation on subarachnoid space. MSE images were obtained with repetition time (TR) of 1100-1500 ms or cardiac gating, an echo time (TE) of 30, 60, 90, 120, 150, and 180 ms symmetrical 6 echoes, and total acquisition time of more than 281 sec. LF images were obtained with TR of 500, 250, and 100 ms, TE of 18 ms, a flip angle of 30 degree, and total acquisition time of 128 sec. Eleven lesions of spinal disk degeneration and 12 of indentation on subarachnoid space were detected with LF. On the other hand, 26 lesions of spinal disk degeneration and 38 of indentation on subarachnoid space were detected with MSE. Although the parameters of LF employed in this study were relatively effective to emphasize T2{sup *}-based contrast, the ability of LF in detection of spinal disk degeneration and indentation on subarachnoid space is less than that of MSE. Signal contrast to noise ratios for normal disk and degenerative disk, epidural-fat and disk herniated material, CSF and disk herniated material, and epidural-fat and CSF were less than 4 with LF, but more than 4 with MSE. This difference of contrast to noise ratio between MSE and LF was one of the main causes of the difference of the detection rate of spinal disk degeneration and indentation on subarachnoid space. (author).

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

Directory of Open Access Journals (Sweden)

Xiao Ling

2016-08-01

Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

Naveed ur Rehman

2015-05-01

Full Text Available A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA, discrete wavelet transform (DWT and non-subsampled contourlet transform (NCT. A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Size effects in van der Waals clusters studied by spin and angle-resolved electron spectroscopy and multi-coincidence ion imaging

International Nuclear Information System (INIS)

Rolles, D; Pesic, Z D; Zhang, H; Bilodeau, R C; Bozek, J D; Berrah, N

2007-01-01

We have studied the valence and inner-shell photoionization of free rare-gas clusters by means of angle and spin resolved photoelectron spectroscopy and momentum resolving electron-multi-ion coincidence spectroscopy. The electron measurements probe the evolution of the photoelectron angular distribution and spin polarization parameters as a function of photon energy and cluster size, and reveal a strong cluster size dependence of the photoelectron angular distributions in certain photon energy regions. In contrast, the spin polarization parameter of the cluster photoelectrons is found to be very close to the atomic value for all covered photon energies and cluster sizes. The ion imaging measurements, which probe the fragmentation dynamics of multiply charged van der Waals clusters, also exhibit a pronounced cluster size dependence

Image de-noising based on mathematical morphology and multi-objective particle swarm optimization

Science.gov (United States)

Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng

2017-07-01

To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

Science.gov (United States)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Extended feature-fusion guidelines to improve image-based multi-modal biometrics

CSIR Research Space (South Africa)

Brown, Dane

2016-09-01

Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

Automated pathologies detection in retina digital images based on complex continuous wavelet transform phase angles.

Science.gov (United States)

Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel

2014-10-01

An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.

Multi-Angle Snowflake Camera Instrument Handbook

Energy Technology Data Exchange (ETDEWEB)

Stuefer, Martin [Univ. of Alaska, Fairbanks, AK (United States); Bailey, J. [Univ. of Alaska, Fairbanks, AK (United States)

2016-07-01

The Multi-Angle Snowflake Camera (MASC) takes 9- to 37-micron resolution stereographic photographs of free-falling hydrometers from three angles, while simultaneously measuring their fall speed. Information about hydrometeor size, shape orientation, and aspect ratio is derived from MASC photographs. The instrument consists of three commercial cameras separated by angles of 36º. Each camera field of view is aligned to have a common single focus point about 10 cm distant from the cameras. Two near-infrared emitter pairs are aligned with the camera’s field of view within a 10-angular ring and detect hydrometeor passage, with the lower emitters configured to trigger the MASC cameras. The sensitive IR motion sensors are designed to filter out slow variations in ambient light. Fall speed is derived from successive triggers along the fall path. The camera exposure times are extremely short, in the range of 1/25,000th of a second, enabling the MASC to capture snowflake sizes ranging from 30 micrometers to 3 cm.

Multiplier-free DCT approximations for RF multi-beam digital aperture-array space imaging and directional sensing

International Nuclear Information System (INIS)

Potluri, U S; Madanayake, A; Rajapaksha, N; Cintra, R J; Bayer, F M

2012-01-01

Multi-beamforming is an important requirement for broadband space imaging applications based on dense aperture arrays (AAs). Usually, the discrete Fourier transform is the transform of choice for AA electromagnetic imaging. Here, the discrete cosine transform (DCT) is proposed as an alternative, enabling the use of emerging fast algorithms that offer greatly reduced complexity in digital arithmetic circuits. We propose two novel high-speed digital architectures for recently proposed fast algorithms (Bouguezel, Ahmad and Swamy 2008 Electron. Lett. 44 1249–50) (BAS-2008) and (Cintra and Bayer 2011 IEEE Signal Process. Lett. 18 579–82) (CB-2011) that provide good approximations to the DCT at zero multiplicative complexity. Further, we propose a novel DCT approximation having zero multiplicative complexity that is shown to be better for multi-beamforming AAs when compared to BAS-2008 and CB-2011. The far-field array pattern of ideal DCT, BAS-2008, CB-2011 and proposed approximation are investigated with error analysis. Extensive hardware realizations, implementation details and performance metrics are provided for synchronous field programmable gate array (FPGA) technology from Xilinx. The resource consumption and speed metrics of BAS-2008, CB-2011 and the proposed approximation are investigated as functions of system word size. The 8-bit versions are mapped to emerging asynchronous FPGAs leading to significantly increased real-time throughput with clock rates at up to 925.6 MHz implying the fastest DCT approximations using reconfigurable logic devices in the literature. (paper)

Indirect gonioscopy system for imaging iridocorneal angle of eye

Science.gov (United States)

Perinchery, Sandeep M.; Fu, Chan Yiu; Baskaran, Mani; Aung, Tin; Murukeshan, V. M.

2017-08-01

Current clinical optical imaging systems do not provide sufficient structural information of trabecular meshwork (TM) in the iridocorneal angle (ICA) of the eye due to their low resolution. Increase in the intraocular pressure (IOP) can occur due to the abnormalities in TM, which could subsequently lead to glaucoma. Here, we present an indirect gonioscopy based imaging probe with significantly improved visualization of structures in the ICA including TM region, compared to the currently available tools. Imaging quality of the developed system was tested in porcine samples. Improved direct high quality visualization of the TM region through this system can be used for Laser trabeculoplasty, which is a primary treatment of glaucoma. This system is expected to be used complementary to angle photography and gonioscopy.

Space imaging measurement system based on fixed lens and moving detector

Science.gov (United States)

Akiyama, Akira; Doshida, Minoru; Mutoh, Eiichiro; Kumagai, Hideo; Yamada, Hirofumi; Ishii, Hiromitsu

2006-08-01

We have developed the Space Imaging Measurement System based on the fixed lens and fast moving detector to the control of the autonomous ground vehicle. The space measurement is the most important task in the development of the autonomous ground vehicle. In this study we move the detector back and forth along the optical axis at the fast rate to measure the three-dimensional image data. This system is just appropriate to the autonomous ground vehicle because this system does not send out any optical energy to measure the distance and keep the safety. And we use the digital camera of the visible ray range. Therefore it gives us the cost reduction of the three-dimensional image data acquisition with respect to the imaging laser system. We can combine many pieces of the narrow space imaging measurement data to construct the wide range three-dimensional data. This gives us the improvement of the image recognition with respect to the object space. To develop the fast movement of the detector, we build the counter mass balance in the mechanical crank system of the Space Imaging Measurement System. And then we set up the duct to prevent the optical noise due to the ray not coming through lens. The object distance is derived from the focus distance which related to the best focused image data. The best focused image data is selected from the image of the maximum standard deviation in the standard deviations of series images.

Image-based Exploration of Iso-surfaces for Large Multi- Variable Datasets using Parameter Space.

KAUST Repository

Binyahib, Roba S.

2013-05-13

With an increase in processing power, more complex simulations have resulted in larger data size, with higher resolution and more variables. Many techniques have been developed to help the user to visualize and analyze data from such simulations. However, dealing with a large amount of multivariate data is challenging, time- consuming and often requires high-end clusters. Consequently, novel visualization techniques are needed to explore such data. Many users would like to visually explore their data and change certain visual aspects without the need to use special clusters or having to load a large amount of data. This is the idea behind explorable images (EI). Explorable images are a novel approach that provides limited interactive visualization without the need to re-render from the original data [40]. In this work, the concept of EI has been used to create a workflow that deals with explorable iso-surfaces for scalar fields in a multivariate, time-varying dataset. As a pre-processing step, a set of iso-values for each scalar field is inferred and extracted from a user-assisted sampling technique in time-parameter space. These iso-values are then used to generate iso- surfaces that are then pre-rendered (from a fixed viewpoint) along with additional buffers (i.e. normals, depth, values of other fields, etc.) to provide a compressed representation of iso-surfaces in the dataset. We present a tool that at run-time allows the user to interactively browse and calculate a combination of iso-surfaces superimposed on each other. The result is the same as calculating multiple iso- surfaces from the original data but without the memory and processing overhead. Our tool also allows the user to change the (scalar) values superimposed on each of the surfaces, modify their color map, and interactively re-light the surfaces. We demonstrate the effectiveness of our approach over a multi-terabyte combustion dataset. We also illustrate the efficiency and accuracy of our

Results from a multi aperture Fizeau interferometer ground testbed: demonstrator for a future space-based interferometer

Science.gov (United States)

Baccichet, Nicola; Caillat, Amandine; Rakotonimbahy, Eddy; Dohlen, Kjetil; Savini, Giorgio; Marcos, Michel

2016-08-01

In the framework of the European FP7-FISICA (Far Infrared Space Interferometer Critical Assessment) program, we developed a miniaturized version of the hyper-telescope to demonstrate multi-aperture interferometry on ground. This setup would be ultimately integrated into a CubeSat platform, therefore providing the first real demonstrator of a multi aperture Fizeau interferometer in space. In this paper, we describe the optical design of the ground testbed and the data processing pipeline implemented to reconstruct the object image from interferometric data. As a scientific application, we measured the Sun diameter by fitting a limb-darkening model to our data. Finally, we present the design of a CubeSat platform carrying this miniature Fizeau interferometer, which could be used to monitor the Sun diameter over a long in-orbit period.

Compositional-prior-guided image reconstruction algorithm for multi-modality imaging

Science.gov (United States)

Fang, Qianqian; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

2010-01-01

The development of effective multi-modality imaging methods typically requires an efficient information fusion model, particularly when combining structural images with a complementary imaging modality that provides functional information. We propose a composition-based image segmentation method for X-ray digital breast tomosynthesis (DBT) and a structural-prior-guided image reconstruction for a combined DBT and diffuse optical tomography (DOT) breast imaging system. Using the 3D DBT images from 31 clinically measured healthy breasts, we create an empirical relationship between the X-ray intensities for adipose and fibroglandular tissue. We use this relationship to then segment another 58 healthy breast DBT images from 29 subjects into compositional maps of different tissue types. For each breast, we build a weighted-graph in the compositional space and construct a regularization matrix to incorporate the structural priors into a finite-element-based DOT image reconstruction. Use of the compositional priors enables us to fuse tissue anatomy into optical images with less restriction than when using a binary segmentation. This allows us to recover the image contrast captured by DOT but not by DBT. We show that it is possible to fine-tune the strength of the structural priors by changing a single regularization parameter. By estimating the optical properties for adipose and fibroglandular tissue using the proposed algorithm, we found the results are comparable or superior to those estimated with expert-segmentations, but does not involve the time-consuming manual selection of regions-of-interest. PMID:21258460

PSF Estimation of Space-Variant Ultra-Wide Field of View Imaging Systems

Directory of Open Access Journals (Sweden)

Petr Janout

2017-02-01

Full Text Available Ultra-wide-field of view (UWFOV imaging systems are affected by various aberrations, most of which are highly angle-dependent. A description of UWFOV imaging systems, such as microscopy optics, security camera systems and other special space-variant imaging systems, is a difficult task that can be achieved by estimating the Point Spread Function (PSF of the system. This paper proposes a novel method for modeling the space-variant PSF of an imaging system using the Zernike polynomials wavefront description. The PSF estimation algorithm is based on obtaining field-dependent expansion coefficients of the Zernike polynomials by fitting real image data of the analyzed imaging system using an iterative approach in an initial estimate of the fitting parameters to ensure convergence robustness. The method is promising as an alternative to the standard approach based on Shack–Hartmann interferometry, since the estimate of the aberration coefficients is processed directly in the image plane. This approach is tested on simulated and laboratory-acquired image data that generally show good agreement. The resulting data are compared with the results of other modeling methods. The proposed PSF estimation method provides around 5% accuracy of the optical system model.

Climatology of the Aerosol Optical Depth by Components from the Multi-Angle Imaging Spectroradiometer (MISR) and Chemistry Transport Models

Science.gov (United States)

Lee, Huikyo; Kalashnikova, Olga V.; Suzuki, Kentaroh; Braverman, Amy; Garay, Michael J.; Kahn, Ralph A.

2016-01-01

The Multi-angle Imaging Spectroradiometer (MISR) Joint Aerosol (JOINT_AS) Level 3 product has provided a global, descriptive summary of MISR Level 2 aerosol optical depth (AOD) and aerosol type information for each month over 16+ years since March 2000. Using Version 1 of JOINT_AS, which is based on the operational (Version 22) MISR Level 2 aerosol product, this study analyzes, for the first time, characteristics of observed and simulated distributions of AOD for three broad classes of aerosols: spherical nonabsorbing, spherical absorbing, and nonspherical - near or downwind of their major source regions. The statistical moments (means, standard deviations, and skew-nesses) and distributions of AOD by components derived from the JOINT_AS are compared with results from two chemistry transport models (CTMs), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) and SPectral RadIatioN-TrAnSport (SPRINTARS). Overall, the AOD distributions retrieved from MISR and modeled by GOCART and SPRINTARS agree with each other in a qualitative sense. Marginal distributions of AOD for each aerosol type in both MISR and models show considerable high positive skewness, which indicates the importance of including extreme AOD events when comparing satellite retrievals with models. The MISR JOINT_AS product will greatly facilitate comparisons between satellite observations and model simulations of aerosols by type.

Muon tomography imaging improvement using optimized limited angle data

Science.gov (United States)

Bai, Chuanyong; Simon, Sean; Kindem, Joel; Luo, Weidong; Sossong, Michael J.; Steiger, Matthew

2014-05-01

Image resolution of muon tomography is limited by the range of zenith angles of cosmic ray muons and the flux rate at sea level. Low flux rate limits the use of advanced data rebinning and processing techniques to improve image quality. By optimizing the limited angle data, however, image resolution can be improved. To demonstrate the idea, physical data of tungsten blocks were acquired on a muon tomography system. The angular distribution and energy spectrum of muons measured on the system was also used to generate simulation data of tungsten blocks of different arrangement (geometry). The data were grouped into subsets using the zenith angle and volume images were reconstructed from the data subsets using two algorithms. One was a distributed PoCA (point of closest approach) algorithm and the other was an accelerated iterative maximal likelihood/expectation maximization (MLEM) algorithm. Image resolution was compared for different subsets. Results showed that image resolution was better in the vertical direction for subsets with greater zenith angles and better in the horizontal plane for subsets with smaller zenith angles. The overall image resolution appeared to be the compromise of that of different subsets. This work suggests that the acquired data can be grouped into different limited angle data subsets for optimized image resolution in desired directions. Use of multiple images with resolution optimized in different directions can improve overall imaging fidelity and the intended applications.

A brain MRI bias field correction method created in the Gaussian multi-scale space

Science.gov (United States)

Chen, Mingsheng; Qin, Mingxin

2017-07-01

A pre-processing step is needed to correct for the bias field signal before submitting corrupted MR images to such image-processing algorithms. This study presents a new bias field correction method. The method creates a Gaussian multi-scale space by the convolution of the inhomogeneous MR image with a two-dimensional Gaussian function. In the multi-Gaussian space, the method retrieves the image details from the differentiation of the original image and convolution image. Then, it obtains an image whose inhomogeneity is eliminated by the weighted sum of image details in each layer in the space. Next, the bias field-corrected MR image is retrieved after the Υ correction, which enhances the contrast and brightness of the inhomogeneity-eliminated MR image. We have tested the approach on T1 MRI and T2 MRI with varying bias field levels and have achieved satisfactory results. Comparison experiments with popular software have demonstrated superior performance of the proposed method in terms of quantitative indices, especially an improvement in subsequent image segmentation.

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

Science.gov (United States)

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

Multi-viewpoint Image Array Virtual Viewpoint Rapid Generation Algorithm Based on Image Layering

Science.gov (United States)

Jiang, Lu; Piao, Yan

2018-04-01

The use of multi-view image array combined with virtual viewpoint generation technology to record 3D scene information in large scenes has become one of the key technologies for the development of integrated imaging. This paper presents a virtual viewpoint rendering method based on image layering algorithm. Firstly, the depth information of reference viewpoint image is quickly obtained. During this process, SAD is chosen as the similarity measure function. Then layer the reference image and calculate the parallax based on the depth information. Through the relative distance between the virtual viewpoint and the reference viewpoint, the image layers are weighted and panned. Finally the virtual viewpoint image is rendered layer by layer according to the distance between the image layers and the viewer. This method avoids the disadvantages of the algorithm DIBR, such as high-precision requirements of depth map and complex mapping operations. Experiments show that, this algorithm can achieve the synthesis of virtual viewpoints in any position within 2×2 viewpoints range, and the rendering speed is also very impressive. The average result proved that this method can get satisfactory image quality. The average SSIM value of the results relative to real viewpoint images can reaches 0.9525, the PSNR value can reaches 38.353 and the image histogram similarity can reaches 93.77%.

MR imaging of the temporomandibular joint. Part 2. Effect of flip angle on MR imaging with FLASH sequence

International Nuclear Information System (INIS)

Sakamoto, Maya; Sasano, Takashi; Higano, Shuichi; Takahashi, Shoki; Kurihara, Noriko

1998-01-01

In our previous study on MR imaging of the temporomandibular joint (TMJ), fast low angle shot (FLASH) showed the highest image contrast between disc and surrounding TMJ tissues compared with those of 4 other sequences (i,e., fast imaging with steady precession (FISP), conventional T1-weighted spin echo (SE) and fast spin echo (FSE, TR/TE/ETL: 1100/12/3, 3000/15/7)). Furthermore, FLASH also received a high score on visual evaluation including the position and contour of the disc, and the border between the disc and surrounding tissues. Therefore, we concluded that FLASH was the most suitable sequence for evaluating the TMJ disc. However, the image contrast and signal intensity on MR imaging with gradient echo pulse sequence are affected by flip angle. Consequently, in this report, to find the most suitable flip angle for MR scanning of the TMJ using a FLASH sequence (TR/TE: 450/11), ten TMJs of 5 volunteers were experimentally imaged with various flip angles from 10 degrees to 70 degrees at an interval of 10 degrees between 10 to 70. The image contrast and contrast-to-noise ratio (CNR) between the disc and surrounding tissues were compared. In addition, signal-to-noise ratio (SNR) of phantoms was also calculated using the same imaging parameters. Visual evaluation including position and contour of the disc, and the border between the disc and surrounding tissues, was also performed by 4 radiologists. As the flip angle increased, imaging contrast decreased while SNR increased. Images with flip angles between 30 and 60 degrees demonstrated high CNR. On visual evaluation, images using flip angles between 30 and 50 degrees received high scores. In conclusion, FLASH sequence with a flip angle between 30 and 50 degrees was considered most suitable for evaluating the TMJ disc based on the results of visual assessment and analysis of three major components of image diagnostic quality: image contrast, CNR and SNR. (author)

Use of multi-frequency, multi-polarization, multi-angle airborne radars for class discrimination in a southern temperature forest

Science.gov (United States)

Mehta, N. C.

1984-01-01

The utility of radar scatterometers for discrimination and characterization of natural vegetation was investigated. Backscatter measurements were acquired with airborne multi-frequency, multi-polarization, multi-angle radar scatterometers over a test site in a southern temperate forest. Separability between ground cover classes was studied using a two-class separability measure. Very good separability is achieved between most classes. Longer wavelength is useful in separating trees from non-tree classes, while shorter wavelength and cross polarization are helpful for discrimination among tree classes. Using the maximum likelihood classifier, 50% overall classification accuracy is achieved using a single, short-wavelength scatterometer channel. Addition of multiple incidence angles and another radar band improves classification accuracy by 20% and 50%, respectively, over the single channel accuracy. Incorporation of a third radar band seems redundant for vegetation classification. Vertical transmit polarization is critically important for all classes.

Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

KAUST Repository

Zhu, Xiaofeng; Xie, Qing; Zhu, Yonghua; Liu, Xingyi; Zhang, Shichao

2015-01-01

This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple

Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront

Directory of Open Access Journals (Sweden)

Jingkun Gao

2016-12-01

Full Text Available An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG-based nonuniform FFT (NUFFT is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section of targets in the terahertz regime.

Functional range of movement of the hand: declination angles to reachable space.

Science.gov (United States)

Pham, Hai Trieu; Pathirana, Pubudu N; Caelli, Terry

2014-01-01

The measurement of the range of hand joint movement is an essential part of clinical practice and rehabilitation. Current methods use three finger joint declination angles of the metacarpophalangeal, proximal interphalangeal and distal interphalangeal joints. In this paper we propose an alternate form of measurement for the finger movement. Using the notion of reachable space instead of declination angles has significant advantages. Firstly, it provides a visual and quantifiable method that therapists, insurance companies and patients can easily use to understand the functional capabilities of the hand. Secondly, it eliminates the redundant declination angle constraints. Finally, reachable space, defined by a set of reachable fingertip positions, can be measured and constructed by using a modern camera such as Creative Senz3D or built-in hand gesture sensors such as the Leap Motion Controller. Use of cameras or optical-type sensors for this purpose have considerable benefits such as eliminating and minimal involvement of therapist errors, non-contact measurement in addition to valuable time saving for the clinician. A comparison between using declination angles and reachable space were made based on Hume's experiment on functional range of movement to prove the efficiency of this new approach.

Front-end vision and multi-scale image analysis multi-scale computer vision theory and applications, written in Mathematica

CERN Document Server

Romeny, Bart M Haar

2008-01-01

Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective

Automatic anterior chamber angle assessment for HD-OCT images.

Science.gov (United States)

Tian, Jing; Marziliano, Pina; Baskaran, Mani; Wong, Hong-Tym; Aung, Tin

2011-11-01

Angle-closure glaucoma is a major blinding eye disease and could be detected by measuring the anterior chamber angle in the human eyes. High-definition OCT (Cirrus HD-OCT) is an emerging noninvasive, high-speed, and high-resolution imaging modality for the anterior segment of the eye. Here, we propose a novel algorithm which automatically detects a new landmark, Schwalbe's line, and measures the anterior chamber angle in the HD-OCT images. The distortion caused by refraction is corrected by dewarping the HD-OCT images, and three biometric measurements are defined to quantitatively assess the anterior chamber angle. The proposed algorithm was tested on 40 HD-OCT images of the eye and provided accurate measurements in about 1 second.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

International Nuclear Information System (INIS)

Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J

2016-01-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. (paper)

The design and application of a multi-band IR imager

Science.gov (United States)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

Scattering angle-based filtering via extension in velocity

KAUST Repository

Kazei, Vladimir; Tessmer, Ekkehart; Alkhalifah, Tariq

2016-01-01

The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

Scattering angle-based filtering via extension in velocity

KAUST Repository

Kazei, Vladimir

2016-09-06

The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

Multi-Temporal vs. Hyper-Spectral Imaging for Future Land Imaging at 30 m

Data.gov (United States)

National Aeronautics and Space Administration — We propose to determine the information content of multi-temporal land imaging in discrete Landsat-like spectral bands at 30 m with a 360 km swath width and compare...

Image Analysis Based on Soft Computing and Applied on Space Shuttle During the Liftoff Process

Science.gov (United States)

Dominquez, Jesus A.; Klinko, Steve J.

2007-01-01

Imaging techniques based on Soft Computing (SC) and developed at Kennedy Space Center (KSC) have been implemented on a variety of prototype applications related to the safety operation of the Space Shuttle during the liftoff process. These SC-based prototype applications include detection and tracking of moving Foreign Objects Debris (FOD) during the Space Shuttle liftoff, visual anomaly detection on slidewires used in the emergency egress system for the Space Shuttle at the laJlIlch pad, and visual detection of distant birds approaching the Space Shuttle launch pad. This SC-based image analysis capability developed at KSC was also used to analyze images acquired during the accident of the Space Shuttle Columbia and estimate the trajectory and velocity of the foam that caused the accident.

A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.

Science.gov (United States)

Rau, Jiann-Yeou; Yeh, Po-Chia

2012-01-01

The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum.

Generalized probabilistic scale space for image restoration.

Science.gov (United States)

Wong, Alexander; Mishra, Akshaya K

2010-10-01

A novel generalized sampling-based probabilistic scale space theory is proposed for image restoration. We explore extending the definition of scale space to better account for both noise and observation models, which is important for producing accurately restored images. A new class of scale-space realizations based on sampling and probability theory is introduced to realize this extended definition in the context of image restoration. Experimental results using 2-D images show that generalized sampling-based probabilistic scale-space theory can be used to produce more accurate restored images when compared with state-of-the-art scale-space formulations, particularly under situations characterized by low signal-to-noise ratios and image degradation.

Multi-scale Gaussian representation and outline-learning based cell image segmentation

Science.gov (United States)

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

Three dimensional multi perspective imaging with randomly distributed sensors

International Nuclear Information System (INIS)

DaneshPanah, Mehdi; Javidi, Bahrain

2008-01-01

In this paper, we review a three dimensional (3D) passive imaging system that exploits the visual information captured from the scene from multiple perspectives to reconstruct the scene voxel by voxel in 3D space. The primary contribution of this work is to provide a computational reconstruction scheme based on randomly distributed sensor locations in space. In virtually all of multi perspective techniques (e.g. integral imaging, synthetic aperture integral imaging, etc), there is an implicit assumption that the sensors lie on a simple, regular pickup grid. Here, we relax this assumption and suggest a computational reconstruction framework that unifies the available methods as its special cases. The importance of this work is that it enables three dimensional imaging technology to be implemented in a multitude of novel application domains such as 3D aerial imaging, collaborative imaging, long range 3D imaging and etc, where sustaining a regular pickup grid is not possible and/or the parallax requirements call for a irregular or sparse synthetic aperture mode. Although the sensors can be distributed in any random arrangement, we assume that the pickup position is measured at the time of capture of each elemental image. We demonstrate the feasibility of the methods proposed here by experimental results.

Space situational awareness satellites and ground based radiation counting and imaging detector technology

International Nuclear Information System (INIS)

Jansen, Frank; Behrens, Joerg; Pospisil, Stanislav; Kudela, Karel

2011-01-01

We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

Space situational awareness satellites and ground based radiation counting and imaging detector technology

Energy Technology Data Exchange (ETDEWEB)

Jansen, Frank, E-mail: frank.jansen@dlr.de [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Behrens, Joerg [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Pospisil, Stanislav [Czech Technical University, IEAP, 12800 Prague 2, Horska 3a/22 (Czech Republic); Kudela, Karel [Slovak Academy of Sciences, IEP, 04001 Kosice, Watsonova 47 (Slovakia)

2011-05-15

We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

Refraction angle and edge visibility in X-ray diffraction enhanced imaging

International Nuclear Information System (INIS)

Chen Yu; Jia Quanjie; Li Gang; Wang Yuzhu; Xue Xianying; Jiang Xiaoming

2007-01-01

Diffraction-enhanced X-ray imaging could extract accurately the refraction angles of the sample, which is very important to increase the image contrast of low Z samples. In this paper, the DEI experiments with X-rays of different energies were performed both on wedge-shaped and rounded model samples. Refraction angles of the two samples were all obtained accurately, and the results agreed well with the calculations. Quantitative analyses based on Edge Visibility were performed for the wedge-shaped model sample. The results revealed that the calculated positions for the Best Edge Visibility of the slope with fixed refraction angle were calculable in good agreement with the experimental results. A quantitative research on the Edge Visibility of real tissues sample was carried out and the optimal condition for best contrast of DEI images were discussed. (authors)

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

Science.gov (United States)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamic angle selection in X-ray computed tomography

Energy Technology Data Exchange (ETDEWEB)

Dabravolski, Andrei, E-mail: andrei.dabravolski@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Batenburg, Kees Joost, E-mail: joost.batenburg@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Centrum Wiskunde and Informatica (CWI), Science Park 123, 1098 XG Amsterdam (Netherlands); Sijbers, Jan, E-mail: jan.sijbers@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium)

2014-04-01

Highlights: • We propose the dynamic angle selection algorithm for CT scanning. • The approach is based on the concept of information gain over a set of solutions. • Projection angles are selected based on the already available projection data. • The approach can lead to more accurate results from fewer projections. - Abstract: In X-ray tomography, a number of radiographs (projections) are recorded from which a tomogram is then reconstructed. Conventionally, these projections are acquired equiangularly, resulting in an unbiased sampling of the Radon space. However, especially in case when only a limited number of projections can be acquired, the selection of the angles has a large impact on the quality of the reconstructed image. In this paper, a dynamic algorithm is proposed, in which new projection angles are selected by maximizing the information gain about the object, given the set of possible new angles. Experiments show that this approach can select projection angles for which the accuracy of the reconstructed image is significantly higher compared to the standard angle selections schemes.

Dynamic angle selection in X-ray computed tomography

International Nuclear Information System (INIS)

Dabravolski, Andrei; Batenburg, Kees Joost; Sijbers, Jan

2014-01-01

Highlights: • We propose the dynamic angle selection algorithm for CT scanning. • The approach is based on the concept of information gain over a set of solutions. • Projection angles are selected based on the already available projection data. • The approach can lead to more accurate results from fewer projections. - Abstract: In X-ray tomography, a number of radiographs (projections) are recorded from which a tomogram is then reconstructed. Conventionally, these projections are acquired equiangularly, resulting in an unbiased sampling of the Radon space. However, especially in case when only a limited number of projections can be acquired, the selection of the angles has a large impact on the quality of the reconstructed image. In this paper, a dynamic algorithm is proposed, in which new projection angles are selected by maximizing the information gain about the object, given the set of possible new angles. Experiments show that this approach can select projection angles for which the accuracy of the reconstructed image is significantly higher compared to the standard angle selections schemes

Neutron μstiX. Micrometer structure investigation with real space and reciprocal space crossover using neutron imaging detectors

Energy Technology Data Exchange (ETDEWEB)

Muehlbauer, Martin Johann

2013-07-19

This work is concerned with the investigation of inhomogeneities in materials with length scales of the order of micrometers by means of neutrons. In real space this is done by neutron imaging methods measuring the transmitted signal while for Ultra Small Angle Neutron Scattering (USANS) the signal of the scattered neutrons is assigned to a spatial frequency distribution in reciprocal space. The part about neutron imaging is focused on time-resolved neutron radiography on an injection nozzle similar to the ones used for modern diesel truck engines. The associated experiments have been carried out at the neutron imaging facility ANTARES at the Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) of the Technische Universitaet Muenchen in Garching near Munich. Especially the demands on the detector system were high. Therefore different detection methods and detector configurations have been tested. On the one hand the detector should allow for a time resolution high enough to record the injection process lasting about 900 μs. On the other hand it needed to offer a spatial resolution sufficient to resolve the test oil inside the spray hole of a maximum diameter of less than 200 μm. An advanced aim of this work is the visualization of cavitation phenomena which may occur during the injection process inside of the spray hole. In order to operate the injector at conditions as close to reality as possible a high pressure pump supplying the injector with test oil at a pressure of 1600 bar was needed in addition to the specially developed control electronics, the recuperation tank and the exhaust gas equipment for the escaping atomized spray. A second part of the work describes USANS experiments based on the idea of Dr. Roland Gaehler and carried out at the instrument D11 at the Institut Laue-Langevin in Grenoble. For this purpose a specific multi-beam geometry was applied, where a multi-slit aperture replaced the standard source aperture and the sample aperture was

Neutron μstiX. Micrometer structure investigation with real space and reciprocal space crossover using neutron imaging detectors

International Nuclear Information System (INIS)

Muehlbauer, Martin Johann

2013-01-01

This work is concerned with the investigation of inhomogeneities in materials with length scales of the order of micrometers by means of neutrons. In real space this is done by neutron imaging methods measuring the transmitted signal while for Ultra Small Angle Neutron Scattering (USANS) the signal of the scattered neutrons is assigned to a spatial frequency distribution in reciprocal space. The part about neutron imaging is focused on time-resolved neutron radiography on an injection nozzle similar to the ones used for modern diesel truck engines. The associated experiments have been carried out at the neutron imaging facility ANTARES at the Forschungs-Neutronenquelle Heinz Maier-Leibnitz (FRM II) of the Technische Universitaet Muenchen in Garching near Munich. Especially the demands on the detector system were high. Therefore different detection methods and detector configurations have been tested. On the one hand the detector should allow for a time resolution high enough to record the injection process lasting about 900 μs. On the other hand it needed to offer a spatial resolution sufficient to resolve the test oil inside the spray hole of a maximum diameter of less than 200 μm. An advanced aim of this work is the visualization of cavitation phenomena which may occur during the injection process inside of the spray hole. In order to operate the injector at conditions as close to reality as possible a high pressure pump supplying the injector with test oil at a pressure of 1600 bar was needed in addition to the specially developed control electronics, the recuperation tank and the exhaust gas equipment for the escaping atomized spray. A second part of the work describes USANS experiments based on the idea of Dr. Roland Gaehler and carried out at the instrument D11 at the Institut Laue-Langevin in Grenoble. For this purpose a specific multi-beam geometry was applied, where a multi-slit aperture replaced the standard source aperture and the sample aperture was

Double-theodolite measurement system used in the image calibration of space photographic instrument

Institute of Scientific and Technical Information of China (English)

LI Yan; QIAO Yan-feng; SU Wan-xin; LIU Ze-xun

2005-01-01

The purpose of characterizing the image of space photographic instrument is to gain the space included angles from three coordinate axes in the three-dimensional coordinate of the image and the directionality of the three axes of coordinate in the frame of axes of the instrument. The two reference frames will keep in the same direction finally by adjusting according to space angles. This problem was solved by a new high-precision measurement system composed of a double-theodolite and a set of communication system. In the survey system, two TDA5005 total stations from Leica Company will be selected as the double-theodolite and the interdependence of both coordinate systems can be achieved by moving the stations only at one time. Therefore, this measurement system provides a highly efficient and high-precision surveying method to the image calibration of the space photographic instrument. According to the experiment, its measuring accuracy can reach arc-second level.

Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

Science.gov (United States)

Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

2015-02-01

A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

Photometric Calibration and Image Stitching for a Large Field of View Multi-Camera System

Directory of Open Access Journals (Sweden)

Yu Lu

2016-04-01

Full Text Available A new compact large field of view (FOV multi-camera system is introduced. The camera is based on seven tiny complementary metal-oxide-semiconductor sensor modules covering over 160° × 160° FOV. Although image stitching has been studied extensively, sensor and lens differences have not been considered in previous multi-camera devices. In this study, we have calibrated the photometric characteristics of the multi-camera device. Lenses were not mounted on the sensor in the process of radiometric response calibration to eliminate the influence of the focusing effect of uniform light from an integrating sphere. Linearity range of the radiometric response, non-linearity response characteristics, sensitivity, and dark current of the camera response function are presented. The R, G, and B channels have different responses for the same illuminance. Vignetting artifact patterns have been tested. The actual luminance of the object is retrieved by sensor calibration results, and is used to blend images to make panoramas reflect the objective luminance more objectively. This compensates for the limitation of stitching images that are more realistic only through the smoothing method. The dynamic range limitation of can be resolved by using multiple cameras that cover a large field of view instead of a single image sensor with a wide-angle lens. The dynamic range is expanded by 48-fold in this system. We can obtain seven images in one shot with this multi-camera system, at 13 frames per second.

Horror Image Recognition Based on Context-Aware Multi-Instance Learning.

Science.gov (United States)

Li, Bing; Xiong, Weihua; Wu, Ou; Hu, Weiming; Maybank, Stephen; Yan, Shuicheng

2015-12-01

Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme emotions. In this paper, we present a novel context-aware multi-instance learning (CMIL) algorithm for horror image recognition. The CMIL algorithm identifies horror images and picks out the regions that cause the sensation of horror in these horror images. It obtains contextual cues among adjacent regions in an image using a random walk on a contextual graph. Borrowing the strength of the fuzzy support vector machine (FSVM), we define a heuristic optimization procedure based on the FSVM to search for the optimal classifier for the CMIL. To improve the initialization of the CMIL, we propose a novel visual saliency model based on the tensor analysis. The average saliency value of each segmented region is set as its initial fuzzy membership in the CMIL. The advantage of the tensor-based visual saliency model is that it not only adaptively selects features, but also dynamically determines fusion weights for saliency value combination from different feature subspaces. The effectiveness of the proposed CMIL model is demonstrated by its use in horror image recognition on two large-scale image sets collected from the Internet.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

International Nuclear Information System (INIS)

Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

2011-01-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

Estimation of canopy carotenoid content of winter wheat using multi-angle hyperspectral data

Science.gov (United States)

Kong, Weiping; Huang, Wenjiang; Liu, Jiangui; Chen, Pengfei; Qin, Qiming; Ye, Huichun; Peng, Dailiang; Dong, Yingying; Mortimer, A. Hugh

2017-11-01

Precise estimation of carotenoid (Car) content in crops, using remote sensing data, could be helpful for agricultural resources management. Conventional methods for Car content estimation were mostly based on reflectance data acquired from nadir direction. However, reflectance acquired at this direction is highly influenced by canopy structure and soil background reflectance. Off-nadir observation is less impacted, and multi-angle viewing data are proven to contain additional information rarely exploited for crop Car content estimation. The objective of this study was to explore the potential of multi-angle observation data for winter wheat canopy Car content estimation. Canopy spectral reflectance was measured from nadir as well as from a series of off-nadir directions during different growing stages of winter wheat, with concurrent canopy Car content measurements. Correlation analyses were performed between Car content and the original and continuum removed spectral reflectance. Spectral features and previously published indices were derived from data obtained at different viewing angles and were tested for Car content estimation. Results showed that spectral features and indices obtained from backscattering directions between 20° and 40° view zenith angle had a stronger correlation with Car content than that from the nadir direction, and the strongest correlation was observed from about 30° backscattering direction. Spectral absorption depth at 500 nm derived from spectral data obtained from 30° backscattering direction was found to reduce the difference induced by plant cultivars greatly. It was the most suitable for winter wheat canopy Car estimation, with a coefficient of determination 0.79 and a root mean square error of 19.03 mg/m2. This work indicates the importance of taking viewing geometry effect into account when using spectral features/indices and provides new insight in the application of multi-angle remote sensing for the estimation of crop

Development of multi-color scintillator based X-ray image intensifier

International Nuclear Information System (INIS)

Nittoh, Koichi; Konagai, Chikara; Noji, Takashi

2004-01-01

A multi-color scintillator based high-sensitive, wide dynamic range and long-life X-ray image intensifier has been developed. An europium activated Y 2 O 2 S scintillator, emitting red, green and blue photons of different intensities, is utilized as the output fluorescent screen of the intensifier. By combining this image intensifier with a suitably tuned high sensitive color CCD camera, it is possible for a sensitivity of the red color component to become six times higher than that of the conventional image intensifier. Simultaneous emission of a moderate green color and a weak blue color covers different sensitivity regions. This widens the dynamic range, by nearly two orders of ten. With this image intensifier, it is possible to image simultaneously complex objects containing various different X-ray transmission from paper, water or plastic to heavy metals. This high sensitivity intensifier, operated at lower X-ray exposure, causes less degradation of scintillator materials and less colorization of output screen glass, and thus helps achieve a longer lifetime. This color scintillator based image intensifier is being introduced for X-ray inspection in various fields

Status of the Multi-Angle SpectroRadiometer Instrument for EOS- AM1 and Its Application to Remote Sensing of Aerosols

Science.gov (United States)

Diner, D. J.; Abdou, W. A.; Bruegge, C. J.; Conel, J. E.; Kahn, R. A.; Martonchik, J. V.; Paradise, S. R.; West, R. A.

1995-01-01

The Multi-Angle Imaging SpectroRadiometer (MISR) is being developed at JPL for the AM1 spacecraft in the Earth Observing System (EOS) series. This paper reports on the progress of instrument fabrication and testing, and it discusses the strategy to use the instrument for studying tropospheric aerosols.

Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

Science.gov (United States)

Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

2017-12-01

This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

Frequency scaling for angle gathers

KAUST Repository

Zuberi, M. A H; Alkhalifah, Tariq Ali

2014-01-01

Angle gathers provide an extra dimension to analyze the velocity after migration. Space-shift and time shift-imaging conditions are two methods used to obtain angle gathers, but both are reasonably expensive. By scaling the time-lag axis of the time-shifted images, the computational cost of the time shift imaging condition can be considerably reduced. In imaging and more so Full waveform inversion, frequencydomain Helmholtz solvers are used more often to solve for the wavefields than conventional time domain extrapolators. In such cases, we do not need to extend the image, instead we scale the frequency axis of the frequency domain image to obtain the angle gathers more efficiently. Application on synthetic data demonstrate such features.

An intelligent space for mobile robot localization using a multi-camera system.

Science.gov (United States)

Rampinelli, Mariana; Covre, Vitor Buback; de Queiroz, Felippe Mendonça; Vassallo, Raquel Frizera; Bastos-Filho, Teodiano Freire; Mazo, Manuel

2014-08-15

This paper describes an intelligent space, whose objective is to localize and control robots or robotic wheelchairs to help people. Such an intelligent space has 11 cameras distributed in two laboratories and a corridor. The cameras are fixed in the environment, and image capturing is done synchronously. The system was programmed as a client/server with TCP/IP connections, and a communication protocol was defined. The client coordinates the activities inside the intelligent space, and the servers provide the information needed for that. Once the cameras are used for localization, they have to be properly calibrated. Therefore, a calibration method for a multi-camera network is also proposed in this paper. A robot is used to move a calibration pattern throughout the field of view of the cameras. Then, the captured images and the robot odometry are used for calibration. As a result, the proposed algorithm provides a solution for multi-camera calibration and robot localization at the same time. The intelligent space and the calibration method were evaluated under different scenarios using computer simulations and real experiments. The results demonstrate the proper functioning of the intelligent space and validate the multi-camera calibration method, which also improves robot localization.

An Intelligent Space for Mobile Robot Localization Using a Multi-Camera System

Directory of Open Access Journals (Sweden)

Mariana Rampinelli

2014-08-01

Full Text Available This paper describes an intelligent space, whose objective is to localize and control robots or robotic wheelchairs to help people. Such an intelligent space has 11 cameras distributed in two laboratories and a corridor. The cameras are fixed in the environment, and image capturing is done synchronously. The system was programmed as a client/server with TCP/IP connections, and a communication protocol was defined. The client coordinates the activities inside the intelligent space, and the servers provide the information needed for that. Once the cameras are used for localization, they have to be properly calibrated. Therefore, a calibration method for a multi-camera network is also proposed in this paper. A robot is used to move a calibration pattern throughout the field of view of the cameras. Then, the captured images and the robot odometry are used for calibration. As a result, the proposed algorithm provides a solution for multi-camera calibration and robot localization at the same time. The intelligent space and the calibration method were evaluated under different scenarios using computer simulations and real experiments. The results demonstrate the proper functioning of the intelligent space and validate the multi-camera calibration method, which also improves robot localization.

Large field distributed aperture laser semiactive angle measurement system design with imaging fiber bundles.

Science.gov (United States)

Xu, Chunyun; Cheng, Haobo; Feng, Yunpeng; Jing, Xiaoli

2016-09-01

A type of laser semiactive angle measurement system is designed for target detecting and tracking. Only one detector is used to detect target location from four distributed aperture optical systems through a 4×1 imaging fiber bundle. A telecentric optical system in image space is designed to increase the efficiency of imaging fiber bundles. According to the working principle of a four-quadrant (4Q) detector, fiber diamond alignment is adopted between an optical system and a 4Q detector. The structure of the laser semiactive angle measurement system is, we believe, novel. Tolerance analysis is carried out to determine tolerance limits of manufacture and installation errors of the optical system. The performance of the proposed method is identified by computer simulations and experiments. It is demonstrated that the linear region of the system is ±12°, with measurement error of better than 0.2°. In general, this new system can be used with large field of view and high accuracy, providing an efficient, stable, and fast method for angle measurement in practical situations.

A classification model of Hyperion image base on SAM combined decision tree

Science.gov (United States)

Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

2009-10-01

Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model

Angle imaging: Advances and challenges

Science.gov (United States)

Quek, Desmond T L; Nongpiur, Monisha E; Perera, Shamira A; Aung, Tin

2011-01-01

Primary angle closure glaucoma (PACG) is a major form of glaucoma in large populous countries in East and South Asia. The high visual morbidity from PACG is related to the destructive nature of the asymptomatic form of the disease. Early detection of anatomically narrow angles is important and the subsequent prevention of visual loss from PACG depends on an accurate assessment of the anterior chamber angle (ACA). This review paper discusses the advantages and limitations of newer ACA imaging technologies, namely ultrasound biomicroscopy, Scheimpflug photography, anterior segment optical coherence tomography and EyeCam, highlighting the current clinical evidence comparing these devices with each other and with clinical dynamic indentation gonioscopy, the current reference standard. PMID:21150037

PETRA, MSVAT-SPACE and SEMAC sequences for metal artefact reduction in dental MR imaging

International Nuclear Information System (INIS)

Hilgenfeld, Tim; Heil, Alexander; Bendszus, Martin; Prager, Marcel; Heiland, Sabine; Schwindling, Franz Sebastian; Rammelsberg, Peter; Nittka, Mathias; Grodzki, David

2017-01-01

Dental MRI is often impaired by artefacts due to metallic dental materials. Several sequences were developed to reduce susceptibility artefacts. Here, we evaluated a set of sequences for artefact reduction for dental MRI for the first time. Artefact volume, signal-to-noise ratio (SNR) and image quality were assessed on a 3-T MRI for pointwise encoding time reduction with radial acquisition (PETRA), multiple-slab acquisition with view angle tilting gradient, based on a sampling perfection with application-optimised contrasts using different flip angle evolution (SPACE) sequence (MSVAT-SPACE), slice-encoding for metal-artefact correction (SEMAC) and compared to a standard SPACE and a standard turbo-spin-echo (TSE) sequence. Field-of-view and acquisition times were chosen to enable in vivo application. Two implant-supported prostheses were tested (porcelain fused to metal non-precious alloy and monolithic zirconia). Smallest artefact was measured for TSE sequences with no difference between the standard TSE and the SEMAC. MSVAT-SPACE reduced artefacts about 56% compared to the standard SPACE. Effect of the PETRA was dependent on sample used. Image quality and SNR were comparable for all sequences except PETRA, which yielded poor results. There is no benefit in terms of artefact reduction for SEMAC compared to standard TSE. Usage of MSVAT-SPACE is advantageous since artefacts are reduced and higher resolution is achieved. (orig.)

PETRA, MSVAT-SPACE and SEMAC sequences for metal artefact reduction in dental MR imaging

Energy Technology Data Exchange (ETDEWEB)

Hilgenfeld, Tim; Heil, Alexander; Bendszus, Martin [Heidelberg University Hospital, Department of Neuroradiology, Heidelberg (Germany); Prager, Marcel; Heiland, Sabine [Heidelberg University Hospital, Department of Neuroradiology, Heidelberg (Germany); Heidelberg University Hospital, Section of Experimental Radiology, Heidelberg (Germany); Schwindling, Franz Sebastian; Rammelsberg, Peter [Heidelberg University Hospital, Department of Prosthodontics, Heidelberg (Germany); Nittka, Mathias; Grodzki, David [Siemens Healthcare GmbH, Erlangen (Germany)

2017-12-15

Dental MRI is often impaired by artefacts due to metallic dental materials. Several sequences were developed to reduce susceptibility artefacts. Here, we evaluated a set of sequences for artefact reduction for dental MRI for the first time. Artefact volume, signal-to-noise ratio (SNR) and image quality were assessed on a 3-T MRI for pointwise encoding time reduction with radial acquisition (PETRA), multiple-slab acquisition with view angle tilting gradient, based on a sampling perfection with application-optimised contrasts using different flip angle evolution (SPACE) sequence (MSVAT-SPACE), slice-encoding for metal-artefact correction (SEMAC) and compared to a standard SPACE and a standard turbo-spin-echo (TSE) sequence. Field-of-view and acquisition times were chosen to enable in vivo application. Two implant-supported prostheses were tested (porcelain fused to metal non-precious alloy and monolithic zirconia). Smallest artefact was measured for TSE sequences with no difference between the standard TSE and the SEMAC. MSVAT-SPACE reduced artefacts about 56% compared to the standard SPACE. Effect of the PETRA was dependent on sample used. Image quality and SNR were comparable for all sequences except PETRA, which yielded poor results. There is no benefit in terms of artefact reduction for SEMAC compared to standard TSE. Usage of MSVAT-SPACE is advantageous since artefacts are reduced and higher resolution is achieved. (orig.)

New 4.4 km-resolution aerosol product from NASA's Multi-angle Imaging SpectroRadiometer: A user's guide

Science.gov (United States)

Nastan, A.; Garay, M. J.; Witek, M. L.; Seidel, F.; Bull, M. A.; Kahn, R. A.; Diner, D. J.

2017-12-01

The NASA Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has provided an 18-year-and-growing aerosol data record. MISR's V22 aerosol product has been used extensively in studies of regional and global climate and the health effects of particulate air pollution. The MISR team recently released a new version of this product (V23), which increases the spatial resolution from 17.6 km to 4.4 km, improves performance versus AERONET, and provides better spatial coverage, more accurate cloud screening, and improved radiometric conditioning relative to V22. The product formatting was also completely revamped to improve clarity and usability. Established and prospective users of the MISR aerosol product are invited to learn about the features and performance of the new product and to participate in one-on-one demonstrations of how to obtain, visualize, and analyze the new product. Because the aerosol product is used in generating atmospherically-corrected surface bidirectional reflectance factors, improvements in MISR's 1.1 km resolution land surface product are a by-product of the updated aerosol retrievals. Illustrative comparisons of the V22 and V23 aerosol and surface products will be shown.

Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data

Science.gov (United States)

Matej, Samuel; Li, Yusheng; Panetta, Joseph; Karp, Joel S.; Surti, Suleman

2016-01-01

The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake

Development of a compact scintillator-based high-resolution Compton camera for molecular imaging

Energy Technology Data Exchange (ETDEWEB)

Kishimoto, A., E-mail: daphne3h-aya@ruri.waseda.jp [Research Institute for Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku, Tokyo (Japan); Kataoka, J.; Koide, A.; Sueoka, K.; Iwamoto, Y.; Taya, T. [Research Institute for Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku, Tokyo (Japan); Ohsuka, S. [Central Research Laboratory, Hamamatsu Photonics K.K., 5000 Hirakuchi, Hamakita-ku, Hamamatsu, Shizuoka (Japan)

2017-02-11

The Compton camera, which shows gamma-ray distribution utilizing the kinematics of Compton scattering, is a promising detector capable of imaging across a wide range of energy. In this study, we aim to construct a small-animal molecular imaging system in a wide energy range by using the Compton camera. We developed a compact medical Compton camera based on a Ce-doped Gd{sub 3}Al{sub 2}Ga{sub 3}O{sub 12} (Ce:GAGG) scintillator and multi-pixel photon counter (MPPC). A basic performance confirmed that for 662 keV, the typical energy resolution was 7.4 % (FWHM) and the angular resolution was 4.5° (FWHM). We then used the medical Compton camera to conduct imaging experiments based on a 3-D imaging reconstruction algorithm using the multi-angle data acquisition method. The result confirmed that for a {sup 137}Cs point source at a distance of 4 cm, the image had a spatial resolution of 3.1 mm (FWHM). Furthermore, we succeeded in producing 3-D multi-color image of different simultaneous energy sources ({sup 22}Na [511 keV], {sup 137}Cs [662 keV], and {sup 54}Mn [834 keV]).

Wide-azimuth angle gathers for anisotropic wave-equation migration

KAUST Repository

Sava, Paul C.

2012-10-15

Extended common-image-point gathers (CIP) constructed by wide-azimuth TI wave-equation migration contain all the necessary information for angle decomposition as a function of the reflection and azimuth angles at selected locations in the subsurface. The aperture and azimuth angles are derived from the extended images using analytic relations between the space- and time-lag extensions using information which is already available at the time of migration, i.e. the anisotropic model parameters. CIPs are cheap to compute because they can be distributed in the image at the most relevant positions, as indicated by the geologic structure. If the reflector dip is known at the CIP locations, then the computational cost can be reduced by evaluating only two components of the space-lag vector. The transformation from extended images to angle gathers is a planar Radon transform which depends on the local medium parameters. This transformation allows us to separate all illumination directions for a given experiment, or between different experiments. We do not need to decompose the reconstructed wavefields or to choose the most energetic directions for decomposition. Applications of the method include illumination studies in complex areas where ray-based methods fail, and assuming that the subsurface illumination is sufficiently dense, the study of amplitude variation with aperture and azimuth angles. © 2012 European Association of Geoscientists & Engineers.

Wide-azimuth angle gathers for anisotropic wave-equation migration

KAUST Repository

Sava, Paul C.; Alkhalifah, Tariq Ali

2012-01-01

Extended common-image-point gathers (CIP) constructed by wide-azimuth TI wave-equation migration contain all the necessary information for angle decomposition as a function of the reflection and azimuth angles at selected locations in the subsurface. The aperture and azimuth angles are derived from the extended images using analytic relations between the space- and time-lag extensions using information which is already available at the time of migration, i.e. the anisotropic model parameters. CIPs are cheap to compute because they can be distributed in the image at the most relevant positions, as indicated by the geologic structure. If the reflector dip is known at the CIP locations, then the computational cost can be reduced by evaluating only two components of the space-lag vector. The transformation from extended images to angle gathers is a planar Radon transform which depends on the local medium parameters. This transformation allows us to separate all illumination directions for a given experiment, or between different experiments. We do not need to decompose the reconstructed wavefields or to choose the most energetic directions for decomposition. Applications of the method include illumination studies in complex areas where ray-based methods fail, and assuming that the subsurface illumination is sufficiently dense, the study of amplitude variation with aperture and azimuth angles. © 2012 European Association of Geoscientists & Engineers.

Pore-scale Simulation and Imaging of Multi-phase Flow and Transport in Porous Media (Invited)

Science.gov (United States)

Crawshaw, J.; Welch, N.; Daher, I.; Yang, J.; Shah, S.; Grey, F.; Boek, E.

2013-12-01

We combine multi-scale imaging and computer simulation of multi-phase flow and reactive transport in rock samples to enhance our fundamental understanding of long term CO2 storage in rock formations. The imaging techniques include Confocal Laser Scanning Microscopy (CLSM), micro-CT and medical CT scanning, with spatial resolutions ranging from sub-micron to mm respectively. First, we report a new sample preparation technique to study micro-porosity in carbonates using CLSM in 3 dimensions. Second, we use micro-CT scanning to generate high resolution 3D pore space images of carbonate and cap rock samples. In addition, we employ micro-CT to image the processes of evaporation in fractures and cap rock degradation due to exposure to CO2 flow. Third, we use medical CT scanning to image spontaneous imbibition in carbonate rock samples. Our imaging studies are complemented by computer simulations of multi-phase flow and transport, using the 3D pore space images obtained from the scanning experiments. We have developed a massively parallel lattice-Boltzmann (LB) code to calculate the single phase flow field in these pore space images. The resulting flow fields are then used to calculate hydrodynamic dispersion using a novel scheme to predict probability distributions for molecular displacements using the LB method and a streamline algorithm, modified for optimal solid boundary conditions. We calculate solute transport on pore-space images of rock cores with increasing degree of heterogeneity: a bead pack, Bentheimer sandstone and Portland carbonate. We observe that for homogeneous rock samples, such as bead packs, the displacement distribution remains Gaussian with time increasing. In the more heterogeneous rocks, on the other hand, the displacement distribution develops a stagnant part. We observe that the fraction of trapped solute increases from the beadpack (0 %) to Bentheimer sandstone (1.5 %) to Portland carbonate (8.1 %), in excellent agreement with PFG

Closed-form solution for the Wigner phase-space distribution function for diffuse reflection and small-angle scattering in a random medium.

Science.gov (United States)

Yura, H T; Thrane, L; Andersen, P E

2000-12-01

Within the paraxial approximation, a closed-form solution for the Wigner phase-space distribution function is derived for diffuse reflection and small-angle scattering in a random medium. This solution is based on the extended Huygens-Fresnel principle for the optical field, which is widely used in studies of wave propagation through random media. The results are general in that they apply to both an arbitrary small-angle volume scattering function, and arbitrary (real) ABCD optical systems. Furthermore, they are valid in both the single- and multiple-scattering regimes. Some general features of the Wigner phase-space distribution function are discussed, and analytic results are obtained for various types of scattering functions in the asymptotic limit s > 1, where s is the optical depth. In particular, explicit results are presented for optical coherence tomography (OCT) systems. On this basis, a novel way of creating OCT images based on measurements of the momentum width of the Wigner phase-space distribution is suggested, and the advantage over conventional OCT images is discussed. Because all previous published studies regarding the Wigner function are carried out in the transmission geometry, it is important to note that the extended Huygens-Fresnel principle and the ABCD matrix formalism may be used successfully to describe this geometry (within the paraxial approximation). Therefore for completeness we present in an appendix the general closed-form solution for the Wigner phase-space distribution function in ABCD paraxial optical systems for direct propagation through random media, and in a second appendix absorption effects are included.

Efficient Mosaicking of Spitzer Space Telescope Images

Science.gov (United States)

Jacob, Joseph; Makovoz, David; Eisenhardt, Peter

2007-01-01

A parallel version of the MOPEX software, which generates mosaics of infrared astronomical images acquired by the Spitzer Space Telescope, extends the capabilities of the prior serial version. In the parallel version, both the input image space and the output mosaic space are divided among the available parallel processors. This is the only software that performs the point-source detection and the rejection of spurious imaging effects of cosmic rays required by Spitzer scientists. This software includes components that implement outlier-detection algorithms that can be fine-tuned for a particular set of image data by use of a number of adjustable parameters. This software has been used to construct a mosaic of the Spitzer Infrared Array Camera Shallow Survey, which comprises more than 17,000 exposures in four wavelength bands from 3.6 to 8 m and spans a solid angle of about 9 square degrees. When this software was executed on 32 nodes of the 1,024-processor Cosmos cluster computer at NASA s Jet Propulsion Laboratory, a speedup of 8.3 was achieved over the serial version of MOPEX. The performance is expected to improve dramatically once a true parallel file system is installed on Cosmos.

Contrast-enhanced CISS imaging of cerebellopontine angle tumors

Energy Technology Data Exchange (ETDEWEB)

Tozaki, Mitsuhiro; Toyoda, Keiko; Hata, Yuichi; Fukuda, Yasushi; Fukuda, Kunihiko [Jikei Univ., Tokyo (Japan). School of Medicine; Katano, Shuichi

1999-10-01

Our purpose of this study was to evaluate the clinical usefulness of contrast-enhanced CISS-3DFT MR imaging for the diagnosis of CP angle tumors. CISS-3DFT MR imaging is expected for screening procedure of acoustic schwannoma because of excellent spatial resolution. Recently, we discovered contrast enhancement effect on CISS sequence in spite of heavily T{sub 2}-weighted images. Fourteen patients with CP angle tumors were performed on a 1.0 T MR unit. Transaxial CISS-3DFT MRI was obtained both before and after intravenous injections of Gd-DTPA. Multiplanar reconstructions (MPRs) were performed in all cases. Contrast enhancement effect of CP angle tumors, and the relationship between tumors and the adjacent cranial nerves were evaluated. Contrast enhancement effect of the tumors was present in all cases in spite of heavily T{sub 2}-weighted images of CISS sequences. In the internal auditory canal, relationship between the tumors and the cranial nerves was demonstrated in 6 cases (6/9). In the cerebellopontine cistern, all cases were demonstrated (11/11). Contrast-enhanced CISS-3DFT MR imaging with a good contrast resolution and an excellent spatial resolution is useful for the diagnosis of CP angle tumors. (author)

Angled oblique sagittal MR imaging of rotator cuff tears: comparison with standard oblique sagittal images

International Nuclear Information System (INIS)

Tuite, M.J.; Asinger, D.; Orwin, J.F.

2001-01-01

Objective. To compare the accuracy for diagnosing rotator cuff tears of oblique coronal images supplemented with standard oblique sagittal images versus thinner-section angled oblique sagittal images.Design and patients. The study included 75 consecutive patients who had a shoulder MR scan followed by arthroscopy. MR images included oblique coronal, oblique sagittal (4 mm thick, 1 mm interslice gap), and angled oblique sagittal (3 mm/0.2 mm) images perpendicular to the lateral cuff. A musculoskeletal staff radiologist and fellow separately evaluated the cuff for tears on the oblique coronal images supplemented with either the oblique sagittal or the angled sagittal images.Results. For distinguishing a cuff tear from no tear, the staff radiologist had an accuracy of 0.76 (95% confidence interval: 0.67, 0.85) with the standard sagittal set, and 0.88 (0.80, 0.95) with the angled set (P=0.04). There was a nonsignificant improvement in accuracy for the fellow, calculated as 0.73 (0.63, 0.83) on the standard sagittal set and 0.76 (0.67, 0.85) on the angled set. Both readers also improved their diagnostic accuracy for partial-thickness tears with the angled set, although the improvement was statistically significant only for the staff radiologist.Conclusion. There is a slight improvement in accuracy for diagnosing rotator cuff tears, particularly partial-thickness tears, for the more experienced radiologist using thinner-section angled oblique sagittal images. These images may be useful as a supplemental sequence in patients where it is important to identify partial-thickness tears accurately. (orig.)

Angled oblique sagittal MR imaging of rotator cuff tears: comparison with standard oblique sagittal images

Energy Technology Data Exchange (ETDEWEB)

Tuite, M J; Asinger, D; Orwin, J F [Dept. of Radiology, Univ. of Wisconsin Hospital and Clinics, Madison, WI (United States)

2001-05-01

Objective. To compare the accuracy for diagnosing rotator cuff tears of oblique coronal images supplemented with standard oblique sagittal images versus thinner-section angled oblique sagittal images.Design and patients. The study included 75 consecutive patients who had a shoulder MR scan followed by arthroscopy. MR images included oblique coronal, oblique sagittal (4 mm thick, 1 mm interslice gap), and angled oblique sagittal (3 mm/0.2 mm) images perpendicular to the lateral cuff. A musculoskeletal staff radiologist and fellow separately evaluated the cuff for tears on the oblique coronal images supplemented with either the oblique sagittal or the angled sagittal images.Results. For distinguishing a cuff tear from no tear, the staff radiologist had an accuracy of 0.76 (95% confidence interval: 0.67, 0.85) with the standard sagittal set, and 0.88 (0.80, 0.95) with the angled set (P=0.04). There was a nonsignificant improvement in accuracy for the fellow, calculated as 0.73 (0.63, 0.83) on the standard sagittal set and 0.76 (0.67, 0.85) on the angled set. Both readers also improved their diagnostic accuracy for partial-thickness tears with the angled set, although the improvement was statistically significant only for the staff radiologist.Conclusion. There is a slight improvement in accuracy for diagnosing rotator cuff tears, particularly partial-thickness tears, for the more experienced radiologist using thinner-section angled oblique sagittal images. These images may be useful as a supplemental sequence in patients where it is important to identify partial-thickness tears accurately. (orig.)

AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES

Directory of Open Access Journals (Sweden)

F. Alidoost

2015-12-01

Full Text Available Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

A 2D multi-term time and space fractional Bloch-Torrey model based on bilinear rectangular finite elements

Science.gov (United States)

Qin, Shanlin; Liu, Fawang; Turner, Ian W.

2018-03-01

The consideration of diffusion processes in magnetic resonance imaging (MRI) signal attenuation is classically described by the Bloch-Torrey equation. However, many recent works highlight the distinct deviation in MRI signal decay due to anomalous diffusion, which motivates the fractional order generalization of the Bloch-Torrey equation. In this work, we study the two-dimensional multi-term time and space fractional diffusion equation generalized from the time and space fractional Bloch-Torrey equation. By using the Galerkin finite element method with a structured mesh consisting of rectangular elements to discretize in space and the L1 approximation of the Caputo fractional derivative in time, a fully discrete numerical scheme is derived. A rigorous analysis of stability and error estimation is provided. Numerical experiments in the square and L-shaped domains are performed to give an insight into the efficiency and reliability of our method. Then the scheme is applied to solve the multi-term time and space fractional Bloch-Torrey equation, which shows that the extra time derivative terms impact the relaxation process.

Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

L. DJEROU,

2012-01-01

Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

Angle-resolved imaging of single-crystal materials with MeV helium ions

Energy Technology Data Exchange (ETDEWEB)

Strathman, M D; Baumann, S [Charles Evans and Associates, Redwood City, CA (United States)

1992-02-01

The simplest form of angle-resolved mapping for single-crystal materials is the creation of a channeling angular scan. Several laboratories have expanded this simple procedure to include mapping as a function of two independent tilts. These angle-resolved images are particularly suited to the assessment of crystal parameters including disorder, lattice location of impurities, and lattice stress. This paper will describe the use of the Charles Evans and Associates RBS-400 scattering chamber for acquisition, display, and analysis of angle-resolved images obtained from backscattered helium ions. Typical data acquisition times are 20 min for a {+-}2deg X-Y tilt scan with 2500 pixels (8/100deg resolution), and 10 nC per pixel. In addition, we will present a method for automatically aligning crystals for channeling measurements based on this imaging technology. (orig.).

Angle-resolved imaging of single-crystal materials with MeV helium ions

International Nuclear Information System (INIS)

Strathman, M.D.; Baumann, S.

1992-01-01

The simplest form of angle-resolved mapping for single-crystal materials is the creation of a channeling angular scan. Several laboratories have expanded this simple procedure to include mapping as a function of two independent tilts. These angle-resolved images are particularly suited to the assessment of crystal parameters including disorder, lattice location of impurities, and lattice stress. This paper will describe the use of the Charles Evans and Associates RBS-400 scattering chamber for acquisition, display, and analysis of angle-resolved images obtained from backscattered helium ions. Typical data acquisition times are 20 min for a ±2deg X-Y tilt scan with 2500 pixels (8/100deg resolution), and 10 nC per pixel. In addition, we will present a method for automatically aligning crystals for channeling measurements based on this imaging technology. (orig.)

An efficient multi-resolution GA approach to dental image alignment

Science.gov (United States)

Nassar, Diaa Eldin; Ogirala, Mythili; Adjeroh, Donald; Ammar, Hany

2006-02-01

Automating the process of postmortem identification of individuals using dental records is receiving an increased attention in forensic science, especially with the large volume of victims encountered in mass disasters. Dental radiograph alignment is a key step required for automating the dental identification process. In this paper, we address the problem of dental radiograph alignment using a Multi-Resolution Genetic Algorithm (MR-GA) approach. We use location and orientation information of edge points as features; we assume that affine transformations suffice to restore geometric discrepancies between two images of a tooth, we efficiently search the 6D space of affine parameters using GA progressively across multi-resolution image versions, and we use a Hausdorff distance measure to compute the similarity between a reference tooth and a query tooth subject to a possible alignment transform. Testing results based on 52 teeth-pair images suggest that our algorithm converges to reasonable solutions in more than 85% of the test cases, with most of the error in the remaining cases due to excessive misalignments.

Automatic method for estimation of in situ effective contact angle from X-ray micro tomography images of two-phase flow in porous media.

Science.gov (United States)

Scanziani, Alessio; Singh, Kamaljit; Blunt, Martin J; Guadagnini, Alberto

2017-06-15

Multiphase flow in porous media is strongly influenced by the wettability of the system, which affects the arrangement of the interfaces of different phases residing in the pores. We present a method for estimating the effective contact angle, which quantifies the wettability and controls the local capillary pressure within the complex pore space of natural rock samples, based on the physical constraint of constant curvature of the interface between two fluids. This algorithm is able to extract a large number of measurements from a single rock core, resulting in a characteristic distribution of effective in situ contact angle for the system, that is modelled as a truncated Gaussian probability density distribution. The method is first validated on synthetic images, where the exact angle is known analytically; then the results obtained from measurements within the pore space of rock samples imaged at a resolution of a few microns are compared to direct manual assessment. Finally the method is applied to X-ray micro computed tomography (micro-CT) scans of two Ketton cores after waterflooding, that display water-wet and mixed-wet behaviour. The resulting distribution of in situ contact angles is characterized in terms of a mixture of truncated Gaussian densities. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Making Faces - State-Space Models Applied to Multi-Modal Signal Processing

DEFF Research Database (Denmark)

Lehn-Schiøler, Tue

2005-01-01

The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....

Imaging the Surfaces of Stars from Space

Science.gov (United States)

Carpenter, Kenneth; Rau, Gioia

2018-04-01

Imaging of Stellar Surfacess has been dominated to-date by ground-based observations, but space-based facilities offer tremendous potential for extending the wavelength coverage and ultimately the resolution of such efforts. We review the imaging accomplished so far from space and then talk about exciting future prospects. The earliest attempts from space indirectly produced surface maps via the Doppler Imaging Technique, using UV spectra obtained with the International Ultraviolet Explorer (IUE). Later, the first direct UV images were obtained with the Hubble Space Telescope (HST), of Mira and Betelgeuse, using the Faint Object Camera (FOC). We will show this work and then investigate prospects for IR imaging with the James Webb Space Telescope (JWST). The real potential of space-based Imaging of Stellar Surfacess, however, lies in the future, when large-baseline Fizeau interferometers, such as the UV-optical Stellar Imager (SI) Vision Mission, with a 30-element array and 500m max baseline, are flown. We describe SI and its science goals, which include 0.1 milli-arcsec spectral Imaging of Stellar Surfacess and the probing of internal structure and flows via asteroseismology.

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

Science.gov (United States)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

Science.gov (United States)

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-02-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Six-dimensional real and reciprocal space small-angle X-ray scattering tomography.

Science.gov (United States)

Schaff, Florian; Bech, Martin; Zaslansky, Paul; Jud, Christoph; Liebi, Marianne; Guizar-Sicairos, Manuel; Pfeiffer, Franz

2015-11-19

When used in combination with raster scanning, small-angle X-ray scattering (SAXS) has proven to be a valuable imaging technique of the nanoscale, for example of bone, teeth and brain matter. Although two-dimensional projection imaging has been used to characterize various materials successfully, its three-dimensional extension, SAXS computed tomography, poses substantial challenges, which have yet to be overcome. Previous work using SAXS computed tomography was unable to preserve oriented SAXS signals during reconstruction. Here we present a solution to this problem and obtain a complete SAXS computed tomography, which preserves oriented scattering information. By introducing virtual tomography axes, we take advantage of the two-dimensional SAXS information recorded on an area detector and use it to reconstruct the full three-dimensional scattering distribution in reciprocal space for each voxel of the three-dimensional object in real space. The presented method could be of interest for a combined six-dimensional real and reciprocal space characterization of mesoscopic materials with hierarchically structured features with length scales ranging from a few nanometres to a few millimetres--for example, biomaterials such as bone or teeth, or functional materials such as fuel-cell or battery components.

Image reconstruction from limited angle Compton camera data

International Nuclear Information System (INIS)

Tomitani, T.; Hirasawa, M.

2002-01-01

The Compton camera is used for imaging the distributions of γ ray direction in a γ ray telescope for astrophysics and for imaging radioisotope distributions in nuclear medicine without the need for collimators. The integration of γ rays on a cone is measured with the camera, so that some sort of inversion method is needed. Parra found an analytical inversion algorithm based on spherical harmonics expansion of projection data. His algorithm is applicable to the full set of projection data. In this paper, six possible reconstruction algorithms that allow image reconstruction from projections with a finite range of scattering angles are investigated. Four algorithms have instability problems and two others are practical. However, the variance of the reconstructed image diverges in these two cases, so that window functions are introduced with which the variance becomes finite at a cost of spatial resolution. These two algorithms are compared in terms of variance. The algorithm based on the inversion of the summed back-projection is superior to the algorithm based on the inversion of the summed projection. (author)

UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

Science.gov (United States)

Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

2015-06-01

Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

A Learning State-Space Model for Image Retrieval

Directory of Open Access Journals (Sweden)

Lee Greg C

2007-01-01

Full Text Available This paper proposes an approach based on a state-space model for learning the user concepts in image retrieval. We first design a scheme of region-based image representation based on concept units, which are integrated with different types of feature spaces and with different region scales of image segmentation. The design of the concept units aims at describing similar characteristics at a certain perspective among relevant images. We present the details of our proposed approach based on a state-space model for interactive image retrieval, including likelihood and transition models, and we also describe some experiments that show the efficacy of our proposed model. This work demonstrates the feasibility of using a state-space model to estimate the user intuition in image retrieval.

Multi-dimensional imaging

CERN Document Server

Javidi, Bahram; Andres, Pedro

2014-01-01

Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and

kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

Directory of Open Access Journals (Sweden)

Yang Bai

2018-03-01

Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.

Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

Directory of Open Access Journals (Sweden)

ZHAI Weixin

2016-12-01

Full Text Available Widely applied location aware devices, including mobile phones and GPS receivers, have provided great convenience for collecting large volume individuals' geographical information. The researches on the human's society behavior space has attracts an increasingly number of researchers. In our research, based on location-based Flickr data From 2004 to May, 2014 in China, we choose five levels of spatial grids to form the multi-scale frame for investigate the correlation between the scale and the geo-spatial cognition on human's social activity space. The HT-index is selected as the fractal inspired by Alexander to estimate the maturity of the society activity on different scales. The results indicate that that the scale characteristics are related to the spatial cognition to a certain extent. It is favorable to use the spatial grid as a tool to control scales for geo-spatial cognition on human's social activity space.

Keyhole imaging method for dynamic objects behind the occlusion area

Science.gov (United States)

Hao, Conghui; Chen, Xi; Dong, Liquan; Zhao, Yuejin; Liu, Ming; Kong, Lingqin; Hui, Mei; Liu, Xiaohua; Wu, Hong

2018-01-01

A method of keyhole imaging based on camera array is realized to obtain the video image behind a keyhole in shielded space at a relatively long distance. We get the multi-angle video images by using a 2×2 CCD camera array to take the images behind the keyhole in four directions. The multi-angle video images are saved in the form of frame sequences. This paper presents a method of video frame alignment. In order to remove the non-target area outside the aperture, we use the canny operator and morphological method to realize the edge detection of images and fill the images. The image stitching of four images is accomplished on the basis of the image stitching algorithm of two images. In the image stitching algorithm of two images, the SIFT method is adopted to accomplish the initial matching of images, and then the RANSAC algorithm is applied to eliminate the wrong matching points and to obtain a homography matrix. A method of optimizing transformation matrix is proposed in this paper. Finally, the video image with larger field of view behind the keyhole can be synthesized with image frame sequence in which every single frame is stitched. The results show that the screen of the video is clear and natural, the brightness transition is smooth. There is no obvious artificial stitching marks in the video, and it can be applied in different engineering environment .

Batman flies: a compact spectro-imager for space observation

Science.gov (United States)

Zamkotsian, Frederic; Ilbert, Olivier; Zoubian, Julien; Delsanti, Audrey; Boissier, Samuel; Lancon, Ariane

2017-11-01

Multi-object spectroscopy (MOS) is a key technique for large field of view surveys. MOEMS programmable slit masks could be next-generation devices for selecting objects in future infrared astronomical instrumentation for space telescopes. MOS is used extensively to investigate astronomical objects by optimizing the Signal-to-Noise Ratio (SNR): high precision spectra are obtained and the problem of spectral confusion and background level occurring in slitless spectroscopy is cancelled. Fainter limiting fluxes are reached and the scientific return is maximized both in cosmology and in legacy science. Major telescopes around the world are equipped with MOS in order to simultaneously record several hundred spectra in a single observation run. Next generation MOS for space like the Near Infrared Multi-Object Spectrograph (NIRSpec) for the James Webb Space Telescope (JWST) require a programmable multi-slit mask. Conventional masks or complex fiber-optics-based mechanisms are not attractive for space. The programmable multi-slit mask requires remote control of the multislit configuration in real time. During the early-phase studies of the European Space Agency (ESA) EUCLID mission, a MOS instrument based on a MOEMS device has been assessed. Due to complexity and cost reasons, slitless spectroscopy was chosen for EUCLID, despite a much higher efficiency with slit spectroscopy. A promising possible solution is the use of MOEMS devices such as micromirror arrays (MMA) [1,2,3] or micro-shutter arrays (MSA) [4]. MMAs are designed for generating reflecting slits, while MSAs generate transmissive slits. In Europe an effort is currently under way to develop single-crystalline silicon micromirror arrays for future generation infrared multi-object spectroscopy (collaboration LAM / EPFL-CSEM) [5,6]. By placing the programmable slit mask in the focal plane of the telescope, the light from selected objects is directed toward the spectrograph, while the light from other objects and

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

Science.gov (United States)

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

Science.gov (United States)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement

Directory of Open Access Journals (Sweden)

Hakan Kartal

2018-06-01

Full Text Available Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

Simulation analysis of impulse characteristics of space debris irradiated by multi-pulse laser

Science.gov (United States)

Lin, Zhengguo; Jin, Xing; Chang, Hao; You, Xiangyu

2018-02-01

Cleaning space debris with laser is a hot topic in the field of space security research. Impulse characteristics are the basis of cleaning space debris with laser. In order to study the impulse characteristics of rotating irregular space debris irradiated by multi-pulse laser, the impulse calculation method of rotating space debris irradiated by multi-pulse laser is established based on the area matrix method. The calculation method of impulse and impulsive moment under multi-pulse irradiation is given. The calculation process of total impulse under multi-pulse irradiation is analyzed. With a typical non-planar space debris (cube) as example, the impulse characteristics of space debris irradiated by multi-pulse laser are simulated and analyzed. The effects of initial angular velocity, spot size and pulse frequency on impulse characteristics are investigated.

Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

Azimuth and angle gathers from wave equation imaging in VTI media

KAUST Repository

Alkhalifah, Tariq Ali; Fomel, Sergey B.

2009-01-01

by the need to properly estimate multiple anisotropic parameters for a proper representation of the medium. We extract angle gathers for each downward-continuation step from converting offset-space-frequency planes into angle-space planes simultaneously

High frame rate multi-resonance imaging refractometry with distributed feedback dye laser sensor

DEFF Research Database (Denmark)

Vannahme, Christoph; Dufva, Martin; Kristensen, Anders

2015-01-01

imaging refractometry without moving parts is presented. DFB dye lasers are low-cost and highly sensitive refractive index sensors. The unique multi-wavelength DFB laser structure presented here comprises several areas with different grating periods. Imaging in two dimensions of space is enabled...... by analyzing laser light from all areas in parallel with an imaging spectrometer. With this multi-resonance imaging refractometry method, the spatial position in one direction is identified from the horizontal, i.e., spectral position of the multiple laser lines which is obtained from the spectrometer charged...

Imaging findings and significance of deep neck space infection

International Nuclear Information System (INIS)

Zhuang Qixin; Gu Yifeng; Du Lianjun; Zhu Lili; Pan Yuping; Li Minghua; Yang Shixun; Shang Kezhong; Yin Shankai

2004-01-01

Objective: To study the imaging appearance of deep neck space cellulitis and abscess and to evaluate the diagnostic criteria of deep neck space infection. Methods: CT and MRI findings of 28 cases with deep neck space infection proved by clinical manifestation and pathology were analyzed, including 11 cases of retropharyngeal space, 5 cases of parapharyngeal space infection, 4 cases of masticator space infection, and 8 cases of multi-space infection. Results: CT and MRI could display the swelling of the soft tissues and displacement, reduction, or disappearance of lipoid space in the cellulitis. In inflammatory tissues, MRI imaging demonstrated hypointense or isointense signal on T 1 WI, and hyperintense signal changes on T 2 WI. In abscess, CT could display hypodensity in the center and boundary enhancement of the abscess. MRI could display obvious hyperintense signal on T 2 WI and boundary enhancement. Conclusion: CT and MRI could provide useful information for deep neck space cellulitis and abscess

Importance-truncated shell model for multi-shell valence spaces

Energy Technology Data Exchange (ETDEWEB)

Stumpf, Christina; Vobig, Klaus; Roth, Robert [Institut fuer Kernphysik, TU Darmstadt (Germany)

2016-07-01

The valence-space shell model is one of the work horses in nuclear structure theory. In traditional applications, shell-model calculations are carried out using effective interactions constructed in a phenomenological framework for rather small valence spaces, typically spanned by one major shell. We improve on this traditional approach addressing two main aspects. First, we use new effective interactions derived in an ab initio approach and, thus, establish a connection to the underlying nuclear interaction providing access to single- and multi-shell valence spaces. Second, we extend the shell model to larger valence spaces by applying an importance-truncation scheme based on a perturbative importance measure. In this way, we reduce the model space to the relevant basis states for the description of a few target eigenstates and solve the eigenvalue problem in this physics-driven truncated model space. In particular multi-shell valence spaces are not tractable otherwise. We combine the importance-truncated shell model with refined extrapolation schemes to approximately recover the exact result. We present first results obtained in the importance-truncated shell model with the newly derived ab initio effective interactions for multi-shell valence spaces, e.g., the sdpf shell.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

Directory of Open Access Journals (Sweden)

Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

Science.gov (United States)

Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Multi-focus Image Fusion Using Epifluorescence Microscopy for Robust Vascular Segmentation

OpenAIRE

Pelapur, Rengarajan; Prasath, Surya; Palaniappan, Kannappan

2014-01-01

We are building a computerized image analysis system for Dura Mater vascular network from fluorescence microscopy images. We propose a system that couples a multi-focus image fusion module with a robust adaptive filtering based segmentation. The robust adaptive filtering scheme handles noise without destroying small structures, and the multi focal image fusion considerably improves the overall segmentation quality by integrating information from multiple images. Based on the segmenta...

Angle gathers in wave-equation imaging for transversely isotropic media

KAUST Repository

Alkhalifah, Tariq Ali; Fomel, Sergey B.

2010-01-01

In recent years, wave-equation imaged data are often presented in common-image angle-domain gathers as a decomposition in the scattering angle at the reflector, which provide a natural access to analysing migration velocities and amplitudes. In the case of anisotropic media, the importance of angle gathers is enhanced by the need to properly estimate multiple anisotropic parameters for a proper representation of the medium. We extract angle gathers for each downward-continuation step from converting offset-frequency planes into angle-frequency planes simultaneously with applying the imaging condition in a transversely isotropic with a vertical symmetry axis (VTI) medium. The analytic equations, though cumbersome, are exact within the framework of the acoustic approximation. They are also easily programmable and show that angle gather mapping in the case of anisotropic media differs from its isotropic counterpart, with the difference depending mainly on the strength of anisotropy. Synthetic examples demonstrate the importance of including anisotropy in the angle gather generation as mapping of the energy is negatively altered otherwise. In the case of a titled axis of symmetry (TTI), the same VTI formulation is applicable but requires a rotation of the wavenumbers. © 2010 European Association of Geoscientists & Engineers.

Angle gathers in wave-equation imaging for transversely isotropic media

KAUST Repository

Alkhalifah, Tariq Ali

2010-11-12

In recent years, wave-equation imaged data are often presented in common-image angle-domain gathers as a decomposition in the scattering angle at the reflector, which provide a natural access to analysing migration velocities and amplitudes. In the case of anisotropic media, the importance of angle gathers is enhanced by the need to properly estimate multiple anisotropic parameters for a proper representation of the medium. We extract angle gathers for each downward-continuation step from converting offset-frequency planes into angle-frequency planes simultaneously with applying the imaging condition in a transversely isotropic with a vertical symmetry axis (VTI) medium. The analytic equations, though cumbersome, are exact within the framework of the acoustic approximation. They are also easily programmable and show that angle gather mapping in the case of anisotropic media differs from its isotropic counterpart, with the difference depending mainly on the strength of anisotropy. Synthetic examples demonstrate the importance of including anisotropy in the angle gather generation as mapping of the energy is negatively altered otherwise. In the case of a titled axis of symmetry (TTI), the same VTI formulation is applicable but requires a rotation of the wavenumbers. © 2010 European Association of Geoscientists & Engineers.

Mid-space-independent deformable image registration.

Science.gov (United States)

Aganj, Iman; Iglesias, Juan Eugenio; Reuter, Martin; Sabuncu, Mert Rory; Fischl, Bruce

2017-05-15

Aligning images in a mid-space is a common approach to ensuring that deformable image registration is symmetric - that it does not depend on the arbitrary ordering of the input images. The results are, however, generally dependent on the mathematical definition of the mid-space. In particular, the set of possible solutions is typically restricted by the constraints that are enforced on the transformations to prevent the mid-space from drifting too far from the native image spaces. The use of an implicit atlas has been proposed as an approach to mid-space image registration. In this work, we show that when the atlas is aligned to each image in the native image space, the data term of implicit-atlas-based deformable registration is inherently independent of the mid-space. In addition, we show that the regularization term can be reformulated independently of the mid-space as well. We derive a new symmetric cost function that only depends on the transformation morphing the images to each other, rather than to the atlas. This eliminates the need for anti-drift constraints, thereby expanding the space of allowable deformations. We provide an implementation scheme for the proposed framework, and validate it through diffeomorphic registration experiments on brain magnetic resonance images. Copyright © 2017 Elsevier Inc. All rights reserved.

Defect inspection in hot slab surface: multi-source CCD imaging based fuzzy-rough sets method

Science.gov (United States)

Zhao, Liming; Zhang, Yi; Xu, Xiaodong; Xiao, Hong; Huang, Chao

2016-09-01

To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough sets method is proposed for hot slab surface quality assessment. The applicability of the presented method and the devised system are mainly tied to the surface quality inspection for strip, billet and slab surface etcetera. In this work we take into account the complementary advantages in two common machine vision (MV) systems(line array CCD traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging)), and through establishing the model of fuzzy-rough sets in the detection system the seeds for relative fuzzy connectedness(RFC) delineation for ROI can placed adaptively, which introduces the upper and lower approximation sets for RIO definition, and by which the boundary region can be delineated by RFC region competitive classification mechanism. For the first time, a Multi-source CCD imaging based fuzzy-rough sets strategy is attempted for CC-slab surface defects inspection that allows an automatic way of AI algorithms and powerful ROI delineation strategies to be applied to the MV inspection field.

PLANE MATCHING WITH OBJECT-SPACE SEARCHING USING INDEPENDENTLY RECTIFIED IMAGES

Directory of Open Access Journals (Sweden)

H. Takeda

2012-07-01

Full Text Available In recent years, the social situation in cities has changed significantly such as redevelopment due to the massive earthquake and large-scale urban development. For example, numerical simulations can be used to study this phenomenon. Such simulations require the construction of high-definition three-dimensional city models that accurately reflect the real world. Progress in sensor technology allows us to easily obtain multi-view images. However, the existing multi-image matching techniques are inadequate. In this paper, we propose a new technique for multi-image matching. Since the existing method of feature searching is complicated, we have developed a rectification method that can be processed independently for each image does not depend on the stereo-pair. The object-space searching method that produces mismatches due to the occlusion or distortion of wall textures on images is the focus of our study. Our proposed technique can also match the building wall surface. The proposed technique has several advantages, and its usefulness is clarified through an experiment using actual images.

Multi-focus image fusion based on area-based standard deviation in dual tree contourlet transform domain

Science.gov (United States)

Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin

2018-04-01

Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.

WE-DE-BRA-01: SCIENCE COUNCIL JUNIOR INVESTIGATOR COMPETITION WINNER: Acceleration of a Limited-Angle Intrafraction Verification (LIVE) System Using Adaptive Prior Knowledge Based Image Estimation

International Nuclear Information System (INIS)

Zhang, Y; Yin, F; Ren, L; Zhang, Y

2016-01-01

Purpose: To develop an adaptive prior knowledge based image estimation method to reduce the scan angle needed in the LIVE system to reconstruct 4D-CBCT for intrafraction verification. Methods: The LIVE system has been previously proposed to reconstructs 4D volumetric images on-the-fly during arc treatment for intrafraction target verification and dose calculation. This system uses limited-angle beam’s eye view (BEV) MV cine images acquired from the treatment beam together with the orthogonally acquired limited-angle kV projections to reconstruct 4D-CBCT images for target verification during treatment. In this study, we developed an adaptive constrained free-form deformation reconstruction technique in LIVE to further reduce the scanning angle needed to reconstruct the CBCT images. This technique uses free form deformation with energy minimization to deform prior images to estimate 4D-CBCT based on projections acquired in limited angle (orthogonal 6°) during the treatment. Note that the prior images are adaptively updated using the latest CBCT images reconstructed by LIVE during treatment to utilize the continuity of patient motion.The 4D digital extended-cardiac-torso (XCAT) phantom was used to evaluate the efficacy of this technique with LIVE system. A lung patient was simulated with different scenario, including baseline drifts, amplitude change and phase shift. Limited-angle orthogonal kV and beam’s eye view (BEV) MV projections were generated for each scenario. The CBCT reconstructed by these projections were compared with the ground-truth generated in XCAT.Volume-percentage-difference (VPD) and center-of-mass-shift (COMS) were calculated between the reconstructed and the ground-truth tumors to evaluate the reconstruction accuracy. Results: Using orthogonal-view of 6° kV and BEV- MV projections, the VPD/COMS values were 12.7±4.0%/0.7±0.5 mm, 13.0±5.1%/0.8±0.5 mm, and 11.4±5.4%/0.5±0.3 mm for the three scenarios, respectively. Conclusion: The

WE-DE-BRA-01: SCIENCE COUNCIL JUNIOR INVESTIGATOR COMPETITION WINNER: Acceleration of a Limited-Angle Intrafraction Verification (LIVE) System Using Adaptive Prior Knowledge Based Image Estimation

Energy Technology Data Exchange (ETDEWEB)

Zhang, Y; Yin, F; Ren, L [Duke University Medical Center, Durham, NC (United States); Zhang, Y [UT Southwestern Medical Ctr at Dallas, Dallas, TX (United States)

2016-06-15

Purpose: To develop an adaptive prior knowledge based image estimation method to reduce the scan angle needed in the LIVE system to reconstruct 4D-CBCT for intrafraction verification. Methods: The LIVE system has been previously proposed to reconstructs 4D volumetric images on-the-fly during arc treatment for intrafraction target verification and dose calculation. This system uses limited-angle beam’s eye view (BEV) MV cine images acquired from the treatment beam together with the orthogonally acquired limited-angle kV projections to reconstruct 4D-CBCT images for target verification during treatment. In this study, we developed an adaptive constrained free-form deformation reconstruction technique in LIVE to further reduce the scanning angle needed to reconstruct the CBCT images. This technique uses free form deformation with energy minimization to deform prior images to estimate 4D-CBCT based on projections acquired in limited angle (orthogonal 6°) during the treatment. Note that the prior images are adaptively updated using the latest CBCT images reconstructed by LIVE during treatment to utilize the continuity of patient motion.The 4D digital extended-cardiac-torso (XCAT) phantom was used to evaluate the efficacy of this technique with LIVE system. A lung patient was simulated with different scenario, including baseline drifts, amplitude change and phase shift. Limited-angle orthogonal kV and beam’s eye view (BEV) MV projections were generated for each scenario. The CBCT reconstructed by these projections were compared with the ground-truth generated in XCAT.Volume-percentage-difference (VPD) and center-of-mass-shift (COMS) were calculated between the reconstructed and the ground-truth tumors to evaluate the reconstruction accuracy. Results: Using orthogonal-view of 6° kV and BEV- MV projections, the VPD/COMS values were 12.7±4.0%/0.7±0.5 mm, 13.0±5.1%/0.8±0.5 mm, and 11.4±5.4%/0.5±0.3 mm for the three scenarios, respectively. Conclusion: The

Sparsity-based multi-height phase recovery in holographic microscopy

KAUST Repository

Rivenson, Yair

2016-11-30

High-resolution imaging of densely connected samples such as pathology slides using digital in-line holographic microscopy requires the acquisition of several holograms, e.g., at >6–8 different sample-to-sensor distances, to achieve robust phase recovery and coherent imaging of specimen. Reducing the number of these holographic measurements would normally result in reconstruction artifacts and loss of image quality, which would be detrimental especially for biomedical and diagnostics-related applications. Inspired by the fact that most natural images are sparse in some domain, here we introduce a sparsity-based phase reconstruction technique implemented in wavelet domain to achieve at least 2-fold reduction in the number of holographic measurements for coherent imaging of densely connected samples with minimal impact on the reconstructed image quality, quantified using a structural similarity index. We demonstrated the success of this approach by imaging Papanicolaou smears and breast cancer tissue slides over a large field-of-view of ~20 mm2 using 2 in-line holograms that are acquired at different sample-to-sensor distances and processed using sparsity-based multi-height phase recovery. This new phase recovery approach that makes use of sparsity can also be extended to other coherent imaging schemes, involving e.g., multiple illumination angles or wavelengths to increase the throughput and speed of coherent imaging.

Sparsity-based multi-height phase recovery in holographic microscopy

Science.gov (United States)

Rivenson, Yair; Wu, Yichen; Wang, Hongda; Zhang, Yibo; Feizi, Alborz; Ozcan, Aydogan

2016-11-01

High-resolution imaging of densely connected samples such as pathology slides using digital in-line holographic microscopy requires the acquisition of several holograms, e.g., at >6-8 different sample-to-sensor distances, to achieve robust phase recovery and coherent imaging of specimen. Reducing the number of these holographic measurements would normally result in reconstruction artifacts and loss of image quality, which would be detrimental especially for biomedical and diagnostics-related applications. Inspired by the fact that most natural images are sparse in some domain, here we introduce a sparsity-based phase reconstruction technique implemented in wavelet domain to achieve at least 2-fold reduction in the number of holographic measurements for coherent imaging of densely connected samples with minimal impact on the reconstructed image quality, quantified using a structural similarity index. We demonstrated the success of this approach by imaging Papanicolaou smears and breast cancer tissue slides over a large field-of-view of ~20 mm2 using 2 in-line holograms that are acquired at different sample-to-sensor distances and processed using sparsity-based multi-height phase recovery. This new phase recovery approach that makes use of sparsity can also be extended to other coherent imaging schemes, involving e.g., multiple illumination angles or wavelengths to increase the throughput and speed of coherent imaging.

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

Science.gov (United States)

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Feasibility study of an image slicer for future space application

Science.gov (United States)

Calcines, A.; Ichimoto, K.

2014-08-01

This communication presents the feasibility study of an image slicer for future space missions, especially for the integral field unit (IFU) of the SUVIT (Solar UV-Visible-IR telescope) spectro-polarimeter on board the Japanese-led solar space mission Solar-C as a backup option. The MuSICa (Multi-Slit Image slicer based on collimator-Camera) image slicer concept, originally developed for the European Solar Telescope, has been adapted to the SUVIT requirements. The IFU will reorganizes a 2-D field of view of 10 x 10 arcsec2 into three slits of 0.18 arcsec width by 185.12 arcsec length using flat slicer mirrors of 100 μm width. The layout of MuSICa for Solar-C is telecentric and offers an optical quality limited by diffraction. The entrance for the SUVIT spectro-polarimeter is composed by the three IFU slits and one ordinal long slit to study, using high resolution spectro-polarimetry, the solar atmosphere (Photosphere and Chromosphere) within a spectral range between 520 nm (optionally 280 nm) and 1,100 nm.

Efficient and automatic image reduction framework for space debris detection based on GPU technology

Science.gov (United States)

Diprima, Francesco; Santoni, Fabio; Piergentili, Fabrizio; Fortunato, Vito; Abbattista, Cristoforo; Amoruso, Leonardo

2018-04-01

In the last years, the increasing number of space debris has triggered the need of a distributed monitoring system for the prevention of possible space collisions. Space surveillance based on ground telescope allows the monitoring of the traffic of the Resident Space Objects (RSOs) in the Earth orbit. This space debris surveillance has several applications such as orbit prediction and conjunction assessment. In this paper is proposed an optimized and performance-oriented pipeline for sources extraction intended to the automatic detection of space debris in optical data. The detection method is based on the morphological operations and Hough Transform for lines. Near real-time detection is obtained using General Purpose computing on Graphics Processing Units (GPGPU). The high degree of processing parallelism provided by GPGPU allows to split data analysis over thousands of threads in order to process big datasets with a limited computational time. The implementation has been tested on a large and heterogeneous images data set, containing both imaging satellites from different orbit ranges and multiple observation modes (i.e. sidereal and object tracking). These images were taken during an observation campaign performed from the EQUO (EQUatorial Observatory) observatory settled at the Broglio Space Center (BSC) in Kenya, which is part of the ASI-Sapienza Agreement.

Classification of high-resolution remote sensing images based on multi-scale superposition

Science.gov (United States)

Wang, Jinliang; Gao, Wenjie; Liu, Guangjie

2017-07-01

Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

Co-registration of fluorescence diffuse optical tomography (fDOT) with positron emission tomography (PET) and development of multi-angle fDOT

International Nuclear Information System (INIS)

Tong, X.

2012-01-01

This thesis concerns the image processing of fluorescence diffuse optical tomography (fDOT), following two axes: fDOT image co-registration with PET (positron emission tomography) image and improvement of fDOT image reconstructions using mirrors to collect additional projections. It is presented in two parts:In the first part, an automatic method to co-register the fDOT images with PET images has been developed to correlate all the information from each modality. This co-registration method is based on automatic detection of fiducial markers (FM) present in both modalities. The particularity of this method is the use of optical surface image obtained in fDOT imaging system, which serves to identify the Z position of FM in optical images. We tested this method on a model of mice bearing tumor xenografts of MEN2A cancer cells that mimic a human medullary thyroid carcinoma, after a double injection of radiotracer [ 18 F] 2-fluoro-2-Deoxy-D-glucose (FDG) for PET imaging and optical fluorescent infrared tracer Sentidye. With the accuracy of our method, we can demonstrate that the signal of Sentidye is present both in the tumor and surrounding vessels.The fDOT reconstruction image quality is degraded along the Z axis due to a limited number of projections for reconstruction. In the second part, the work is oriented towards a new method of fDOT image reconstruction with a new multi-angle data acquisition system in placing two mirrors on each side of the animal. This work was conducted in collaboration with the CS Department of University College London (UCL), a partner of the European project FMT-XCT. TOAST software developed by this team was used as source code for the reconstruction algorithm, and was modified to adapt to the concerned problem. After several tests on the adjustment of program parameters, we applied this method on a phantom that simulating the biological tissue and on mice. The results showed an improvement in the reconstructed image of a semi

SU-E-I-71: Quality Assessment of Surrogate Metrics in Multi-Atlas-Based Image Segmentation

International Nuclear Information System (INIS)

Zhao, T; Ruan, D

2015-01-01

Purpose: With the ever-growing data of heterogeneous quality, relevance assessment of atlases becomes increasingly critical for multi-atlas-based image segmentation. However, there is no universally recognized best relevance metric and even a standard to compare amongst candidates remains elusive. This study, for the first time, designs a quantification to assess relevance metrics’ quality, based on a novel perspective of the metric as surrogate for inferring the inaccessible oracle geometric agreement. Methods: We first develop an inference model to relate surrogate metrics in image space to the underlying oracle relevance metric in segmentation label space, with a monotonically non-decreasing function subject to random perturbations. Subsequently, we investigate model parameters to reveal key contributing factors to surrogates’ ability in prognosticating the oracle relevance value, for the specific task of atlas selection. Finally, we design an effective contract-to-noise ratio (eCNR) to quantify surrogates’ quality based on insights from these analyses and empirical observations. Results: The inference model was specialized to a linear function with normally distributed perturbations, with surrogate metric exemplified by several widely-used image similarity metrics, i.e., MSD/NCC/(N)MI. Surrogates’ behaviors in selecting the most relevant atlases were assessed under varying eCNR, showing that surrogates with high eCNR dominated those with low eCNR in retaining the most relevant atlases. In an end-to-end validation, NCC/(N)MI with eCNR of 0.12 compared to MSD with eCNR of 0.10 resulted in statistically better segmentation with mean DSC of about 0.85 and the first and third quartiles of (0.83, 0.89), compared to MSD with mean DSC of 0.84 and the first and third quartiles of (0.81, 0.89). Conclusion: The designed eCNR is capable of characterizing surrogate metrics’ quality in prognosticating the oracle relevance value. It has been demonstrated to be

SU-G-BRA-03: PCA Based Imaging Angle Optimization for 2D Cine MRI Based Radiotherapy Guidance

Energy Technology Data Exchange (ETDEWEB)

Chen, T; Yue, N; Jabbour, S; Zhang, M [Rutgers University, New Brunswick, NJ (United States)

2016-06-15

Purpose: To develop an imaging angle optimization methodology for orthogonal 2D cine MRI based radiotherapy guidance using Principal Component Analysis (PCA) of target motion retrieved from 4DCT. Methods: We retrospectively analyzed 4DCT of 6 patients with lung tumor. A radiation oncologist manually contoured the target volume at the maximal inhalation phase of the respiratory cycle. An object constrained deformable image registration (DIR) method has been developed to track the target motion along the respiration at ten phases. The motion of the center of the target mass has been analyzed using the PCA to find out the principal motion components that were uncorrelated with each other. Two orthogonal image planes for cineMRI have been determined using this method to minimize the through plane motion during MRI based radiotherapy guidance. Results: 3D target respiratory motion for all 6 patients has been efficiently retrieved from 4DCT. In this process, the object constrained DIR demonstrated satisfactory accuracy and efficiency to enable the automatic motion tracking for clinical application. The average motion amplitude in the AP, lateral, and longitudinal directions were 3.6mm (min: 1.6mm, max: 5.6mm), 1.7mm (min: 0.6mm, max: 2.7mm), and 5.6mm (min: 1.8mm, max: 16.1mm), respectively. Based on PCA, the optimal orthogonal imaging planes were determined for cineMRI. The average angular difference between the PCA determined imaging planes and the traditional AP and lateral imaging planes were 47 and 31 degrees, respectively. After optimization, the average amplitude of through plane motion reduced from 3.6mm in AP images to 2.5mm (min:1.3mm, max:3.9mm); and from 1.7mm in lateral images to 0.6mm (min: 0.2mm, max:1.5mm), while the principal in plane motion amplitude increased from 5.6mm to 6.5mm (min: 2.8mm, max: 17mm). Conclusion: DIR and PCA can be used to optimize the orthogonal image planes of cineMRI to minimize the through plane motion during radiotherapy

SU-G-BRA-03: PCA Based Imaging Angle Optimization for 2D Cine MRI Based Radiotherapy Guidance

International Nuclear Information System (INIS)

Chen, T; Yue, N; Jabbour, S; Zhang, M

2016-01-01

Purpose: To develop an imaging angle optimization methodology for orthogonal 2D cine MRI based radiotherapy guidance using Principal Component Analysis (PCA) of target motion retrieved from 4DCT. Methods: We retrospectively analyzed 4DCT of 6 patients with lung tumor. A radiation oncologist manually contoured the target volume at the maximal inhalation phase of the respiratory cycle. An object constrained deformable image registration (DIR) method has been developed to track the target motion along the respiration at ten phases. The motion of the center of the target mass has been analyzed using the PCA to find out the principal motion components that were uncorrelated with each other. Two orthogonal image planes for cineMRI have been determined using this method to minimize the through plane motion during MRI based radiotherapy guidance. Results: 3D target respiratory motion for all 6 patients has been efficiently retrieved from 4DCT. In this process, the object constrained DIR demonstrated satisfactory accuracy and efficiency to enable the automatic motion tracking for clinical application. The average motion amplitude in the AP, lateral, and longitudinal directions were 3.6mm (min: 1.6mm, max: 5.6mm), 1.7mm (min: 0.6mm, max: 2.7mm), and 5.6mm (min: 1.8mm, max: 16.1mm), respectively. Based on PCA, the optimal orthogonal imaging planes were determined for cineMRI. The average angular difference between the PCA determined imaging planes and the traditional AP and lateral imaging planes were 47 and 31 degrees, respectively. After optimization, the average amplitude of through plane motion reduced from 3.6mm in AP images to 2.5mm (min:1.3mm, max:3.9mm); and from 1.7mm in lateral images to 0.6mm (min: 0.2mm, max:1.5mm), while the principal in plane motion amplitude increased from 5.6mm to 6.5mm (min: 2.8mm, max: 17mm). Conclusion: DIR and PCA can be used to optimize the orthogonal image planes of cineMRI to minimize the through plane motion during radiotherapy

TU-AB-202-11: Tumor Segmentation by Fusion of Multi-Tracer PET Images Using Copula Based Statistical Methods

International Nuclear Information System (INIS)

Lapuyade-Lahorgue, J; Ruan, S; Li, H; Vera, P

2016-01-01

Purpose: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. Methods: Non-standardized Gamma distributions are convenient to model intensity distributions in PET. As a serious correlation exists in multi-tracer PET images, we proposed a new fusion method based on copula which is capable to represent dependency between different tracers. The Hidden Markov Field (HMF) model is used to represent spatial relationship between PET image voxels and statistical dynamics of intensities for each modality. Real PET images of five patients with FDG and FMISO are used to evaluate quantitatively and qualitatively our method. A comparison between individual and multi-tracer segmentations was conducted to show advantages of the proposed fusion method. Results: The segmentation results show that fusion with Gaussian copula can receive high Dice coefficient of 0.84 compared to that of 0.54 and 0.3 of monomodal segmentation results based on individual segmentation of FDG and FMISO PET images. In addition, high correlation coefficients (0.75 to 0.91) for the Gaussian copula for all five testing patients indicates the dependency between tumor regions in the multi-tracer PET images. Conclusion: This study shows that using multi-tracer PET imaging can efficiently improve the segmentation of tumor region where hypoxia and glucidic consumption are present at the same time. Introduction of copulas for modeling the dependency between two tracers can simultaneously take into account information from both tracers and deal with two pathological phenomena. Future work will be to consider other families of copula such as spherical and archimedian copulas, and to eliminate partial volume

Image Mosaic Techniques OptimizationUsing Wavelet

Institute of Scientific and Technical Information of China (English)

ZHOUAn-qi; CUILi

2014-01-01

This essay concentrates on two key procedures of image mosaic——image registration and imagefusion.Becauseof the character of geometric transformation invariance of edge points, wecalculate the angle difference of the direction vector ofedge points in different images anddraw an angle difference histogramto adjust the rotationproblem. Through this way, algorithm based on gray information is expandedandcan be used in images withdisplacementand rotation. Inthe term of image fusion, wavelet multi-scale analysis is used to fuse spliced images. In order to choose the best method of imagefusion,weevaluate the results of different methods of image fusion by cross entropy.

Multi-color imaging of magnetic Co/Pt heterostructures

Directory of Open Access Journals (Sweden)

Felix Willems

2017-01-01

Full Text Available We present an element specific and spatially resolved view of magnetic domains in Co/Pt heterostructures in the extreme ultraviolet spectral range. Resonant small-angle scattering and coherent imaging with Fourier-transform holography reveal nanoscale magnetic domain networks via magnetic dichroism of Co at the M2,3 edges as well as via strong dichroic signals at the O2,3 and N6,7 edges of Pt. We demonstrate for the first time simultaneous, two-color coherent imaging at a free-electron laser facility paving the way for a direct real space access to ultrafast magnetization dynamics in complex multicomponent material systems.

EIT image regularization by a new Multi-Objective Simulated Annealing algorithm.

Science.gov (United States)

Castro Martins, Thiago; Sales Guerra Tsuzuki, Marcos

2015-01-01

Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

Variable flip angle excitation for reduced acquisition time magnetic resonance imaging

International Nuclear Information System (INIS)

Mills, T.C.; Ortendahl, D.A.; Hylton, N.M.; Carlson, J.W.; Crooks, L.E.; Kaufman, L.

1987-01-01

This paper describes an MRI technique which can be used to acquire images at short TR values while maintaining the sensitivity to disease found in longer TR images. For spin echo imaging there are three acquisition parameters that can be set in the imaging protocol; TR, the repetition interval; TE, the time of echo and Θ, the excitation flip angle. Standard imaging techniques set Θ to 90 degrees regardless of the TR value. With Θ fixed, imaging systems have been optimized by varying the value for TE and TR with the results in general indicating the need for long TR values. However, if the flip angle is included as a variable acquisition parameter the optimal operating point can be changed. The solution to the Bloch equation shows a functional relationship between the flip angle and the ratio TR/T1. This functionality was first observed by Ernst and Anderson as a method to increase the signal generated in fourier transform magnetic resonance spectroscopy. When TR/T1<1 the optimum flip angle for producing maximum magnetization in the transverse plane is less then 90 degrees. Therefore, by reducing both TR and flip angle it is possible to maintain signal intensity while reducing the time of data acquisition

Multi-pinhole collimator design for small-object imaging with SiliSPECT: a high-resolution SPECT

International Nuclear Information System (INIS)

Shokouhi, S; Peterson, T E; Metzler, S D; Wilson, D W

2009-01-01

We have designed a multi-pinhole collimator for a dual-headed, stationary SPECT system that incorporates high-resolution silicon double-sided strip detectors. The compact camera design of our system enables imaging at source-collimator distances between 20 and 30 mm. Our analytical calculations show that using knife-edge pinholes with small-opening angles or cylindrically shaped pinholes in a focused, multi-pinhole configuration in combination with this camera geometry can generate narrow sensitivity profiles across the field of view that can be useful for imaging small objects at high sensitivity and resolution. The current prototype system uses two collimators each containing 127 cylindrically shaped pinholes that are focused toward a target volume. Our goal is imaging objects such as a mouse brain, which could find potential applications in molecular imaging.

Research on spatial-variant property of bistatic ISAR imaging plane of space target

International Nuclear Information System (INIS)

Guo Bao-Feng; Wang Jun-Ling; Gao Mei-Guo

2015-01-01

The imaging plane of inverse synthetic aperture radar (ISAR) is the projection plane of the target. When taking an image using the range-Doppler theory, the imaging plane may have a spatial-variant property, which causes the change of scatter’s projection position and results in migration through resolution cells. In this study, we focus on the spatial-variant property of the imaging plane of a three-axis-stabilized space target. The innovative contributions are as follows. 1) The target motion model in orbit is provided based on a two-body model. 2) The instantaneous imaging plane is determined by the method of vector analysis. 3) Three Euler angles are introduced to describe the spatial-variant property of the imaging plane, and the image quality is analyzed. The simulation results confirm the analysis of the spatial-variant property. The research in this study is significant for the selection of the imaging segment, and provides the evidence for the following data processing and compensation algorithm. (paper)

Effect of solar chimney inclination angle on space flow pattern and ventilation rate

Energy Technology Data Exchange (ETDEWEB)

Bassiouny, Ramadan; Korah, Nader S.A. [Department of Mechanical Power Engineering and Energy, Minia University, Minia 61111 (Egypt)

2009-02-15

The solar chimney is a simple and practical idea that is applied to enhance space natural ventilation. The chimney could be vertical or inclined. The chimney inclination angle is an important parameter that greatly affects space flow pattern and ventilation rate. In the present study, the effect of chimney inclination angle on air change per hour and indoor flow pattern was numerically and analytically investigated. A numerical simulation using Ansys, a FEM-based code, was used to predict flow pattern. Then the results were compared with published experimental measurements. A FORTRAN program was developed to iteratively solve the mathematical model that was obtained through an overall energy balance on the solar chimney. The analytical results showed that an optimum air flow rate value was achieved when the chimney inclination is between 45 and 70 for latitude of 28.4 . The numerically predicted flow pattern inside the space supports this finding. Moreover, in the present study a correlation to predict the air change per hour was developed. The correlation was tested within a solar intensity greater than or equal to 500 W/m{sup 2}, and chimney width from 0.1 m to 0.35 m for different inclination angles with acceptable values. (author)

Multi-spectral endogenous fluorescence imaging for bacterial differentiation

Science.gov (United States)

Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

2017-07-01

In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

Estimation of carrying angle based on CT images in preoperative surgical planning for cubitus deformities

International Nuclear Information System (INIS)

Park, Shinsuk; Kim, Eugene

2009-01-01

Conventionally, the carrying angle of the elbow is measured using simple two-dimensional radiography or goniometry, which has questionable reliability. This study proposes a novel method for estimating carrying angles using computed tomography that can enhance the reliability of the angle measurement. Data of CT scans from 25 elbow joints were processed to build segmented three-dimensional models. The cross-sectional centerlines of the ulna and the humerus were traced from the 3D models, and the angle between 2 vectors formed from the centerlines of the humerus and the ulna was defined as the 'three-dimensional carrying angle.' These angles were compared with those measured by simple radiograph. Two cases of angular deformity were underwent surgery based on this preoperative surgical planning, and the postoperative 3D carrying angles were evaluated using the proposed method. The mean value of the calculated three-dimensional carrying angle was 20.7deg±3.61, while it was 16.3deg±3.21 based on simple radiography without statistical difference. Based on the 3D carrying angle estimations, 2 surgical cases of cubitus deformities were planned by comparison with the normal contra-lateral elbow. Postoperative angle estimations confirmed that the corrected angles were nearly identical to the planned angles for both cases. The results of this study showed that the carrying angle can be accurately estimated using three-dimensional CT and that the proposed method is useful in evaluating deformities of the elbow with high reliability. (author)

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

Science.gov (United States)

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

Science.gov (United States)

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

CO-REGISTRATION OF TERRESTRIAL AND UAV-BASED IMAGES – EXPERIMENTAL RESULTS

Directory of Open Access Journals (Sweden)

M. Gerke

2016-03-01

Full Text Available For many applications within urban environments the combined use of images taken from the ground and from unmanned aerial platforms seems interesting: while from the airborne perspective the upper parts of objects including roofs can be observed, the ground images can complement the data from lateral views to retrieve a complete visualisation or 3D reconstruction of interesting areas. The automatic co-registration of air- and ground-based images is still a challenge and cannot be considered solved. The main obstacle is originating from the fact that objects are photographed from quite different angles, and hence state-of-the-art tie point measurement approaches cannot cope with the induced perspective transformation. One first important step towards a solution is to use airborne images taken under slant directions. Those oblique views not only help to connect vertical images and horizontal views but also provide image information from 3D-structures not visible from the other two directions. According to our experience, however, still a good planning and many images taken under different viewing angles are needed to support an automatic matching across all images and complete bundle block adjustment. Nevertheless, the entire process is still quite sensible – the removal of a single image might lead to a completely different or wrong solution, or separation of image blocks. In this paper we analyse the impact different parameters and strategies have on the solution. Those are a the used tie point matcher, b the used software for bundle adjustment. Using the data provided in the context of the ISPRS benchmark on multi-platform photogrammetry, we systematically address the mentioned influences. Concerning the tie-point matching we test the standard SIFT point extractor and descriptor, but also the SURF and ASIFT-approaches, the ORB technique, as well as (AKAZE, which are based on a nonlinear scale space. In terms of pre-processing we analyse the

Interdependence of torque, joint angle, angular velocity and muscle action during human multi-joint leg extension.

Science.gov (United States)

Hahn, Daniel; Herzog, Walter; Schwirtz, Ansgar

2014-08-01

Force and torque production of human muscles depends upon their lengths and contraction velocity. However, these factors are widely assumed to be independent of each other and the few studies that dealt with interactions of torque, angle and angular velocity are based on isolated single-joint movements. Thus, the purpose of this study was to determine force/torque-angle and force/torque-angular velocity properties for multi-joint leg extensions. Human leg extension was investigated (n = 18) on a motor-driven leg press dynamometer while measuring external reaction forces at the feet. Extensor torque in the knee joint was calculated using inverse dynamics. Isometric contractions were performed at eight joint angle configurations of the lower limb corresponding to increments of 10° at the knee from 30 to 100° of knee flexion. Concentric and eccentric contractions were performed over the same range of motion at mean angular velocities of the knee from 30 to 240° s(-1). For contractions of increasing velocity, optimum knee angle shifted from 52 ± 7 to 64 ± 4° knee flexion. Furthermore, the curvature of the concentric force/torque-angular velocity relations varied with joint angles and maximum angular velocities increased from 866 ± 79 to 1,238 ± 132° s(-1) for 90-50° knee flexion. Normalised eccentric forces/torques ranged from 0.85 ± 0.12 to 1.32 ± 0.16 of their isometric reference, only showing significant increases above isometric and an effect of angular velocity for joint angles greater than optimum knee angle. The findings reveal that force/torque production during multi-joint leg extension depends on the combined effects of angle and angular velocity. This finding should be accounted for in modelling and optimisation of human movement.

Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

Directory of Open Access Journals (Sweden)

Zhongwen Hu

2016-02-01

Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

Extended depth of field integral imaging using multi-focus fusion

Science.gov (United States)

Piao, Yongri; Zhang, Miao; Wang, Xiaohui; Li, Peihua

2018-03-01

In this paper, we propose a new method for depth of field extension in integral imaging by realizing the image fusion method on the multi-focus elemental images. In the proposed method, a camera is translated on a 2D grid to take multi-focus elemental images by sweeping the focus plane across the scene. Simply applying an image fusion method on the elemental images holding rich parallax information does not work effectively because registration accuracy of images is the prerequisite for image fusion. To solve this problem an elemental image generalization method is proposed. The aim of this generalization process is to geometrically align the objects in all elemental images so that the correct regions of multi-focus elemental images can be exacted. The all-in focus elemental images are then generated by fusing the generalized elemental images using the block based fusion method. The experimental results demonstrate that the depth of field of synthetic aperture integral imaging system has been extended by realizing the generation method combined with the image fusion on multi-focus elemental images in synthetic aperture integral imaging system.

3D OBJECT COORDINATES EXTRACTION BY RADARGRAMMETRY AND MULTI STEP IMAGE MATCHING

Directory of Open Access Journals (Sweden)

A. Eftekhari

2013-09-01

Full Text Available Nowadays by high resolution SAR imaging systems as Radarsat-2, TerraSAR-X and COSMO-skyMed, three-dimensional terrain data extraction using SAR images is growing. InSAR and Radargrammetry are two most common approaches for removing 3D object coordinate from SAR images. Research has shown that extraction of terrain elevation data using satellite repeat pass interferometry SAR technique due to atmospheric factors and the lack of coherence between the images in areas with dense vegetation cover is a problematic. So the use of Radargrammetry technique can be effective. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-stage algorithm founded on the combination of feature based and area based image matching. Then the RPCs that calculate for each images use for extracting 3D coordinate in matched points. At the end, the coordinates calculating that compare with coordinates extracted from 1 meters DEM. The results show root mean square errors for 360 points are 3.09 meters. We use a pair of spotlight TerraSAR-X images from JAM (IRAN in this article.

Perceptual quality of color images of natural scenes transformed in CIELUV color space

NARCIS (Netherlands)

Fedorovskaya, E.A.; Blommaert, F.J.J.; Ridder, de H.; Eschbach, R.; Braun, K.

1997-01-01

Transformations of digitized color images in perceptually-uniform CIELUV color space and their perceptual relevance were investigated. Chroma veriation was chosen as the first step of a series of investigations into possible transformations (including lightness, hue-angle, chroma, ect.) To obtain

Perceptual quality of color images of natural scenes transformed in CIELUV color space

NARCIS (Netherlands)

Fedorovskaya, E.A.; Blommaert, F.J.J.; Ridder, de H.

1993-01-01

Transformations of digitized color images in perceptually-uniform CIELUV color space and their perceptual relevance were investigated. Chroma variation was chosen as the first step of a series of investigations into possible transformations (including lightness, hue-angle, chroma, etc.). To obtain

Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

Directory of Open Access Journals (Sweden)

Qianghui Zhang

2016-07-01

Full Text Available Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS, which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD based on Stolt interpolation. Finally, a modified TSP (MTSP is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application.

Large-Scale Multi-Resolution Representations for Accurate Interactive Image and Volume Operations

KAUST Repository

Sicat, Ronell B.

2015-11-25

and voxel footprints in input images and volumes. We show that the continuous pdfs encoded in the sparse pdf map representation enable accurate multi-resolution non-linear image operations on gigapixel images. Similarly, we show that sparse pdf volumes enable more consistent multi-resolution volume rendering compared to standard approaches, on both artificial and real world large-scale volumes. The supplementary videos demonstrate our results. In the standard approach, users heavily rely on panning and zooming interactions to navigate the data within the limits of their display devices. However, panning across the whole spatial domain and zooming across all resolution levels of large-scale images to search for interesting regions is not practical. Assisted exploration techniques allow users to quickly narrow down millions to billions of possible regions to a more manageable number for further inspection. However, existing approaches are not fully user-driven because they typically already prescribe what being of interest means. To address this, we introduce the patch sets representation for large-scale images. Patches inside a patch set are grouped and encoded according to similarity via a permutohedral lattice (p-lattice) in a user-defined feature space. Fast set operations on p-lattices facilitate patch set queries that enable users to describe what is interesting. In addition, we introduce an exploration framework—GigaPatchExplorer—for patch set-based image exploration. We show that patch sets in our framework are useful for a variety of user-driven exploration tasks in gigapixel images and whole collections thereof.

Detection of relationships among multi-modal brain imaging meta-features via information flow.

Science.gov (United States)

Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

2018-01-15

Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is

MultiSpec—a tool for multispectral hyperspectral image data analysis

Science.gov (United States)

Biehl, Larry; Landgrebe, David

2002-12-01

MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

Two Phase Non-Rigid Multi-Modal Image Registration Using Weber Local Descriptor-Based Similarity Metrics and Normalized Mutual Information

Directory of Open Access Journals (Sweden)

Feng Yang

2013-06-01

Full Text Available Non-rigid multi-modal image registration plays an important role in medical image processing and analysis. Existing image registration methods based on similarity metrics such as mutual information (MI and sum of squared differences (SSD cannot achieve either high registration accuracy or high registration efficiency. To address this problem, we propose a novel two phase non-rigid multi-modal image registration method by combining Weber local descriptor (WLD based similarity metrics with the normalized mutual information (NMI using the diffeomorphic free-form deformation (FFD model. The first phase aims at recovering the large deformation component using the WLD based non-local SSD (wldNSSD or weighted structural similarity (wldWSSIM. Based on the output of the former phase, the second phase is focused on getting accurate transformation parameters related to the small deformation using the NMI. Extensive experiments on T1, T2 and PD weighted MR images demonstrate that the proposed wldNSSD-NMI or wldWSSIM-NMI method outperforms the registration methods based on the NMI, the conditional mutual information (CMI, the SSD on entropy images (ESSD and the ESSD-NMI in terms of registration accuracy and computation efficiency.

Multi-scale simulations of field ion microscopy images—Image compression with and without the tip shank

International Nuclear Information System (INIS)

NiewieczerzaŁ, Daniel; Oleksy, CzesŁaw; Szczepkowicz, Andrzej

2012-01-01

Multi-scale simulations of field ion microscopy images of faceted and hemispherical samples are performed using a 3D model. It is shown that faceted crystals have compressed images even in cases with no shank. The presence of the shank increases the compression of images of faceted crystals quantitatively in the same way as for hemispherical samples. It is hereby proven that the shank does not influence significantly the local, relative variations of the magnification caused by the atomic-scale structure of the sample. -- Highlights: ► Multi-scale simulations of field ion microscopy images. ► Faceted and hemispherical samples with and without shank. ► Shank causes overall compression, but does not influence local magnification effects. ► Image compression linearly increases with the shank angle. ► Shank changes compression of image of faceted tip in the same way as for smooth sample.

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

Science.gov (United States)

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

A multi-object spectral imaging instrument

OpenAIRE

Gibson, G.M.; Dienerowitz, M.; Kelleher, P.A.; Harvey, A.R.; Padgett, M.J.

2013-01-01

We have developed a snapshot spectral imaging system which fits onto the side camera port of a commercial inverted microscope. The system provides spectra, in real time, from multiple points randomly selected on the microscope image. Light from the selected points in the sample is directed from the side port imaging arm using a digital micromirror device to a spectrometer arm based on a dispersing prism and CCD camera. A multi-line laser source is used to calibrate the pixel positions on the ...

Characteristics of magnetic resonance imaging with partial flip angle and gradient field echo

International Nuclear Information System (INIS)

Hamada, Tatsumi; Uto, Tatsurou; Okafuji, Tatsumasa; Ookusa, Akihiko; Oonishi, Takuya; Mabuchi, Nobuhisa; Fujii, Kouichi; Yoshioka, Hiroyasu; Ishida, Osamu

1988-01-01

Characteristics of a magnetic resonance (MR) imaging pulse sequence with short repetition time (Tr), short echo time (Te), partial flip angle and gradient field echo, at 0.5 T, were studied. A series of sagittal images of the cerebrospinal region was obtained with varied Tr, Te and flip angle, signal intensities were measured by means of a region of interest (ROI) function, and optimal parameters to achieve maximum tissue contrast were found. Of the parameters flip angle had the greatest effect on tissue contrast. Flip angles less than 20 or more than 60 degrees were necessary to discriminate between spinal cord and cerebrospinal fluid. So called MR myelography was obtained with the flip angle of 15 degrees. Opposed and inphase images were obtained at the Te levels of 21 and 28 ms, respectively. Likewise, a series of transverse images of the abdomen with short Tr, short Te and varied flip angles was obtained in a breath-holding interval, and signal intensities of ROIs were measured. Maximum intensities of the liver, the spleen and perirenal fat were obtained at the flip angles of 40, 30 and 60 degrees, respectively. Although maximum intensity was found at the flip angle of 30 degrees for both of the renal cortex and medulla, the maximum contrast between the two tissues was obtained at the flip angles of 50-60 degrees. The image contrast obtained by these pulse sequences was also theoretically predictable, and so it is thought possible that flip angle, Tr and Te are manipulated to yield a desired contrast. (author)

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

Science.gov (United States)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

Multi sensor satellite imagers for commercial remote sensing

Science.gov (United States)

Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

2005-10-01

This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

Measurement of Critical Contact Angle in a Microgravity Space Experiment

Science.gov (United States)

Concus, P.; Finn, R.; Weislogel, M.

1998-01-01

Mathematical theory predicts that small changes in container shape or in contact angle can give rise to large shifts of liquid in a microgravity environment. This phenomenon was investigated in the Interface Configuration Experiment on board the USMT,2 Space Shuttle flight. The experiment's "double proboscis" containers were designed to strike a balance between conflicting requirements of sizable volume of liquid shift (for ease of observation) and abruptness of the shift (for accurate determination of critical contact angle). The experimental results support the classical concept of macroscopic contact angle and demonstrate the role of hysteresis in impeding orientation toward equilibrium.

High energy electron radiography system design and simulation study of beam angle-position correlation and aperture effect on the images

International Nuclear Information System (INIS)

Zhao, Quantang; Cao, S.C.; Liu, M.; Sheng, X.K.; Wang, Y.R.; Zong, Y.; Zhang, X.M.; Jing, Y.; Cheng, R.; Zhao, Y.T.; Zhang, Z.M.; Du, Y.C.; Gai, W.

2016-01-01

A beam line dedicated to high-energy electron radiography experimental research with linear achromat and imaging lens systems has been designed. The field of view requirement on the target and the beam angle-position correlation correction can be achieved by fine-tuning the fields of the quadrupoles used in the achromat in combination with already existing six quadrupoles before the achromat. The radiography system is designed by fully considering the space limitation of the laboratory and the beam diagnostics devices. Two kinds of imaging lens system, a quadruplet and an octuplet system are integrated into one beam line with the same object plane and image plane but with different magnification factor. The beam angle-position correlation on the target required by the imaging lens system and the aperture effect on the images are studied with particle tracking simulation. It is shown that the aperture position is also correlated to the beam angle-position on the target. With matched beam on the target, corresponding aperture position and suitable aperture radius, clear pictures can be imaged by both lens systems. The aperture is very important for the imaging. The details of the beam optical requirements, optimized parameters and the simulation results are presented.

FULLY AUTOMATED IMAGE ORIENTATION IN THE ABSENCE OF TARGETS

Directory of Open Access Journals (Sweden)

C. Stamatopoulos

2012-07-01

Full Text Available Automated close-range photogrammetric network orientation has traditionally been associated with the use of coded targets in the object space to allow for an initial relative orientation (RO and subsequent spatial resection of the images. Over the past decade, automated orientation via feature-based matching (FBM techniques has attracted renewed research attention in both the photogrammetry and computer vision (CV communities. This is largely due to advances made towards the goal of automated relative orientation of multi-image networks covering untargetted (markerless objects. There are now a number of CV-based algorithms, with accompanying open-source software, that can achieve multi-image orientation within narrow-baseline networks. From a photogrammetric standpoint, the results are typically disappointing as the metric integrity of the resulting models is generally poor, or even unknown, while the number of outliers within the image matching and triangulation is large, and generally too large to allow relative orientation (RO via the commonly used coplanarity equations. On the other hand, there are few examples within the photogrammetric research field of automated markerless camera calibration to metric tolerances, and these too are restricted to narrow-baseline, low-convergence imaging geometry. The objective addressed in this paper is markerless automatic multi-image orientation, maintaining metric integrity, within networks that incorporate wide-baseline imagery. By wide-baseline we imply convergent multi-image configurations with convergence angles of up to around 90°. An associated aim is provision of a fast, fully automated process, which can be performed without user intervention. For this purpose, various algorithms require optimisation to allow parallel processing utilising multiple PC cores and graphics processing units (GPUs.

Geometric approach to the design of an imaging probe to evaluate the iridocorneal angle structures

Science.gov (United States)

Hong, Xun Jie Jeesmond; V. K., Shinoj; Murukeshan, V. M.; Baskaran, M.; Aung, Tin

2017-06-01

Photographic imaging methods allow the tracking of anatomical changes in the iridocorneal angle structures and the monitoring of treatment responses overtime. In this work, we aim to design an imaging probe to evaluate the iridocorneal angle structures using geometrical optics. We first perform an analytical analysis on light propagation from the anterior chamber of the eye to the exterior medium using Snell's law. This is followed by adopting a strategy to achieve uniform near field irradiance, by simplifying the complex non-rotational symmetric irradiance distribution of LEDs tilted at an angle. The optimization is based on the geometric design considerations of an angled circular ring array of 4 LEDs (or a 2 × 2 square LED array). The design equation give insights on variable parameters such as the illumination angle of the LEDs, ring array radius, viewing angle of the LEDs, and the working distance. A micro color CCD video camera that has sufficient resolution to resolve the iridocorneal angle structures at the required working distance is then chosen. The proposed design aspects fulfil the safety requirements recommended by the International Commission on Non-ionizing Radiation Protection.

Controlling T2 blurring in 3D RARE arterial spin labeling acquisition through optimal combination of variable flip angles and k-space filtering.

Science.gov (United States)

Zhao, Li; Chang, Ching-Di; Alsop, David C

2018-02-09

To improve the SNR efficiency and reduce the T 2 blurring of 3D rapid acquisition with relaxation enhancement stack-of-spiral arterial spin labeling imaging by using variable refocusing flip angles and k-space filtering. An algorithm for determining the optimal combination of variable flip angles and filtering correction is proposed. The flip angles are designed using extended phase graph physical simulations in an analytical and global optimization framework, with an optional constraint on deposited power. Optimal designs for correcting to Hann and Fermi window functions were compared with conventional constant amplitude or variable flip angle only designs on 6 volunteers. With the Fermi window correction, the proposed optimal designs provided 39.8 and 27.3% higher SNR (P variable flip angle designs. Even when power deposition was limited to 50% of the constant amplitude design, the proposed method outperformed the SNR (P variable flip angles can be derived as the output of an optimization problem. The combined design of variable flip angle and k-space filtering provided superior SNR to designs primarily emphasizing either approach singly. © 2018 International Society for Magnetic Resonance in Medicine.

T2-weighted MR imaging of the liver: Qualitative and quantitative comparison of SPACE MR imaging with turbo spin-echo MR imaging

Energy Technology Data Exchange (ETDEWEB)

Dohan, Anthony, E-mail: anthony.dohan@lrb.aphp.fr [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Université Paris-Diderot, Sorbonne Paris Cité, 10 Rue de Verdun, 75010 Paris (France); UMR INSERM 965, Hôpital Lariboisière, 2 Rue Amboise Paré, 75010 Paris (France); Gavini, Jean-Philippe, E-mail: jpgavini@gmail.com [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Université Paris-Diderot, Sorbonne Paris Cité, 10 Rue de Verdun, 75010 Paris (France); Placé, Vinciane, E-mail: vinciane.place@gmail.com [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Sebbag, Delphine, E-mail: delphinesebbag@gmail.com [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Université Paris-Diderot, Sorbonne Paris Cité, 10 Rue de Verdun, 75010 Paris (France); Vignaud, Alexandre, E-mail: alexandre.vignaud@cea.fr [LRMN, Neurospin, CEA-SACLAY, Bâtiment 145, 91 191 Gif-sur-Yvette Cedex (France); and others

2013-11-01

Objective: To qualitatively and quantitatively compare T2-weighted MR imaging of the liver using volumetric spin-echo with sampling perfection with application-optimized contrast using different flip angle evolutions (SPACE) with conventional turbo spin-echo (TSE) sequence for fat-suppressed T2-weighted MR imaging of the liver. Materials and methods: Thirty-three patients with suspected focal liver lesions had SPACE MR imaging and conventional fat-suppressed TSE MR imaging. Images were analyzed quantitatively by measuring the lesion-to-liver contrast-to-noise ratio (CNR), and the signal-to-noise ratio (SNR) of main focal hepatic lesions, hepatic and splenic parenchyma and qualitatively by evaluating the presence of vascular, respiratory motion and cardiac artifacts. Wilcoxon signed rank test was used to search for differences between the two sequences. Results: SPACE MR imaging showed significantly greater CNR for focal liver lesions (median = 22.82) than TSE MR imaging (median = 14.15) (P < .001). No differences were found for SNR of hepatic parenchyma (P = .097), main focal hepatic lesions (P = .35), and splenic parenchyma (P = .25). SPACE sequence showed less artifacts than TSE sequence (vascular, P < .001; respiratory motion, P < .001; cardiac, P < .001) but needed a longer acquisition time (228.4 vs. 162.1 s; P < .001). Conclusion: SPACE MR imaging provides a significantly increased CNR for focal liver lesions and less artifacts by comparison with the conventional TSE sequence. These results should stimulate further clinical studies with a surgical standard of reference to compare the two techniques in terms of sensitivity for malignant lesions.

Improvement of viewing-zone angle and image quality of digital holograms

Energy Technology Data Exchange (ETDEWEB)

Nomura, Takanori, E-mail: nom@sys.wakayama-u.ac.j [Faculty of Systems Enigneering, Wakayama Univesity, 930 Sakaedani, Wakayama, 640-8510 (Japan)

2010-02-01

The method to improve of a viewing-zone angle and an image quality of a digital hologram is presented. A number of digital holograms of a central object are recorded from the position on the circumference. The holograms are used for a hologram synthesis to improve the image quality from whole viewing-zone angle. The synthesis is achieved by a correlation between a hologram and numerically propagated holograms. The large-sized synthesized digital hologram has a wide viewing-zone angle and less speckles. Some experimental results are shown to confirm the proposed method.

A conjunct near-surface spectroscopy system for fix-angle and multi-angle continuous measurements of canopy reflectance and sun-induced chlorophyll fluorescence

Science.gov (United States)

Zhang, Qian; Fan, Yifeng; Zhang, Yongguang; Chou, Shuren; Ju, Weimin; Chen, Jing M.

2016-09-01

An automated spectroscopy system, which is divided into fix-angle and multi-angle subsystems, for collecting simultaneous, continuous and long-term measurements of canopy hyper-spectra in a crop ecosystem is developed. The fix-angle subsystem equips two spectrometers: one is HR2000+ (OceanOptics) covering the spectral range 200-1100 nm with 1.0 nm spectral resolution, and another one is QE65PRO (OceanOptics) providing 0.1 nm spectral resolution within the 730-780 nm spectral range. Both spectrometers connect a cosine-corrected fiber-optic fixed up-looking to collect the down-welling irradiance and a bare fiber-optic to measure the up-welling radiance from the vegetation. An inline fiber-optic shutter FOS-2x2-TTL (OceanOptics) is used to switch between input fibers to collect the signal from either the canopy or sky at one time. QE65PRO is used to permit estimation of vegetation Sun-Induced Fluorescence (SIF) in the O2-A band. The data collection scheme includes optimization of spectrometer integration time to maximize the signal to noise ratio and measurement of instrument dark currency. The multi-angle subsystem, which can help understanding bidirectional reflectance effects, alternatively use HR4000 (OceanOptics) providing 0.1 nm spectral resolution within the 680-800 nm spectral range to measure multi-angle SIF. This subsystem additionally includes a spectrometer Unispec-DC (PPSystems) featuring both up-welling and down-welling channels with 3 nm spectral resolution covering the 300-1100 nm spectral range. Two down-looking fiber-optics are mounted on a rotating device PTU-D46 (FLIR Systems), which can rotate horizontally and vertically at 10° angular step widths. Observations can be used to calculate canopy reflectance, vegetation indices and SIF for monitoring plant physiological processes.

In situ beam angle measurement in a multi-wafer high current ion implanter

International Nuclear Information System (INIS)

Freer, B.S.; Reece, R.N.; Graf, M.A.; Parrill, T.; Polner, D.

2005-01-01

Direct, in situ measurement of the average angle and angular content of an ion beam in a multi-wafer ion implanter is reported for the first time. A new type of structure and method are described. The structures are located on the spinning disk, allowing precise angular alignment to the wafers. Current that passes through the structures is known to be within a range of angles and is detected behind the disk. By varying the angle of the disk around two axes, beam current versus angle is mapped and the average angle and angular spread are calculated. The average angle measured in this way is found to be consistent with that obtained by other techniques, including beam centroid offset and wafer channeling methods. Average angle of low energy beams, for which it is difficult to use other direct methods, is explored. A 'pencil beam' system is shown to give average angle repeatability of 0.13 deg. (1σ) or less, for two low energy beams under normal tuning variations, even though no effort was made to control the angle

Fully refocused multi-shot spatiotemporally encoded MRI: robust imaging in the presence of metallic implants.

Science.gov (United States)

Ben-Eliezer, Noam; Solomon, Eddy; Harel, Elad; Nevo, Nava; Frydman, Lucio

2012-12-01

An approach has been recently introduced for acquiring arbitrary 2D NMR spectra or images in a single scan, based on the use of frequency-swept RF pulses for the sequential excitation and acquisition of the spins response. This spatiotemporal-encoding (SPEN) approach enables a unique, voxel-by-voxel refocusing of all frequency shifts in the sample, for all instants throughout the data acquisition. The present study investigates the use of this full-refocusing aspect of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that complicate conventional imaging approaches. 2D MRI experiments were performed at 7 T on phantoms and on mice in vivo, focusing on imaging in proximity to metallic objects. Fully refocused SPEN-based spin echo imaging sequences were implemented, using both Cartesian and back-projection trajectories, and compared with k-space encoded spin echo imaging schemes collected on identical samples under equal bandwidths and acquisition timing conditions. In all cases assayed, the fully refocused spatiotemporally encoded experiments evidenced a ca. 50 % reduction in signal dephasing in the proximity of the metal, as compared to analogous results stemming from the k-space encoded spin echo counterparts. The results in this study suggest that SPEN-based acquisition schemes carry the potential to overcome strong field inhomogeneities, of the kind that currently preclude high-field, high-resolution tissue characterizations in the neighborhood of metallic implants.

Angle Control-Based Multi-Terminal Out-of-Step Protection System

Directory of Open Access Journals (Sweden)

Antans Sauhats

2017-03-01

Full Text Available From time to time a sequence of unexpected and overlapping contingencies may lead to power system angular instability and even blackouts if not addressed adequately by means of an out-of-step (OOS protection system. The motivation of the paper is an attempt to develop a workable prototype of the OOS protection system. The deficiencies of the protection currently used in the Latvian Power System network are highlighted and a new protection structure is proposed. The protection system comprises of several strategically located terminals, exchanging information in real time by means of a communication network. The OOS condition detection method is based on system-wide generation sources, electromotive forces, vectors, and angle control. The network splitting decision is based on generator coherence evaluation. Protection terminals determine online the groups of coherent generators and choose the splitting boundary from a predefined transmission lines (TLs cut sets list. The protection system structure, algorithm of operation, and possible IEC 61850 communication standard-based implementation are described.

Study of limited angle swing laminography and its application in the inspection of flat components

International Nuclear Information System (INIS)

Ming Ming; Li Zheng; Wang Jing; Cheng Jianping; Wang Xuewu; Kang Kejun

2002-01-01

It is important to inspect the inner defects, density distribution of the multi-structure complex material. The conflict of resolution of reconstructed image and reconstruction efficiency baffled people long when applying radiation laminography to that kind of material. Limited angle swing laminography algorithm was put forward. A simulation of printed circuits board by MATLAB attested the rationality and high efficiency of this algorithm. Based upon the simulation, the principle of choosing optimal projection angle was discussed. Finally, an application example was given

Factors influencing fast low angle positive contrast steady-state free precession (FLAPS) magnetic resonance imaging

International Nuclear Information System (INIS)

Dharmakumar, Rohan; Koktzoglou, Ioannis; Li Debiao

2007-01-01

The presence of susceptibility-shifting media can lead to signal voids in magnetic resonance images. While signal voids have been traditionally used to detect such magnetic perturbers, selective magnetic resonance imaging of off-resonant spins surrounding susceptibility-shifted media allows for them to be visualized as hyper-intense (positive contrast) regions. These positive contrast methods can potentially improve the detection conspicuity of magnetic perturbers against regions that appear dark due to the absence of protons, such as air. Recently, a fast low angle positive contrast steady-state free precession (FLAPS) technique has been proposed as a positive contrast imaging method. This work systematically evaluates the contrast characteristics and acquisition strategies of FLAPS-based imaging from the standpoint of imaging parameters and physical properties of the magnetic perturbers. Results show that scan parameters (T R , flip angle, B 0 ), physical properties of the perturber (size and concentration of shift reagent) and the ratio of the relaxation constants (T 1 /T 2 ) of the medium are significant factors influencing the FLAPS-based positive contrast

Gaze Estimation for Off-Angle Iris Recognition Based on the Biometric Eye Model

Energy Technology Data Exchange (ETDEWEB)

Karakaya, Mahmut [ORNL; Barstow, Del R [ORNL; Santos-Villalobos, Hector J [ORNL; Thompson, Joseph W [ORNL; Bolme, David S [ORNL; Boehnen, Chris Bensing [ORNL

2013-01-01

Iris recognition is among the highest accuracy biometrics. However, its accuracy relies on controlled high quality capture data and is negatively affected by several factors such as angle, occlusion, and dilation. Non-ideal iris recognition is a new research focus in biometrics. In this paper, we present a gaze estimation method designed for use in an off-angle iris recognition framework based on the ANONYMIZED biometric eye model. Gaze estimation is an important prerequisite step to correct an off-angle iris images. To achieve the accurate frontal reconstruction of an off-angle iris image, we first need to estimate the eye gaze direction from elliptical features of an iris image. Typically additional information such as well-controlled light sources, head mounted equipment, and multiple cameras are not available. Our approach utilizes only the iris and pupil boundary segmentation allowing it to be applicable to all iris capture hardware. We compare the boundaries with a look-up-table generated by using our biologically inspired biometric eye model and find the closest feature point in the look-up-table to estimate the gaze. Based on the results from real images, the proposed method shows effectiveness in gaze estimation accuracy for our biometric eye model with an average error of approximately 3.5 degrees over a 50 degree range.

Multi-imaging adaptive concept for IR and submillimeter space telescopes

Science.gov (United States)

Vasilyev, Victor P.

1995-06-01

Nontraditional IR and submillimeter spaceborne telescope concept basing on blind-type parabolic multi-ring mirror is proposed and discussed. Preliminary results for optimization of mirror parameters by means of computer simulation are presented.

Space Radar Image of Chernobyl

Science.gov (United States)

1994-01-01

This is an image of the Chernobyl nuclear power plant and its surroundings, centered at 51.17 north latitude and 30.15 west longitude. The image was acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on its 16th orbit on October 1, 1994. The area is located on the northern border of the Ukraine Republic and was produced by using the L-band (horizontally transmitted and received) polarization. The differences in the intensity are due to differences in vegetation cover, with brighter areas being indicative of more vegetation. These data were acquired as part of a collaboration between NASA and the National Space Agency of Ukraine in Remote Sensing and Earth Sciences. NASA has included several sites provided by the Ukrainian space agency as targets of opportunity during the second flight of SIR-C/X-SAR. The Ukrainian space agency also plans to conduct airborne surveys of these sites during the mission. The Chernobyl nuclear power plant is located toward the top of the image near the Pripyat River. The 12-kilometer (7.44-mile)-long cooling pond is easily distinguishable as an elongated dark shape in the center near the top of the image. The reactor complex is visible as the bright area to the extreme left of the cooling pond and the city of Chernobyl is the bright area just below the cooling pond next to the Pripyat River. The large dark area in the bottom right of the image is the Kiev Reservoir just north of Kiev. Also visible is the Dnieper River, which feeds into the Kiev Reservoir from the top of the image. The Soviet government evacuated 116,000 people within 30 kilometers (18.6 miles) of the Chernobyl reactor after the explosion and fire on April 26, 1986. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight

Generic framework for vessel detection and tracking based on distributed marine radar image data

Science.gov (United States)

Siegert, Gregor; Hoth, Julian; Banyś, Paweł; Heymann, Frank

2018-04-01

Situation awareness is understood as a key requirement for safe and secure shipping at sea. The primary sensor for maritime situation assessment is still the radar, with the AIS being introduced as supplemental service only. In this article, we present a framework to assess the current situation picture based on marine radar image processing. Essentially, the framework comprises a centralized IMM-JPDA multi-target tracker in combination with a fully automated scheme for track management, i.e., target acquisition and track depletion. This tracker is conditioned on measurements extracted from radar images. To gain a more robust and complete situation picture, we are exploiting the aspect angle diversity of multiple marine radars, by fusing them a priori to the tracking process. Due to the generic structure of the proposed framework, different techniques for radar image processing can be implemented and compared, namely the BLOB detector and SExtractor. The overall framework performance in terms of multi-target state estimation will be compared for both methods based on a dedicated measurement campaign in the Baltic Sea with multiple static and mobile targets given.

Quantification of the multi-streaming effect in redshift space distortion

Energy Technology Data Exchange (ETDEWEB)

Zheng, Yi; Oh, Minji [Korea Astronomy and Space Science Institute, 776, Daedeokdae-ro, Yuseong-gu, Daejeon 34055 (Korea, Republic of); Zhang, Pengjie, E-mail: yizheng@kasi.re.kr, E-mail: zhangpj@sjtu.edu.cn, E-mail: minjioh@kasi.re.kr [Center for Astronomy and Astrophysics, Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240 (China)

2017-05-01

Both multi-streaming (random motion) and bulk motion cause the Finger-of-God (FoG) effect in redshift space distortion (RSD). We apply a direct measurement of the multi-streaming effect in RSD from simulations, proving that it induces an additional, non-negligible FoG damping to the redshift space density power spectrum. We show that, including the multi-streaming effect, the RSD modelling is significantly improved. We also provide a theoretical explanation based on halo model for the measured effect, including a fitting formula with one to two free parameters. The improved understanding of FoG helps break the f σ{sub 8}−σ {sub v} degeneracy in RSD cosmology, and has the potential of significantly improving cosmological constraints.

Electron energy spectrum and maximum disruption angle under multi-photon beamstrahlung

Energy Technology Data Exchange (ETDEWEB)

Yokoya, Kaoru; Chen, Pisin

1989-03-01

The final electron energy spectrum under multi-photon beamstrahlung process is derived analytically in the classical and the intermediate regimes. The maximum disruption angle from the low energy tail of the spectrum is also estimated. The results are then applied to the TLC and the CLIC parameters. 6 refs., 1 fig., 1 tab.

A Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms

Directory of Open Access Journals (Sweden)

Nasreddine Taleb

2010-09-01

Full Text Available Image registration is a fundamental task used in image processing to match two or more images taken at different times, from different sensors or from different viewpoints. The objective is to find in a huge search space of geometric transformations, an acceptable accurate solution in a reasonable time to provide better registered images. Exhaustive search is computationally expensive and the computational cost increases exponentially with the number of transformation parameters and the size of the data set. In this work, we present an efficient image registration algorithm that uses genetic algorithms within a multi-resolution framework based on the Non-Subsampled Contourlet Transform (NSCT. An adaptable genetic algorithm for registration is adopted in order to minimize the search space. This approach is used within a hybrid scheme applying the two techniques fitness sharing and elitism. Two NSCT based methods are proposed for registration. A comparative study is established between these methods and a wavelet based one. Because the NSCT is a shift-invariant multidirectional transform, the second method is adopted for its search speeding up property. Simulation results clearly show that both proposed techniques are really promising methods for image registration compared to the wavelet approach, while the second technique has led to the best performance results of all. Moreover, to demonstrate the effectiveness of these methods, these registration techniques have been successfully applied to register SPOT, IKONOS and Synthetic Aperture Radar (SAR images. The algorithm has been shown to work perfectly well for multi-temporal satellite images as well, even in the presence of noise.

A rigid image registration based on the nonsubsampled contourlet transform and genetic algorithms.

Science.gov (United States)

Meskine, Fatiha; Chikr El Mezouar, Miloud; Taleb, Nasreddine

2010-01-01

Image registration is a fundamental task used in image processing to match two or more images taken at different times, from different sensors or from different viewpoints. The objective is to find in a huge search space of geometric transformations, an acceptable accurate solution in a reasonable time to provide better registered images. Exhaustive search is computationally expensive and the computational cost increases exponentially with the number of transformation parameters and the size of the data set. In this work, we present an efficient image registration algorithm that uses genetic algorithms within a multi-resolution framework based on the Non-Subsampled Contourlet Transform (NSCT). An adaptable genetic algorithm for registration is adopted in order to minimize the search space. This approach is used within a hybrid scheme applying the two techniques fitness sharing and elitism. Two NSCT based methods are proposed for registration. A comparative study is established between these methods and a wavelet based one. Because the NSCT is a shift-invariant multidirectional transform, the second method is adopted for its search speeding up property. Simulation results clearly show that both proposed techniques are really promising methods for image registration compared to the wavelet approach, while the second technique has led to the best performance results of all. Moreover, to demonstrate the effectiveness of these methods, these registration techniques have been successfully applied to register SPOT, IKONOS and Synthetic Aperture Radar (SAR) images. The algorithm has been shown to work perfectly well for multi-temporal satellite images as well, even in the presence of noise.

Imaging of the perivertebral space.

Science.gov (United States)

Mills, Megan K; Shah, Lubdha M

2015-01-01

The perivertebral space extends from the skull base to the mediastinum and is delineated by the deep layer of the deep cervical fascia. The different tissue types, including muscles, bones, nerves, and vascular structures, give rise to the various disorders that can be seen in this space. This article defines the anatomy of the perivertebral space, guides lesion localization, discusses different disease processes arising within this space, and reviews the best imaging approaches. Copyright © 2015 Elsevier Inc. All rights reserved.

Combining the Pixel-based and Object-based Methods for Building Change Detection Using High-resolution Remote Sensing Images

Directory of Open Access Journals (Sweden)

ZHANG Zhiqiang

2018-01-01

Full Text Available Timely and accurate change detection of buildings provides important information for urban planning and management.Accompanying with the rapid development of satellite remote sensing technology,detecting building changes from high-resolution remote sensing images have received wide attention.Given that pixel-based methods of change detection often lead to low accuracy while object-based methods are complicated for uses,this research proposes a method that combines pixel-based and object-based methods for detecting building changes from high-resolution remote sensing images.First,based on the multiple features extracted from the high-resolution images,a random forest classifier is applied to detect changed building at the pixel level.Then,a segmentation method is applied to segement the post-phase remote sensing image and to get post-phase image objects.Finally,both changed building at the pixel level and post-phase image objects are fused to recognize the changed building objects.Multi-temporal QuickBird images are used as experiment data for building change detection with high-resolution remote sensing images,the results indicate that the proposed method could reduce the influence of environmental difference,such as light intensity and view angle,on building change detection,and effectively improve the accuracies of building change detection.

Integration of least angle regression with empirical Bayes for multi-locus genome-wide association studies

Science.gov (United States)

Multi-locus genome-wide association studies has become the state-of-the-art procedure to identify quantitative trait loci (QTL) associated with traits simultaneously. However, implementation of multi-locus model is still difficult. In this study, we integrated least angle regression with empirical B...

Detecting deep venous thrombosis with limited flip angle gradient refocused MR imaging

International Nuclear Information System (INIS)

Spritzer, C.E.; Sussman, S.K.; Herfkens, R.J.; Blinder, R.A.; Saeed, M.; Vogler, J.A.; Baker, M.E.

1987-01-01

This study was undertaken to determine if limited flip angle gradient refocused MR pulse sequences (GRASS) could be used to accurately diagnose deep venous thrombosis (DVT). Sixteen patients (17 extremities) with possible DVT were prospectively evaluated with MR imaging and venography. Typical imaging parameters included a 16-msec echo time, 33-msec repetition time, 30 0 flip angle, and section thickness of 2 nex. MR imaging correctly disclosed the presence (nine cases) or absence (eight cases) of DVT. In one study, GRASS images overestimated the extent of clot due to slow venous blood flow. Subsequently the flip angle was varied to distinguish between venous thrombus and slow flow. When this technique was used, no false-positive studies occurred in the remaining patients. MR gradient refocused imaging appears to be an accurate aid for the diagnosis of DVT

Modeling human faces with multi-image photogrammetry

Science.gov (United States)

D'Apuzzo, Nicola

2002-03-01

Modeling and measurement of the human face have been increasing by importance for various purposes. Laser scanning, coded light range digitizers, image-based approaches and digital stereo photogrammetry are the used methods currently employed in medical applications, computer animation, video surveillance, teleconferencing and virtual reality to produce three dimensional computer models of the human face. Depending on the application, different are the requirements. Ours are primarily high accuracy of the measurement and automation in the process. The method presented in this paper is based on multi-image photogrammetry. The equipment, the method and results achieved with this technique are here depicted. The process is composed of five steps: acquisition of multi-images, calibration of the system, establishment of corresponding points in the images, computation of their 3-D coordinates and generation of a surface model. The images captured by five CCD cameras arranged in front of the subject are digitized by a frame grabber. The complete system is calibrated using a reference object with coded target points, which can be measured fully automatically. To facilitate the establishment of correspondences in the images, texture in the form of random patterns can be projected from two directions onto the face. The multi-image matching process, based on a geometrical constrained least squares matching algorithm, produces a dense set of corresponding points in the five images. Neighborhood filters are then applied on the matching results to remove the errors. After filtering the data, the three-dimensional coordinates of the matched points are computed by forward intersection using the results of the calibration process; the achieved mean accuracy is about 0.2 mm in the sagittal direction and about 0.1 mm in the lateral direction. The last step of data processing is the generation of a surface model from the point cloud and the application of smooth filters. Moreover, a

A method to measure internal contact angle in opaque systems by magnetic resonance imaging.

Science.gov (United States)

Zhu, Weiqin; Tian, Ye; Gao, Xuefeng; Jiang, Lei

2013-07-23

Internal contact angle is an important parameter for internal wettability characterization. However, due to the limitation of optical imaging, methods available for contact angle measurement are only suitable for transparent or open systems. For most of the practical situations that require contact angle measurement in opaque or enclosed systems, the traditional methods are not effective. Based upon the requirement, a method suitable for contact angle measurement in nontransparent systems is developed by employing MRI technology. In the Article, the method is demonstrated by measuring internal contact angles in opaque cylindrical tubes. It proves that the method also shows great feasibility in transparent situations and opaque capillary systems. By using the method, contact angle in opaque systems could be measured successfully, which is significant in understanding the wetting behaviors in nontransparent systems and calculating interfacial parameters in enclosed systems.

Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification

Directory of Open Access Journals (Sweden)

Fang Xu

2017-09-01

Full Text Available Ship detection by Unmanned Airborne Vehicles (UAVs and satellites plays an important role in a spectrum of related military and civil applications. To improve the detection efficiency, accuracy, and speed, a novel ship detection method from coarse to fine is presented. Ship targets are viewed as uncommon regions in the sea background caused by the differences in colors, textures, shapes, or other factors. Inspired by this fact, a global saliency model is constructed based on high-frequency coefficients of the multi-scale and multi-direction wavelet decomposition, which can characterize different feature information from edge to texture of the input image. To further reduce the false alarms, a new and effective multi-level discrimination method is designed based on the improved entropy and pixel distribution, which is robust against the interferences introduced by islands, coastlines, clouds, and shadows. The experimental results on optical remote sensing images validate that the presented saliency model outperforms the comparative models in terms of the area under the receiver operating characteristic curves core and the accuracy in the images with different sizes. After the target identification, the locations and the number of the ships in various sizes and colors can be detected accurately and fast with high robustness.

Two-stage atlas subset selection in multi-atlas based image segmentation

Energy Technology Data Exchange (ETDEWEB)

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

Two-stage atlas subset selection in multi-atlas based image segmentation.

Science.gov (United States)

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

Two-stage atlas subset selection in multi-atlas based image segmentation

International Nuclear Information System (INIS)

Zhao, Tingting; Ruan, Dan

2015-01-01

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

A novel algorithm of super-resolution image reconstruction based on multi-class dictionaries for natural scene

Science.gov (United States)

Wu, Wei; Zhao, Dewei; Zhang, Huan

2015-12-01

Super-resolution image reconstruction is an effective method to improve the image quality. It has important research significance in the field of image processing. However, the choice of the dictionary directly affects the efficiency of image reconstruction. A sparse representation theory is introduced into the problem of the nearest neighbor selection. Based on the sparse representation of super-resolution image reconstruction method, a super-resolution image reconstruction algorithm based on multi-class dictionary is analyzed. This method avoids the redundancy problem of only training a hyper complete dictionary, and makes the sub-dictionary more representatives, and then replaces the traditional Euclidean distance computing method to improve the quality of the whole image reconstruction. In addition, the ill-posed problem is introduced into non-local self-similarity regularization. Experimental results show that the algorithm is much better results than state-of-the-art algorithm in terms of both PSNR and visual perception.

2.5D Multi-View Gait Recognition Based on Point Cloud Registration

Science.gov (United States)

Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

2014-01-01

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM. PMID:24686727

Space- and Ground-based Coronal Spectro-Polarimetry

Science.gov (United States)

Fineschi, Silvano; Bemporad, Alessandro; Rybak, Jan; Capobianco, Gerardo

This presentation gives an overview of the near-future perspectives of ultraviolet and visible-light spectro-polarimetric instrumentation for probing coronal magnetism from space-based and ground-based observatories. Spectro-polarimetric imaging of coronal emission-lines in the visible-light wavelength-band provides an important diagnostics tool of the coronal magnetism. The interpretation in terms of Hanle and Zeeman effect of the line-polarization in forbidden emission-lines yields information on the direction and strength of the coronal magnetic field. As study case, this presentation will describe the Torino Coronal Magnetograph (CorMag) for the spectro-polarimetric observation of the FeXIV, 530.3 nm, forbidden emission-line. CorMag - consisting of a Liquid Crystal (LC) Lyot filter and a LC linear polarimeter - has been recently installed on the Lomnicky Peak Observatory 20cm Zeiss coronagraph. The preliminary results from CorMag will be presented. The linear polarization by resonance scattering of coronal permitted line-emission in the ultraviolet (UV)can be modified by magnetic fields through the Hanle effect. Space-based UV spectro-polarimeters would provide an additional tool for the disgnostics of coronal magnetism. As a case study of space-borne UV spectro-polarimeters, this presentation will describe the future upgrade of the Sounding-rocket Coronagraphic Experiment (SCORE) to include the capability of imaging polarimetry of the HI Lyman-alpha, 121.6 nm. SCORE is a multi-wavelength imager for the emission-lines, HeII 30.4 nm and HI 121.6 nm, and visible-light broad-band emission of the polarized K-corona. SCORE has flown successfully in 2009. This presentation will describe how in future re-flights SCORE could observe the expected Hanle effect in corona with a HI Lyman-alpha polarimeter.

The image of public space on planned housing based on environmental and behavior cognition mapping (case study: Cemara Asri Estate)

Science.gov (United States)

Nirfalini Aulia, Dwira; Zahara, Aina

2018-03-01

Public spaces in a planned housing is a place of social interaction for every visitor of public space. The research on public space image uses four public spaces that meet the criteria of public space such as pedestrian sidewalks, public park, water front and worship place. Research on the perception of public space is interesting to investigate because housing development is part of the forming of a society that should design with proper architectural considerations. The purpose of this research is to know the image of public space on the planned housing in Medan City based on the mapping of environmental and behavior cognition and to know the difference between the image that happened to four group respondent. The research method of architecture used in this research is a descriptive qualitative method with case study approach (most similar case). Analysis of data used using mental maps and questionnaires. Then the image of public space is formed based on the elements of public space, wayfinding, route choice, and movement. The image difference that occurs to the housing residents and architecture students, design and planning are outstanding, visitors to the public housing space is good, people who have never visited the public space is inadequate.

Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

Science.gov (United States)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

2006-03-01

Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

International Nuclear Information System (INIS)

Zhao, Tingting; Ruan, Dan

2016-01-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation. (paper)

Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

Science.gov (United States)

Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

2017-06-01

This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

Toward Microsatellite Based Space Situational Awareness

Science.gov (United States)

Scott, L.; Wallace, B.; Sale, M.; Thorsteinson, S.

2013-09-01

The NEOSSat microsatellite is a dual mission space telescope which will perform asteroid detection and Space Situational Awareness (SSA) observation experiments on deep space, earth orbiting objects. NEOSSat was launched on 25 February 2013 into a 800 dawn-dusk sun synchronous orbit and is currently undergoing satellite commissioning. The microsatellite consists of a small aperture optical telescope, GPS receiver, high performance attitude control system, and stray light rejection baffle designed to reject stray light from the Sun while searching for asteroids with elongations 45 degrees along the ecliptic. The SSA experimental mission, referred to as HEOSS (High Earth Orbit Space Surveillance), will focus on objects in deep space orbits. The HEOSS mission objective is to evaluate the utility of microsatellites to perform catalog maintenance observations of resident space objects in a manner consistent with the needs of the Canadian Forces. The advantages of placing a space surveillance sensor in low Earth orbit are that the observer can conduct observations without the day-night interruption cycle experienced by ground based telescopes, the telescope is insensitive to adverse weather and the system has visibility to deep space resident space objects which are not normally visible from ground based sensors. Also, from a photometric standpoint, the microsatellite is able to conduct observations on objects with a rapidly changing observer position. The possibility of spin axis estimation on geostationary satellites may be possible and an experiment characterize spin axis of distant resident space objects is being planned. Also, HEOSS offers the ability to conduct observations of satellites at high phase angles which can potentially extend the trackable portion of space in which deep space objects' orbits can be monitored. In this paper we describe the HEOSS SSA experimental data processing system and the preliminary findings of the catalog maintenance experiments

Multi-sensor image fusion and its applications

CERN Document Server

Blum, Rick S

2005-01-01

Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies.After a review of state-of-the-art image fusion techniques,

Many-core computing for space-based stereoscopic imaging

Science.gov (United States)

McCall, Paul; Torres, Gildo; LeGrand, Keith; Adjouadi, Malek; Liu, Chen; Darling, Jacob; Pernicka, Henry

The potential benefits of using parallel computing in real-time visual-based satellite proximity operations missions are investigated. Improvements in performance and relative navigation solutions over single thread systems can be achieved through multi- and many-core computing. Stochastic relative orbit determination methods benefit from the higher measurement frequencies, allowing them to more accurately determine the associated statistical properties of the relative orbital elements. More accurate orbit determination can lead to reduced fuel consumption and extended mission capabilities and duration. Inherent to the process of stereoscopic image processing is the difficulty of loading, managing, parsing, and evaluating large amounts of data efficiently, which may result in delays or highly time consuming processes for single (or few) processor systems or platforms. In this research we utilize the Single-Chip Cloud Computer (SCC), a fully programmable 48-core experimental processor, created by Intel Labs as a platform for many-core software research, provided with a high-speed on-chip network for sharing information along with advanced power management technologies and support for message-passing. The results from utilizing the SCC platform for the stereoscopic image processing application are presented in the form of Performance, Power, Energy, and Energy-Delay-Product (EDP) metrics. Also, a comparison between the SCC results and those obtained from executing the same application on a commercial PC are presented, showing the potential benefits of utilizing the SCC in particular, and any many-core platforms in general for real-time processing of visual-based satellite proximity operations missions.

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

Science.gov (United States)

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

Direct image reconstruction with limited angle projection data for computerized tomography

International Nuclear Information System (INIS)

Inouye, T.

1980-01-01

Discussions are made on the minimum angle range for projection data necessary to reconstruct the complete CT image. As is easily shown from the image reconstruction theorem, the lack of projection angle provides no data for the Fourier transformed function of the object on the corresponding angular directions, where the projections are missing. In a normal situation, the Fourier transformed function of an object image holds an analytic characteristic with respect to two-dimensional orthogonal parameters. This characteristic enables uniquely prolonging the function outside the obtained region employing a sort of analytic continuation with respect to both parameters. In the method reported here, an object pattern, which is confined within a finite range, is shifted to a specified region to have complete orthogonal function expansions without changing the projection angle directions. These orthogonal functions are analytically extended to the missing projection angle range and the whole function is determined. This method does not include any estimation process, whose effectiveness is often seriously jeopardized by the presence of a slight fluctuation component. Computer simulations were carried out to demonstrate the effectiveness of the method

Multi-look polarimetric SAR image filtering using simulated annealing

DEFF Research Database (Denmark)

Schou, Jesper

2000-01-01

Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

Dark-field image contrast in transmission scanning electron microscopy: Effects of substrate thickness and detector collection angle

Energy Technology Data Exchange (ETDEWEB)

Woehl, Taylor, E-mail: tjwoehl@umd.edu; Keller, Robert

2016-12-15

An annular dark field (ADF) detector was placed beneath a specimen in a field emission scanning electron microscope operated at 30 kV to calibrate detector response to incident beam current, and to create transmission images of gold nanoparticles on silicon nitride (SiN) substrates of various thicknesses. Based on the linear response of the ADF detector diodes to beam current, we developed a method that allowed for direct determination of the percentage of that beam current forward scattered to the ADF detector from the sample, i.e. the transmitted electron (TE) yield. Collection angles for the ADF detector region were defined using a masking aperture above the detector and were systematically varied by changing the sample to detector distance. We found the contrast of the nanoparticles, relative to the SiN substrate, decreased monotonically with decreasing inner exclusion angle and increasing substrate thickness. We also performed Monte Carlo electron scattering simulations, which showed quantitative agreement with experimental contrast associated with the nanoparticles. Together, the experiments and Monte Carlo simulations revealed that the decrease in contrast with decreasing inner exclusion angle was due to a rapid increase in the TE yield of the low atomic number substrate. Nanoparticles imaged at low inner exclusion angles (<150 mrad) and on thick substrates (>50 nm) showed low image contrast in their centers surrounded by a bright high-contrast halo on their edges. This complex image contrast was predicted by Monte Carlo simulations, which we interpreted in terms of mixing of the nominally bright field (BF) and ADF electron signals. Our systematic investigation of inner exclusion angle and substrate thickness effects on ADF t-SEM imaging provides fundamental understanding of the contrast mechanisms for image formation, which in turn suggest practical limitations and optimal imaging conditions for different substrate thicknesses. - Highlights: • Developed a

Anterior Segment Imaging Predicts Incident Gonioscopic Angle Closure.

Science.gov (United States)

Baskaran, Mani; Iyer, Jayant V; Narayanaswamy, Arun K; He, Yingke; Sakata, Lisandro M; Wu, Renyi; Liu, Dianna; Nongpiur, Monisha E; Friedman, David S; Aung, Tin

2015-12-01

To investigate the incidence of gonioscopic angle closure after 4 years in subjects with gonioscopically open angles but varying degrees of angle closure detected on anterior segment optical coherence tomography (AS OCT; Visante; Carl Zeiss Meditec, Dublin, CA) at baseline. Prospective, observational study. Three hundred forty-two subjects, mostly Chinese, 50 years of age or older, were recruited, of whom 65 were controls with open angles on gonioscopy and AS OCT at baseline, and 277 were cases with baseline open angles on gonioscopy but closed angles (1-4 quadrants) on AS OCT scans. All subjects underwent gonioscopy and AS OCT at baseline (horizontal and vertical single scans) and after 4 years. The examiner performing gonioscopy was masked to the baseline and AS OCT data. Angle closure in a quadrant was defined as nonvisibility of the posterior trabecular meshwork by gonioscopy and visible iridotrabecular contact beyond the scleral spur in AS OCT scans. Gonioscopic angle closure in 2 or 3 quadrants after 4 years. There were no statistically significant differences in age, ethnicity, or gender between cases and controls. None of the control subjects demonstrated gonioscopic angle closure after 4 years. Forty-eight of the 277 subjects (17.3%; 95% confidence interval [CI], 12.8-23; P < 0.0001) with at least 1 quadrant of angle closure on AS OCT at baseline demonstrated gonioscopic angle closure in 2 or more quadrants, whereas 28 subjects (10.1%; 95% CI, 6.7-14.6; P < 0.004) demonstrated gonioscopic angle closure in 3 or more quadrants after 4 years. Individuals with more quadrants of angle closure on baseline AS OCT scans had a greater likelihood of gonioscopic angle closure developing after 4 years (P < 0.0001, chi-square test for trend for both definitions of angle closure). Anterior segment OCT imaging at baseline predicts incident gonioscopic angle closure after 4 years among subjects who have gonioscopically open angles and iridotrabecular contact on AS OCT at

Application of Multi-Source Remote Sensing Image in Yunnan Province Grassland Resources Investigation

Science.gov (United States)

Li, J.; Wen, G.; Li, D.

2018-04-01

Trough mastering background information of Yunnan province grassland resources utilization and ecological conditions to improves grassland elaborating management capacity, it carried out grassland resource investigation work by Yunnan province agriculture department in 2017. The traditional grassland resource investigation method is ground based investigation, which is time-consuming and inefficient, especially not suitable for large scale and hard-to-reach areas. While remote sensing is low cost, wide range and efficient, which can reflect grassland resources present situation objectively. It has become indispensable grassland monitoring technology and data sources and it has got more and more recognition and application in grassland resources monitoring research. This paper researches application of multi-source remote sensing image in Yunnan province grassland resources investigation. First of all, it extracts grassland resources thematic information and conducts field investigation through BJ-2 high space resolution image segmentation. Secondly, it classifies grassland types and evaluates grassland degradation degree through high resolution characteristics of Landsat 8 image. Thirdly, it obtained grass yield model and quality classification through high resolution and wide scanning width characteristics of MODIS images and sample investigate data. Finally, it performs grassland field qualitative analysis through UAV remote sensing image. According to project area implementation, it proves that multi-source remote sensing data can be applied to the grassland resources investigation in Yunnan province and it is indispensable method.

Continuous imaging space in three-dimensional integral imaging

International Nuclear Information System (INIS)

Zhang Lei; Yang Yong; Wang Jin-Gang; Zhao Xing; Fang Zhi-Liang; Yuan Xiao-Cong

2013-01-01

We report an integral imaging method with continuous imaging space. This method simultaneously reconstructs real and virtual images in the virtual mode, with a minimum gap that separates the entire imaging space into real and virtual space. Experimental results show that the gap is reduced to 45% of that in a conventional integral imaging system with the same parameters. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Image Enhancement In HSI Space Using Wavelet Transform

Science.gov (United States)

Bansal, Sonia; Malhotra, Deepti

2010-11-01

Image processing modifies images to improve them (enhancement, restoration), extract information (analysis, recognition), and change their structure (composition, image editing). Image Enhancement is simple and most appealing area among all the digital image processing techniques. The main purpose of image enhancement is to bring out detail that is hidden in an image or to increase contrast in a low contrast image [1]. The color restoration functions of some real color image enhancement algorithms are greatly at random and not proved , and the real color images enhanced which are based on illumination-reflectance model have the loss of details and the `halos', we proposed a new algorithm to overcome these disadvantages. Firstly, we transform the real color image from RGB space to HSI space which is approximately orthonormal system. Secondly, the illumination and the reflectance of value are separated by homomorphic filtering based on illumination-reflectance model. We have discovered that the high dynamic range of image including high bright lights is mainly caused by the reflectance. Thirdly, the details of reflectance are preserved by wavelet transform. Fourthly, the dynamic range of reflectance is compressed by Butterworth filtering. Lastly, the energy of the saturation of real color image in HSI space is attenuated according to the spectral sensitivity of most human vision.

Deblurring sequential ocular images from multi-spectral imaging (MSI) via mutual information.

Science.gov (United States)

Lian, Jian; Zheng, Yuanjie; Jiao, Wanzhen; Yan, Fang; Zhao, Bojun

2018-06-01

Multi-spectral imaging (MSI) produces a sequence of spectral images to capture the inner structure of different species, which was recently introduced into ocular disease diagnosis. However, the quality of MSI images can be significantly degraded by motion blur caused by the inevitable saccades and exposure time required for maintaining a sufficiently high signal-to-noise ratio. This degradation may confuse an ophthalmologist, reduce the examination quality, or defeat various image analysis algorithms. We propose an early work specially on deblurring sequential MSI images, which is distinguished from many of the current image deblurring techniques by resolving the blur kernel simultaneously for all the images in an MSI sequence. It is accomplished by incorporating several a priori constraints including the sharpness of the latent clear image, the spatial and temporal smoothness of the blur kernel and the similarity between temporally-neighboring images in MSI sequence. Specifically, we model the similarity between MSI images with mutual information considering the different wavelengths used for capturing different images in MSI sequence. The optimization of the proposed approach is based on a multi-scale framework and stepwise optimization strategy. Experimental results from 22 MSI sequences validate that our approach outperforms several state-of-the-art techniques in natural image deblurring.

Multi-image Matching of Airborne SAR Imagery by SANCC

Directory of Open Access Journals (Sweden)

DING Hao

2015-03-01

Full Text Available In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SARimages effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system. The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.

Low flip angle spin-echo MR imaging to obtain better Gd-DTPA enhanced imaging with ECG gating