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1

4-D Display Of Satellite Cloud Images  

NASA Astrophysics Data System (ADS)

A technique has been developed to display GOES satellite cloud images in perspective over a topographical map. Cloud heights are estimated using temperatures from an infrared (IR) satellite image, surface temperature observations, and a climatological model of vertical temperature profiles. Cloud levels are discriminated from each other and from the ground using a pattern recognition algorithm based on the brightness variance technique of Coakley and Bretherton. The cloud regions found by the pattern recognizer are rendered in three-dimensional perspective over a topographical map by an efficient remap of the visible image. The visible shades are mixed with an artificial shade based on the geometry of the cloud-top surface, in order to enhance the texture of the cloud top.

Hibbard, William L.

1988-01-01

2

Identifying Cloud computing usage patterns  

Microsoft Academic Search

The current end-users who are developing Cloud-based applications are struggling with multiple solutions for application programming interfaces (APIs) coming from different providers. This fact is partially a consequence of the focus of these APIs on the service provider expectations not on the end-user requirements. In the design of a generic API for Cloud application development, the first step should be

Dana Petcu

2010-01-01

3

Automatic cloud detection on high resolution images  

Microsoft Academic Search

Remote sensing optical images are often cloudy and then partially unusable. Thus, cloud detection can optimize the image acquisition loop and the end-user image selection. The current pre-processing of SPOT images includes an automatic cloud and snow detection algorithm based on neural networks and fuzzy logic, which globally provides correct cloud masks but with a perfectible confidence. This process must

Ch. Panem; S. Baillarin; C. Latry; H. Vadon; P. Dejean

2005-01-01

4

Cloud computing in medical imaging.  

PubMed

Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing. PMID:23822402

Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

2013-07-01

5

Jupiter's Great Red Spot: Fine-scale matches of model vorticity patterns to prevailing cloud patterns  

NASA Astrophysics Data System (ADS)

We report on a set of six new matches between fine-scale features in the vorticity field of a three-dimensional (3D), primitive-equation, finite-difference model of Jupiter's Great Red Spot that includes no clouds or cloud physics, and quasi-permanent structures in reflected visible-band images of the clouds. These add to similar success by Cho et al. (Cho, J., de la Torre Juárez, M., Ingersoll, A.P., Dritschel, D.G. [2001]. J. Geophys. Res. 106, 5099-5106), who earlier captured four characteristic features of the GRS, also reproduced here, using a 3D quasi-geostrophic, cloud-free contour-dynamics model. In that study and this, the key enabling model attribute is sufficient horizontal resolution, rather than the moist-convective and cloud-microphysics processes often required to match the patterns of clouds in terrestrial hurricanes. The only significant feature that these dry models do not capture is the episodic moist-convective plumes seen in the northwest quadrant adjacent to the GRS. We initialize with Jupiter's averaged zonal winds plus an approximately balanced, smooth 3D ellipsoidal anticyclone. The threshold horizontal grid-resolution to obtain the fine-scale matches is approximately ?y/Ld ? 0.15, where ?y ? 300 km is the meridional grid spacing and Ld ˜ 2000 km the Rossby deformation length. For models with this or finer horizontal resolution, the best correspondence with observations is reached after about six vortex turnaround times from initialization (˜30 Earth days), but good facsimiles of nearly all the studied features appear after only 1.5 turnaround times (˜7-8 days). We conclude that in images of Jupiter, it is not accurate to associate clouds with upward motion, since these dry models reproduce the observed cloud patterns without this association, and indeed the synoptic-scale vertical motions in the model, as well as those deduced from observations, do not at all correspond to the observed cloud patterns. Instead, Jupiter's cloud-top patterns indicate the effects of local shear in the manner of passive-tracer fields. As a corollary, the water clouds on Jupiter, which lie unseen below its visible clouds, are the only ones on the planet likely to correlate with upwelling in the manner that clouds do on Earth. The next step is to extend studies such as this past the reflected visible band, for example to include the GRS's 5-?m emission bright collar, which may require the inclusion of cloud physics to enable the successful simulation of large voids.

Morales-Juberías, Raúl; Dowling, Timothy E.

2013-07-01

6

Pattern recognition of satellite cloud imagery for improved weather prediction  

NASA Technical Reports Server (NTRS)

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

7

Synthetic IR Cloud Image Model  

NASA Astrophysics Data System (ADS)

The presence of clouds affects most infrared (IR) military sensors. Foreground clouds degrade or occult target signatures and background clouds clutter a scene. Models used to assess or predict system performance must include important features of clouds: absorption, single and multiple scattering, thermal emission, partial transmission and spatial non-uniformity. Exact models which account for the details of cloud microphysics require large computation times and inputs which are difficult to obtain. Aerodyne has developed an approximate model which produces realistic cloud scenes in a reasonable amount of computer time. An average optical depth for the cloud is first calculated by use of LOWTRAN6 with specified aerosol optical properties. These properties are combined with a multiple scattering model which uses a two stream approximation. This model assumes that 1) the cloud layer is a parallel plane and infinite, 2) there is a constant single scattering albedo which may be wavelength dependent, 3) there is local thermodynamic equilibrium between particles and atmospheric gases, and 4) there is a uniform cloud temperature and emissivity. The result is an average cloud radiance spectrum along a specified line-of-sight. The line-of-sight may be up-looking or down-looking, and up to two cloud layers may be present. Spatial non-uniformities are incorporated by use of a cloud texture model based on a 1/f spectral shaping of spatial variations. The final scene including the effect of the atmospheric path from the cloud to the observer is in-band integrated and recorded as a grid of radiances with an associated depth map for use in a target/background interface model.

Conant, J.; Dvore, D.; Gruninger, J.

1988-08-01

8

CEDIMS: cloud ethical DICOM image Mojette storage  

NASA Astrophysics Data System (ADS)

Dicom images of patients will necessarily been stored in Clouds. However, ethical constraints must apply. In this paper, a method which provides the two following conditions is presented: 1) the medical information is not readable by the cloud owner since it is distributed along several clouds 2) the medical information can be retrieved from any sufficient subset of clouds In order to obtain this result in a real time processing, the Mojette transform is used. This paper reviews the interesting features of the Mojette transform in terms of information theory. Since only portions of the original Dicom files are stored into each cloud, their contents are not reachable. For instance, we use 4 different public clouds to save 4 different projections of each file, with the additional condition that any 3 over 4 projections are enough to reconstruct the original file. Thus, even if a cloud is unavailable when the user wants to load a Dicom file, the other 3 are giving enough information for real time reconstruction. The paper presents an implementation on 3 actual clouds. For ethical reasons, we use a Dicom image spreaded over 3 public clouds to show the obtained confidentiality and possible real time recovery.

Guédon, Jeanpierre; Evenou, Pierre; Tervé, Pierre; David, Sylvain; Béranger, Jérome

2012-02-01

9

Global patterns of cloud optical thickness variation with temperature  

NASA Technical Reports Server (NTRS)

The International Satellite Cloud Climatology Project dataset is used to correlate variations of cloud optical thickness and cloud temperature in today's atmosphere. The analysis focuses on low clouds in order to limit the importance of changes in cloud vertical extent, particle size, and water phase. Coherent patterns of change are observed on several time and space scales. On the planetary scale, clouds in colder, higher latitudes are found to be optically thicker than clouds in warmer, lower latitudes. On the seasonal scale, winter clouds are, for the most part, optically thicker than summer clouds. The logarithmic derivative of cloud optical thickness with temperature is used to describe the sign and magnitude of the optical thickness-temperature correlation. The seasonal, latitudinal, and day-to-day variations of this relation are examined for Northern Hemisphere clouds in 1984. In cold continental clouds, optical thickness increases with temperature, consistent with the temperature variation of the adiabatic cloud water content. In warm continental and in almost all maritime clouds, however, optical thickness decreases with temperature.

Tselioudis, George; Rossow, William B.; Rind, David

1992-01-01

10

Male pattern baldness (image)  

MedlinePLUS

Male pattern baldness is a sex-linked characteristic that is passed from mother to child. A man can more accurately predict his chances of developing male pattern baldness by observing his mother's father than by looking ...

11

Oblique view of cloud patterns over Pacific Ocean  

NASA Technical Reports Server (NTRS)

An oblique view of unique cloud patterns over the Pacific Ocean caused by aircraft contrail shadows altering cumulus clouds and forming straight line clouds, as photographed from the Apollo spacecraft in Earth orbit during the joint U.S.-USSR Apollo Soyuz Test Project (ASTP) mission. This area is southwest of Los Angeles, California. This photograph was taken at an altitude of 177 kilometers (110 statute miles).

1975-01-01

12

Global patterns of cloud optical thickness variation with temperature  

NASA Technical Reports Server (NTRS)

A global cloud climatology dataset is used to study patterns of cloud optical thickness variation with temperature. The data, which cover the period from July 1983 through June 1995, contain detailed information on the distribution of cloud radiative properties and their diurnal and seasonal variations, as well as information on the vertical distribution of temperature and humidity in the troposphere. For cold low clouds over land, the temperature coefficient of change in optical thickness has a value of about 0.04, which is similar to that deduced from Soviet aircraft observations and derived from thermodynamic considerations for the change of cloud liquid water with temperature. It is suggested that, in this cold-temperature range, cloud optical thickness variations are dominated by changes in the liquid water content of the cloud and that the liquid water content changes in accordance with the thermodynamic theory.

Tselioudis, George; Rind, David; Rossow, William B.

1990-01-01

13

Infrared Image of Low Clouds on Venus  

NASA Technical Reports Server (NTRS)

This false-color image is a near-infrared map of lower-level clouds on the night side of Venus, obtained by the Near Infrared Mapping Spectrometer aboard the Galileo spacecraft as it approached the planet's night side on February 10, 1990. Bright slivers of sunlit high clouds are visible above and below the dark, glowing hemisphere. The spacecraft is about 100,000 kilometers (60,000 miles) above the planet. An infrared wavelength of 2.3 microns (about three times the longest wavelength visible to the human eye) was used. The map shows the turbulent, cloudy middle atmosphere some 50-55 kilometers (30- 33 miles) above the surface, 10-16 kilometers or 6-10 miles below the visible cloudtops. The red color represents the radiant heat from the lower atmosphere (about 400 degrees Fahrenheit) shining through the sulfuric acid clouds, which appear as much as 10 times darker than the bright gaps between clouds. This cloud layer is at about -30 degrees Fahrenheit, at a pressure about 1/2 Earth's surface atmospheric pressure. Near the equator, the clouds appear fluffy and blocky; farther north, they are stretched out into East-West filaments by winds estimated at more than 150 mph, while the poles are capped by thick clouds at this altitude.

1993-01-01

14

Spatial and Temporal Patterns of Aerosol-Cloud Interactions  

NASA Astrophysics Data System (ADS)

This study determines the spatial and temporal distribution of regions with frequent aerosol-cloud interactions (aci) and identifies their meteorological determinants based on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) and ECMWF (European Centre for Medium-Range Weather Forecasts) data products. Atmospheric aerosols influence the microphysical structure of clouds, while both also respond to meteorological conditions. The potential radiative adjustments to changes in a cloud system associated with aerosol-cloud interactions are grouped and termed as effective radiative forcing due to aerosol-cloud interactions (ERFaci). It is difficult to distinguish, to what extent radiative forcing and precipitation patterns of clouds are a result of cloud feedbacks to aerosols or the existing meteorological conditions. A complete understanding of aerosol-cloud-meteorology interactions is crucial as the uncertainty range of ERFaci in climate change modeling could be significantly reduced. In the present study it is suggested that presence of hydrated aerosols is an implication for aci. Knowledge of their vertical and horizontal distribution and frequency over the globe would be important for understanding ERFaci. To identify regions with aerosol-cloud transitions the CAD score (cloud-aerosol discrimination) of the CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) instrument on the CALIPSO satellite is used. It separates aerosols and clouds according to the probability distribution functions of 5 parameters (attenuated backscatter, total color ratio, volume depolarization ratio, altitude and latitude) and assigns the likelihood of cloud or aerosol presence. This parameter is used to calculate relative frequencies of aci on a global scale from 2006 to 2013.

Fuchs, Julia; Cermak, Jan

2014-05-01

15

Image Mining: Detecting Deforestation Patterns  

E-print Network

54 Chapter IV Image Mining: Detecting Deforestation Patterns Through Satellites Marcelino Pereira to analyze satellite images and extract knowledge from this kind of data. The Amazonia deforestation problem of change on deforested areas of Amazonia. The purpose of the authors is to present relevant technologies

Camara, Gilberto

16

Building depth images from scattered point cloud  

NASA Astrophysics Data System (ADS)

With the equation of plane and sphere, we fit them with Linear Least Squares. To cylinder datum fitting, firstly parameterize GQS equation of cylinder from seven parameters to five parameters, then using Local Paraboloid Construct method based on coordinate translation to get fitting initial values, finally evaluate results by Levenberg-Marquardt--a Nonlinear Linear Least Squares. Algorithm. However, initial values with Local Paraboloid Construct method are unstable. So to improve the precision of cylinder fitting ,a robust cylinder fitting method is put forward, which at first gets initial cylinder parameter values by Gauss Image, then fits cylinder by Nonlinear Least Squares for parameterized distance function. After getting reference datums, this paper proposes the methods of creating depth images from scattered point cloud and the specific steps with reference to different datums. Finally we choose some point cloud data of ancient building components from laser scanning data of Forbidden City in China as experiment data. Experiment results demonstrate the stability and high precision of the method of plane, cylinder and sphere fitting as well as the validity of depth images to represent point cloud of object.

Wei, Shuangfeng; Chen, Hong

2009-10-01

17

MISR Stereo Imaging Distinguishes Smoke from Cloud  

NASA Technical Reports Server (NTRS)

These views of western Alaska were acquired by MISR on June 25, 2000 during Terra orbit 2775. The images cover an area of about 150 kilometers x 225 kilometers, and have been oriented with north to the left. The left image is from the vertical-viewing (nadir) camera, whereas the right image is a stereo 'anaglyph' that combines data from the forward-viewing 45-degree and 60-degree cameras. This image appears three-dimensional when viewed through red/blue glasses with the red filter over the left eye. It may help to darken the room lights when viewing the image on a computer screen.

The Yukon River is seen wending its way from upper left to lower right. A forest fire in the Kaiyuh Mountains produced the long smoke plume that originates below and to the right of image center. In the nadir view, the high cirrus clouds at the top of the image and the smoke plume are similar in appearance, and the lack of vertical information makes them hard to differentiate. Viewing the righthand image with stereo glasses, on the other hand, demonstrates that the scene consists of several vertically-stratified layers, including the surface terrain, the smoke, some scattered cumulus clouds, and streaks of high, thin cirrus. This added dimensionality is one of the ways MISR data helps scientists identify and classify various components of terrestrial scenes.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

2000-01-01

18

Short-term forecasting of cloud images using local features  

NASA Astrophysics Data System (ADS)

Short-term forecasting of cloud distribution within a sequence of all-sky images is an important issue in meteorological area. In this work, a cloud image forecasting system is designed, which includes three steps---cloud detection, cloud matching and motion estimation. We treat cloud detection as a classification problem based on Linear Discriminant Analysis. During the matching, a set of Speed Up Robust Features (SURF) are extracted to represent the cloud, then clouds are matched by computing correspondences between SURF features. Finally, affine transform is applied to estimate the motion of cloud. This local features based method is capable of predicting the rotation and scaling of cloud, while the traditional method is only limited to translational motion. Objective evaluation results show higher accuracy of the proposed method compared with some other algorithms.

Jiang, Wenhui; Su, Fei; Zhang, Jun

2014-01-01

19

Capturing and analyzing wheelchair maneuvering patterns with mobile cloud computing.  

PubMed

Power wheelchairs have been widely used to provide independent mobility to people with disabilities. Despite great advancements in power wheelchair technology, research shows that wheelchair related accidents occur frequently. To ensure safe maneuverability, capturing wheelchair maneuvering patterns is fundamental to enable other research, such as safe robotic assistance for wheelchair users. In this study, we propose to record, store, and analyze wheelchair maneuvering data by means of mobile cloud computing. Specifically, the accelerometer and gyroscope sensors in smart phones are used to record wheelchair maneuvering data in real-time. Then, the recorded data are periodically transmitted to the cloud for storage and analysis. The analyzed results are then made available to various types of users, such as mobile phone users, traditional desktop users, etc. The combination of mobile computing and cloud computing leverages the advantages of both techniques and extends the smart phone's capabilities of computing and data storage via the Internet. We performed a case study to implement the mobile cloud computing framework using Android smart phones and Google App Engine, a popular cloud computing platform. Experimental results demonstrated the feasibility of the proposed mobile cloud computing framework. PMID:24110214

Fu, Jicheng; Hao, Wei; White, Travis; Yan, Yuqing; Jones, Maria; Jan, Yih-Kuen

2013-01-01

20

Cloud Imagers Offer New Details on Earth's Health  

NASA Technical Reports Server (NTRS)

A stunning red sunset or purple sunrise is an aesthetic treat with a scientific explanation: The colors are a direct result of the absorption or reflectance of solar radiation by atmospheric aerosols, minute particles (either solid or liquid) in the Earth s atmosphere that occur both naturally and because of human activity. At the beginning or end of the day, the Sun s rays travel farther through the atmosphere to reach an observer s eyes and more green and yellow light is scattered, making the Sun appear red. Sunset and sunrise are especially colorful when the concentration of atmospheric particles is high. This ability of aerosols to absorb and reflect sunlight is not just pretty; it also determines the amount of radiation and heat that reaches the Earth s surface, and can profoundly affect climate. In the atmosphere, aerosols are also important as nuclei for the condensation of water droplets and ice crystals. Clouds with fewer aerosols cannot form as many water droplets (called cloud particles), and consequently, do not scatter light well. In this case, more sunlight reaches the Earth s surface. When aerosol levels in clouds are high, however, more nucleation points can form small liquid water droplets. These smaller cloud particles can reflect up to 90 percent of visible radiation to space, keeping the heat from ever reaching Earth s surface. The tendency for these particles to absorb or reflect the Sun s energy - called extinction by astronomers - depends on a number of factors, including chemical composition and the humidity and temperature in the surrounding air; because cloud particles are so small, they are affected quickly by minute changes in the atmosphere. Because of this sensitivity, atmospheric scientists study cloud particles to anticipate patterns and shifts in climate. Until recently, NASA s study of atmospheric aerosols and cloud particles has been focused primarily on satellite images, which, while granting large-scale atmospheric analysis, limited scientists ability to acquire detailed information about individual particles. Now, experiments with specialized equipment can be flown on standard jets, making it possible for researchers to monitor and more accurately anticipate changes in Earth s atmosphere and weather patterns.

2009-01-01

21

Concentric gravity waves in polar mesospheric clouds from the Cloud Imaging and Particle Size experiment  

NASA Astrophysics Data System (ADS)

concentric atmospheric gravity wave (AGW) events have been identified in Polar Mesospheric Cloud (PMC) images of the summer mesopause region (~82-84 km) made by the Cloud Imaging and Particle Size (CIPS) instrument on board the Aeronomy of Ice in the Mesosphere satellite during the Northern Hemisphere 2007 and 2009 PMC seasons. The AGWs modulate the PMC albedo, ice water content, and particle size, creating concentric ring patterns. On only one occasion (13 July 2007), the concentric AGWs in PMCs were aligned with AGWs with similar shapes observed in 4.3 µm radiance in the lower stratosphere, as measured by Atmospheric Infrared Sounder (AIRS). Coincident AIRS and Infrared Atmospheric Sounding Interferometer nadir measurements of 8.1 µm radiance reveal a region of deep convection in the troposphere close to the estimated centers of the AGWs in the stratosphere, strongly suggesting that convection is the wave source. The AGWs in CIPS on 13 July 2007 were ~1000 km away from the observed deep convection. Three other concentric AGWs in PMCs were 500-1000 km away from deep convection in the troposphere, while no convection was observed related to the wave on 29 July 2009. We perform a 2-D ray tracing study for the AGW event on 13 July 2007. The calculated propagation distance is much shorter than the distance between the AGWs in PMCs and the observed convection. The 2-D ray tracing study indicates that the AGWs in PMCs and in the stratosphere are probably excited by different tropospheric convective systems.

Yue, Jia; Thurairajah, Brentha; Hoffmann, Lars; Alexander, Joan; Chandran, Amal; Taylor, Michael J.; Russell, James M.; Randall, Cora E.; Bailey, Scott M.

2014-05-01

22

Data and image fusion for geometrical cloud characterization  

SciTech Connect

Clouds have a strong influence on the Earth`s climate and therefore on climate change. An important step in improving the accuracy of models that predict global climate change, general circulation models, is improving the parameterization of clouds and cloud-radiation interactions. Improvements in the next generation models will likely include the effect of cloud geometry on the cloud-radiation parameterizations. We have developed and report here methods for characterizing the geometrical features and three-dimensional properties of clouds that could be of significant value in developing these new parameterizations. We developed and report here a means of generating and imaging synthetic clouds which we used to test our characterization algorithms; a method for using Taylor`s hypotheses to infer spatial averages from temporal averages of cloud properties; a computer method for automatically classifying cloud types in an image; and a method for producing numerical three-dimensional renderings of cloud fields based on the fusion of ground-based and satellite images together with meteorological data.

Thorne, L.R.; Buch, K.A.; Sun, Chen-Hui; Diegert, C.

1997-04-01

23

Cloud Detection Method Based on Feature Extraction in Remote Sensing Images  

NASA Astrophysics Data System (ADS)

In remote sensing images, the existence of the clouds has a great impact on the image quality and subsequent image processing, as the images covered with clouds contain little useful information. Therefore, the detection and recognition of clouds is one of the major problems in the application of remote sensing images. Present there are two categories of method to cloud detection. One is setting spectrum thresholds based on the characteristics of the clouds to distinguish them. However, the instability and uncertainty of the practical clouds makes this kind of method complexity and weak adaptability. The other method adopts the features in the images to identify the clouds. Since there will be significant overlaps in some features of the clouds and grounds, the detection result is highly dependent on the effectiveness of the features. This paper presented a cloud detection method based on feature extraction for remote sensing images. At first, find out effective features through training pattern, the features are selected from gray, frequency and texture domains. The different features in the three domains of the training samples are calculated. Through the result of statistical analysis of all the features, the useful features are picked up to form a feature set. In concrete, the set includes three feature vectors, respectively, the gray feature vector constituted of average gray, variance, first-order difference, entropy and histogram, the frequency feature vector constituted of DCT high frequency coefficient and wavelet high frequency coefficient, and the texture feature vector constituted of the hybrid entropy and difference of the gray-gradient co-occurrence matrix and the image fractal dimension. Secondly, a thumbnail will be obtained by down sampling the original image and its features of gray, frequency and texture are computed. Last but not least, the cloud region will be judged by the comparison between the actual feature values and the thresholds determined by the sample training process. Experimental results show that the clouds and ground objects can be separated efficiently, and our method can implement rapid clouds detection and cloudiness calculation.

Changhui, Y.; Yuan, Y.; Minjing, M.; Menglu, Z.

2013-05-01

24

The qualitative analyses of cloud cover on optical satellite image  

Microsoft Academic Search

The remote sensing technology has become the important information source in environment investigation, Moreover, optical satellite images are the most important information source. Although the optical satellite images may provides high resolution, multi-spectral images and better vision images than active satellite, the disadvantage is affected by the atmospheric condition easily. In general, the cloud cover is the most common noise,

Chih-Heng Liu; Mei-Ling Yeh; Tine-Yin Chou; Lung-Shih Yang

2008-01-01

25

Contextual Spatiospectral Postreconstruction of Cloud-Contaminated Images  

Microsoft Academic Search

A general method has been proposed recently for the contextual reconstruction of cloud-contaminated areas in multitemporal multispectral images. It is based on the idea of making the prediction process learn from information available in the cloud-free neighborhood of contaminated areas. Though promising, this method does not fully exploit all available information, thus leaving room for further methodological enhancements. This letter

Souad Benabdelkader; Farid Melgani

2008-01-01

26

Image to Point Cloud Method of 3D-MODELING  

NASA Astrophysics Data System (ADS)

This article describes the method of constructing 3D models of objects (buildings, monuments) based on digital images and a point cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling.

Chibunichev, A. G.; Galakhov, V. P.

2012-07-01

27

Clouds  

NSDL National Science Digital Library

In this scenario-based, problem-based learning (PBL) activity, students investigate cloud formation, cloud classification, and the role of clouds in heating and cooling the Earth; how to interpret TRMM (Tropical Rainfall Measuring Mission) images and data; and the role clouds play in the Earth’s radiant budget and climate. Students assume the role of weather interns in a state climatology office and assist a frustrated student in a homework assignment. Learning is supported by a cloud in a bottle and an ice-albedo demonstration, a three-day cloud monitoring outdoor activity, and student journal assignments. The hands-on activities require two 2-liter soda bottles, an infrared heat lamp, and two thermometers. The resource includes a teacher's guide, questions and answer key, assessment rubric, glossary, and an appendix with information supporting PBL in the classroom.

28

Uneven cloud and fog removing for satellite remote sensing image  

Microsoft Academic Search

Haze is an important influence factor of visible light RS data's obtaining and using. Based on dark channel prior and haze image model, this paper studies the dehaze technology from a single satellite RS image. Aim at the characteristic of uneven cloud in satellite RS image and the problem of the unreasonable estimate for airlight in dehaze method, this paper

Liya Zhou; Zhiyuan Qin

2011-01-01

29

A Time-series Pattern based Noise Generation Strategy for Privacy Protection in Cloud Computing  

E-print Network

A Time-series Pattern based Noise Generation Strategy for Privacy Protection in Cloud Computing of Technology, Sydney Broadway, NSW, Australia 2007 Jinjun.Chen@uts.edu.au Abstract--Cloud computing promises of cloud computing security, there is a need to take special actions to protect privacy at client sides

Yang, Yun

30

Ultraviolet Imaging Polarimetry of the Large Magellanic Cloud. II. Models  

E-print Network

Motivated by new sounding-rocket wide-field polarimetric images of the Large Magellanic Cloud, we have used a three-dimensional Monte Carlo radiation transfer code to investigate the escape of near-ultraviolet photons from young stellar associations embedded within a disk of dusty material (i.e. a galaxy). As photons propagate through the disk, they may be scattered or absorbed by dust. Scattered photons are polarized and tracked until they escape to be observed; absorbed photons heat the dust, which radiates isotropically in the far-infrared, where the galaxy is optically thin. The code produces four output images: near- UV and far-IR flux, and near-UV images in the linear Stokes parameters Q and U. From these images we construct simulated UV polarization maps of the LMC. We use these maps to place constraints on the star + dust geometry of the LMC and the optical properties of its dust grains. By tuning the model input parameters to produce maps that match the observed polarization maps, we derive information about the inclination of the LMC disk to the plane of the sky, and about the scattering phase function g. We compute a grid of models with i = 28 deg., 36 deg., and 45 deg., and g = 0.64, 0.70, 0.77, 0.83, and 0.90. The model which best reproduces the observed polarization maps has i = 36 +2/-5 degrees and g ~0.7. Because of the low signal-to-noise in the data, we cannot place firm constraints on the value of g. The highly inclined models do not match the observed centro-symmetric polarization patterns around bright OB associations, or the distribution of polarization values. Our models approximately reproduce the observed ultraviolet photopolarimetry of the western side of the LMC; however, the output images depend on many input parameters and are nonunique.

Andrew A. Cole; Kenneth Wood; Kenneth H. Nordsieck

1999-09-08

31

A holistic image segmentation framework for cloud detection and extraction  

NASA Astrophysics Data System (ADS)

Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

2013-05-01

32

MY NASA DATA: Patterns in High Cloud Coverage  

NSDL National Science Digital Library

In this data analysis activity, Students will plot and analyze a time series of data for high cloud coverage from a specified location (home or school) and determine whether or not a seasonal pattern exists. The lesson includes step-by-step instructions for use of the MY NASA DATA Live Access Server (LAS), guiding students through selection of a data set from a location of their choice, importing the data into a spreadsheet, creating graphs, and analyzing data plots. The lesson provides detailed procedures, related links and sample graphs, follow-up questions, extensions, and teacher notes. Designed for student use, MY NASA DATA LAS samples micro datasets from large scientific data archives, and provides structured investigations engaging students in exploration of real data to answer real world questions.

33

Space Shuttle Video Images: An Example of Warm Cloud Lightning  

NASA Technical Reports Server (NTRS)

Warm cloud lightning has been reported in several tropical locations. We have been using the intensified monochrome TV cameras at night during a number of shuttle flights to observe large active thunderstorms and their associated lightning. During a nighttime orbital pass of the STS-70 mission on 17 July 1995 at 07:57:42 GMT, the controllers obtained video imagery of a small cloud that was producing lightning. Data from a GOES infrared image establishes that the cloud top had a temperature of about 271 degrees Kelvin ( -2 degrees Celsius). Since this cloud was electrified to the extent that a lightning discharge did occur, it may be another case of lightning in a cloud that presents little if any evidence of frozen or melting precipitation.

Vaughan, Otha H., Jr.; Boeck, William L.

1998-01-01

34

Designing SCIT Architecture Pattern in a Cloud-based Environment  

E-print Network

C-SCIT (Cloud- based Self-Cleansing Intrusion Tolerant) scheme that can provide enhanced intrusion. The main contribution of this paper is to design a Cloud- based Self-Cleansing Intrusion Tolerance (C

Sood, Arun K.

35

The design and implementation of Remote Sensing Images cloud processing software  

Microsoft Academic Search

To Study the Cloud Removal Method of High Resolution Remote Sensing Images, this paper integrated a few useful methods for removing cloud from remote sensing images and introduced a certain software for cloud removal by using MATLAB's graphical user interface (GUI) design features combined with its digital image processing and other functions. By testing its applications in remote sensing image

Shuang Cao; Xiaowen Hu; Wen Ma; Xiaohong Wu; Ruirui Guo

2011-01-01

36

Wide angle infrared cloud imaging for measuring cloud statistics in support of earth space optical communication  

NASA Astrophysics Data System (ADS)

Previous research at Montana State University led to the development of the Infrared Cloud Imager (ICI) for measuring downwelling cloud and sky thermal emission for producing cloud coverage statistics using radiometrically calibrated images of the sky. This technique, that was developed primarily for detection of clouds for studies of arctic climate, provides benefits over commonly used systems by producing localized high resolution data in comparison to satellites images, and, in contrast to visible systems, provides continuous day and night operation. As a continuation of the first effort, in collaboration with the Optical Communications Group at the NASA's Jet Propulsion Laboratory (JPL), here we present a new generation of the ICI that can be used to monitor the cloud coverage of a site that can house a ground telescope dedicated to Earth-space optical communication paths. This new instrument, based around the FLIR Photon camera, expands the field of view (FOV) from 20° to 50° (up to 100° in the latest version), reduces instrument size, reduces instrument cost, and extends the time between calibrations to hours instead of minutes. This has been accomplished by characterizing the changes in the output data for changes in the camera's internal temperature while viewing a constant source. Deployment of this instrument has taken place at JPL's Table Mountain facility, CA, and Bozeman, MT.

Nugent, Paul W.; Shaw, Joseph A.; Piazzolla, Sabino

2007-09-01

37

Jupiter's Cloud Structure from Galileo Imaging Data  

Microsoft Academic Search

The vertical structure of aerosols on Jupiter is inferred from data obtained by the NASA Galileo Solid State Imaging system during the first six orbits of the spacecraft. Images at 889 nm (a strong methane band), 727 nm (a weaker methane band), and 756 nm (continuum) taken at a variety of lighting and viewing angles are used. The images are

D. Banfield; P. J. Gierasch; M. Bell; E. Ustinov; A. P. Ingersoll; A. R. Vasavada; Robert A. West; M. J. S. Belton

1998-01-01

38

Enhanced IR imagery of cloud top temperatures, heights, cloud types and organizational patterns  

NSDL National Science Digital Library

Dorothea Ivanova, Embry-Riddle Aeronautical University Summary The object of this activity is to find enhanced IR imagery, to interpret cloud top temperatures and heights and to identify cloud types and ...

Dorothea Ivanova

39

Solar energy mapping by using cloud images received from GMS  

Microsoft Academic Search

Solar energy maps that indicate the wide-ranging spatial distribution of solar irradiation are required by the researchers of the solar power systems. However, the irradiation measurement networks at ground level are not enough to obtain reliable information of the solar energy distribution in the world. On the other hand, geostationary meteorological satellites (GMS) have provided the images of cloud fields

Kenji Otani; Tadashi Saitoh; I. Tsuda; K. Kurokawa

1994-01-01

40

Cloud Detection with the Earth Polychromatic Imaging Camera (EPIC)  

NASA Technical Reports Server (NTRS)

The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) would provide a unique opportunity for Earth and atmospheric research due not only to its Lagrange point sun-synchronous orbit, but also to the potential for synergistic use of spectral channels in both the UV and visible spectrum. As a prerequisite for most applications, the ability to detect the presence of clouds in a given field of view, known as cloud masking, is of utmost importance. It serves to determine both the potential for cloud contamination in clear-sky applications (e.g., land surface products and aerosol retrievals) and clear-sky contamination in cloud applications (e.g., cloud height and property retrievals). To this end, a preliminary cloud mask algorithm has been developed for EPIC that applies thresholds to reflected UV and visible radiances, as well as to reflected radiance ratios. This algorithm has been tested with simulated EPIC radiances over both land and ocean scenes, with satisfactory results. These test results, as well as algorithm sensitivity to potential instrument uncertainties, will be presented.

Meyer, Kerry; Marshak, Alexander; Lyapustin, Alexei; Torres, Omar; Wang, Yugie

2011-01-01

41

Multiscale image enhancement of chromosome banding patterns  

NASA Astrophysics Data System (ADS)

Visual examination of chromosome banding patterns is an important means of chromosome analysis. Cytogeneticists compare their patient's chromosome image against the prototype normal/abnormal human chromosome banding patterns. Automated chromosome analysis instruments facilitate this by digitally enhancing the chromosome images. Currently available systems employing traditional highpass/bandpass filtering and/or histogram equalization are approximately equivalent to photomicroscopy in their ability to support the detection of band pattern alterations. Improvements in chromosome image display quality, particularly in the detail of the banding pattern, would significantly increase the cost-effectiveness of these systems. In this paper we present our work on the use of multiscale transform and derivative filtering for image enhancement of chromosome banding patterns. A steerable pyramid representation of the chromosome image is generated by a multiscale transform. The derivative filters are designed to detect the bands of a chromosome, and the steerable pyramid transform is chosen based on its desirable properties of shift and rotation invariance. By processing the transform coefficients that correspond to the bands of the chromosome in the pyramid representation, contrast enhancement of the chromosome bands can be achieved with designed flexibility in scale, orientation and location. Compared with existing chromosome image enhancement techniques, this new approach offers the advantage of selective chromosome banding pattern enhancement that allows designated detail analysis. Experimental results indicate improved enhancement capabilities and promise more effective visual aid to comparison of chromosomes to the prototypes and to each other. This will increase the ability of automated chromosome analysis instruments to assist the evaluation of chromosome abnormalities in clinical samples.

Wu, Qiang; Castleman, Kenneth R.

1996-10-01

42

Watershed image segmentation and cloud classification from multispectral MSG-SEVIRI imagery.  

NASA Astrophysics Data System (ADS)

Clouds play an important role in the Earth's climate system, modulating the radiative energy budget. Consequently, a good knowledge of their radiative properties and of the spatial and temporal distribution of cloud cover is necessary. Earth observation satellites provide us with long time-series data on a global scale and they have become essential tools for the continuous monitoring of cloud properties. Thus, for example, ISCCP (International Satellite Cloud Climatology Project), ERBE (Earth Radiation Budget Experiment) or CERES (Clouds and the Earth s Radiant Energy System) projects have provided essential datasets to improve our understanding of the effects of atmospheric cloud radiative forcing on climate. The problem of cloud segmentation and classification from multispectral satellite imagery is considered in this work. Many methods, based on both supervised and unsupervised classi- fication, have been developed previously, but most of them are based on independent pixel processing. In this study, a segmentation algorithm is applied as a first step, in order to get a partition of the original image into a set of meaningful objects. This segmentation is performed through order-invariant watershed algorithms, based on immersion and toboggan approaches. The multi-scale gradient magnitude has been obtained using a multi-resolution morphological operator from spectral data and texture information, computed through fractal and local binary patterns (LBP) methods. To reduce the oversegmentation produced by the watershed technique, a fast region merging is applied, using region dissimilarity functions that takes into account internal and boundary features.Once the objects present in the image have been segmented, they are classified using a multi-threshold classification method based on physical considerations and radiative and texture features. The proposed technique is applied to MSG-SEVIRI multispectral data, including both daylight and nighttime images. This radiometer provides high quality images, every 15 minutes, with 3km resolution at nadir in 11 spectral bands, covering from visible to thermal infrared region. The optimal sets of spectral bands and texture features to obtain good segmentation and classification results are studied. Classification results are evaluated using different ground true data: MODIS cloud products, SAFNWC/MSG SEVIRI cloud data and manual human expert classification based on the visual inspection and other related information. Furthermore, the influence of spatial resolution has been investigated.

González, Albano; Mendez, Zebensui; Munoz, Jonathan; Perez, Juan C.; Armas Padilla, Montserrat

43

Patterns of shallow clouds and rainfall over the Amazon : climatic impacts of deforestation  

E-print Network

(cont.) and, to a lesser extent, cold cloud patterns over the Amazon. Through complex interactions, the results reported in this thesis may have important implications for the local ecosystem dynamics of the Amazon, for ...

Chagnon, Frédéric J. F. (Frédéric Jacques F.), 1975-

2005-01-01

44

Distortion of the HBT images by meson clouds  

E-print Network

We study the effects of mesonic final state interactions on the Hanbury Brown and Twiss (HBT) intensity interferometry for mesons in ultra-relativistic heavy ion collisions. Modification of the one-body amplitude of emitted mesons while going through a cloud of other mesons is estimated in the semiclassical approximation with a mesonic optical potential which incorporates both coherent forward scattering with other mesons and the absorption due to the incoherent scattering in the meson clouds. We show how these effects results in the distortion of the HBT images.

K. Hattori; T. Matsui

2009-09-11

45

Cloud based toolbox for image analysis, processing and reconstruction tasks.  

PubMed

This chapter describes a novel way of carrying out image analysis, reconstruction and processing tasks using cloud based service provided on the Australian National eResearch Collaboration Tools and Resources (NeCTAR) infrastructure. The toolbox allows users free access to a wide range of useful blocks of functionalities (imaging functions) that can be connected together in workflows allowing creation of even more complex algorithms that can be re-run on different data sets, shared with others or additionally adjusted. The functions given are in the area of cellular imaging, advanced X-ray image analysis, computed tomography and 3D medical imaging and visualisation. The service is currently available on the website www.cloudimaging.net.au . PMID:25381109

Bednarz, Tomasz; Wang, Dadong; Arzhaeva, Yulia; Lagerstrom, Ryan; Vallotton, Pascal; Burdett, Neil; Khassapov, Alex; Szul, Piotr; Chen, Shiping; Sun, Changming; Domanski, Luke; Thompson, Darren; Gureyev, Timur; Taylor, John A

2015-01-01

46

Recontruction of high resolution ocean colour images under clouds using neuronal methods  

NASA Astrophysics Data System (ADS)

Mesoscale and sub-mesoscale phytoplankton variability significantly contributes to global primary production budgets. High-resolution modelling studies suggest that incorrect representation of mesoscale and sub-mesoscale variability in ocean global circulation models (OGCM) can result in errors of about 30% in primary production estimations. Thus, characterizing mesoscale and sub-mesoscale phytoplankton variability is important for the parameterization and validation of the OGCM. Ocean colour sensors allow a global observation of small scale chlorophyll variability patterns. However, the frequent presence of clouds in ocean colour remotely sensed imagery, prevents space and time continuity and limits its exploitation. The aim of this study is to propose a new statistical processing approach for the reconstruction of areas covered by clouds in a time sequence ocean colour images. We used a classification methodology consisting in a neural network topological map. Considering a cloud-contaminated image of the sequence, missing data are reconstructed through an unsupervised statistical process that reproduces the local spatio temporal relationships of the cloudy image. The unsupervised process is trained with a selected subset of ocean colour temporal images surrounding the cloudy images. As phytoplankton variability is partly driven by oceanic dynamics, we added a set of satellite-derived dynamic ocean products (sea surface temperature, altimetry, ocean waves) influencing strongly the phytoplankton production. To develop the under cloud reconstruction method, we began by using high resolution (about 2 Km) simulated data (output of the OPA OGCM coupled with the Lobster biogechemical model). We focused on the North Atlantic ocean which is characterized by a strong mesoscale and sub-mesoscale phytoplankton variability. When applied over two seasons(spring and winter),the method was able to reproduce the statistical characteristics of the missing data with a good accuracy. We then tried to assess the ability of the method for reconstructing high resolution real data.

Manel, J.; Thiria, S.; Lévy, M.

2009-04-01

47

reconstruction of high resolution ocean colour images under clouds using neuronal methods  

NASA Astrophysics Data System (ADS)

Mesoscale and sub-mesoscale phytoplankton variability significantly contributes to global primary production budgets. High-resolution modelling studies suggest that incorrect representation of mesoscale and sub-mesoscale variability in ocean global circulation models (OGCM) can result in errors of about 30% in primary production estimations. Thus, characterizing mesoscale and sub-mesoscale phytoplankton variability is important for the parameterization and validation of the OGCM. Ocean colour sensors allow a global observation of small scale chlorophyll variability patterns. However, the frequent presence of clouds in ocean colour remotely sensed imagery, prevents space and time continuity and limits its exploitation. The aim of this study is to propose a new statistical processing approach for the reconstruction of areas covered by clouds in a time sequence ocean colour images. We used a classification methodology consisting in a neural network topological map. Considering a cloud-contaminated image of the sequence, missing data are reconstructed through an unsupervised statistical process that reproduces the local spatio temporal relationships of the cloudy image. The unsupervised process is trained with a selected subset of ocean colour temporal images surrounding the cloudy images. As phytoplankton variability is partly driven by oceanic dynamics, we added a set of satellite-derived dynamic ocean products (sea surface temperature, altimetry, ocean waves) influencing strongly the phytoplankton production. To develop the under cloud reconstruction method, we began by using high resolution (about 2 Km) simulated data (output of the OPA OGCM coupled with the Lobster biogechemical model). We focused on the North Atlantic ocean which is characterized by a strong mesoscale and sub-mesoscale phytoplankton variability. When applied over two seasons(spring and winter),the method was able to reproduce the statistical characteristics of the missing data with a good accuracy. We then tried to assess the ability of the method for reconstructing high resolution real data.

Manel, J.; Thiria, S.; Lévy, M.

2009-04-01

48

Voyager imaging of Triton's clouds and hazes  

NASA Technical Reports Server (NTRS)

Results are presented from a detailed analysis of Voyager images of Triton obtained at the highest solar phase angles; these have been fit to Mie scattering models in order to obtain the mean particle sizes, number densities, and the vertical extent of the two different scattering components of the Triton atmosphere. The 0.001-0.01 optical depths of about 0.17 micron particles are vertically distributed with scale heights of about 10 km throughout Triton. A number of properties of the haze particles in question suggest that they are composed of photochemically produced gases which have condensed in the cold lower atmosphere of Triton.

Rages, Kathy; Pollack, James B.

1992-01-01

49

Searching for pulsars using image pattern recognition  

E-print Network

In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surv eys using image pattern recognition with deep neural nets---the PICS(Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interferences by looking for patterns from candidate. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of up to thousands pixel of image data. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its $\\sim$9000 neurons. Different from other pulsar selection programs which use pre-designed patterns, the PICS AI teaches itself the salient features of different pulsars from a set of human-labeled candidates through machine learning. The deep neural networks in this AI system grant it superior ability in recognizing various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated wi...

Zhu, W W; Madsen, E C; Tan, M; Stairs, I H; Brazier, A; Lazarus, P; Lynch, R; Scholz, P; Stovall, K; Random, S M; Banaszak, S; Biwer, C M; Cohen, S; Dartez, L P; Flanigan, J; Lunsford, G; Matinez, J G; Mata, A; Rohr, M; Walker, A; Allen, B; Bhat, N D R; Bogdanov, S; Camilo, F; Chatterjee, S; Cordes, J M; Crawford, F; Deneva, J S; Desvignes, G; Ferdman, R D; Hessels, J W T; Jenet, F A; Kaplan, D; Kaspi, V M; Knispel, B; Lee, K J; van Leeuwen, J; Lyne, A G; McLaughlin, M A; Spitler, L G

2014-01-01

50

Reflections on current and future applications of multiangle imaging to aerosol and cloud remote sensing  

NASA Astrophysics Data System (ADS)

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its 9 along-track view angles, 4 spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space, nor is there is a similar capability currently available on any other satellite platform. Multiangle imaging offers several tools for remote sensing of aerosol and cloud properties, including bidirectional reflectance and scattering measurements, stereoscopic pattern matching, time lapse sequencing, and potentially, optical tomography. Current data products from MISR employ several of these techniques. Observations of the intensity of scattered light as a function of view angle and wavelength provide accurate measures of aerosol optical depths (AOD) over land, including bright desert and urban source regions. Partitioning of AOD according to retrieved particle classification and incorporation of height information improves the relationship between AOD and surface PM2.5 (fine particulate matter, a regulated air pollutant), constituting an important step toward a satellite-based particulate pollution monitoring system. Stereoscopic cloud-top heights provide a unique metric for detecting interannual variability of clouds and exceptionally high quality and sensitivity for detection and height retrieval for low-level clouds. Using the several-minute time interval between camera views, MISR has enabled a pole-to-pole, height-resolved atmospheric wind measurement system. Stereo imagery also makes possible global measurement of the injection heights and advection speeds of smoke plumes, volcanic plumes, and dust clouds, for which a large database is now available. To build upon what has been learned during the first decade of MISR observations, we are evaluating algorithm updates that not only refine retrieval accuracies but also include enhancements (e.g., finer spatial resolution) that would have been computationally prohibitive just ten years ago. In addition, we are developing technological building blocks for future sensors that enable broader spectral coverage, wider swath, and incorporation of high-accuracy polarimetric imaging. Prototype cameras incorporating photoelastic modulators have been constructed. To fully capitalize on the rich information content of the current and next-generation of multiangle imagers, several algorithmic paradigms currently employed need to be re-examined, e.g., the use of aerosol look-up tables, neglect of 3-D effects, and binary partitioning of the atmosphere into "cloudy" or "clear" designations. Examples of progress in algorithm and technology developments geared toward advanced application of multiangle imaging to remote sensing of aerosols and clouds will be presented.

Diner, David

2010-05-01

51

Venus: cloud level circulation during 1982 as determined from Pioneer cloud photopolarimeter images. I. Time and zonally averaged circulation  

SciTech Connect

Significant mean cloud level circulation changes since 1974, noted in 1982 Venus cloud motion observations, have been validated by independent measurements of cloud motions in nearly-identical sets of images; agreement is obtained not only for the average zonal and meridional components, but for the eddy circulation's meridional transport of momentum. In contrast to 1979 observations, the time latitudinal profile and the longitudinally-averaged zonal component of the cloud motions for 1982 exhibit jets near 45 deg latitude in both the northern and southern hemispheres. 30 references.

Limaye, S.S.; Grassotti, C.; Kuetemeyer, M.J.

1988-02-01

52

DCT-Domain Image Retrieval Via Block-Edge-Patterns  

Microsoft Academic Search

A new algorithm for compressed image retrieval is proposed in this paper based on DCT block edge patterns. This algorithm directly extract three edge patterns from compressed image data to construct an edge pattern histo- gram as an indexing key to retrieve images based on their content features. Three feature-based indexing keys are described, which include: (i) the first two

K. J. Qiu; J. Jiang; G. Xiao; S. Y. Irianto

2006-01-01

53

Characterizing Spatial Patterns of Cloud Cover And Fog Inundation in the California Channel Islands  

NASA Astrophysics Data System (ADS)

Coastal forests in Mediterranean climates are frequently covered by clouds or immersed in fog. Previous studies suggest that clouds strongly modulate forest distributions as well as carbon and water budgets in these semi-arid environments. Both low level stratocumulus cloud cover and fog can enhance the water status of vegetation along the Californian coast and the Channel Islands by reducing insolation and raising relative humidity and thus reducing evapotranspiration, while also potentially supplying water directly to the landscape from fog-drip during otherwise warm and rainless summers. While cloud cover and fog can ameliorate summer drought stress and enhance soil water budgets, they often have different spatial and temporal patterns. The resulting shifts in relative ecological importance of fog and stratus are largely unknown. The overall objective of this project was to map spatial and temporal distributions of daytime cloud cover frequency for the California Channel Islands, and to predict probabilities of surface cloud (fog) contact and immersion for these islands. Daytime cloud cover maps were generated for the northern Channel Islands using GOES satellite imagery for the years 1996-2012. To discriminate fog from stratus the base of the cloud height was constrained by using airport cloud ceiling data and topographic information. In order to observe variation in fog frequency at scales relevant to species distributions on the Channel Islands the native GOES resolution was downscaled by using radiosonde and reanalysis data. Satellite derived estimates of cloud cover and fog were correlated with field measurements of insolation, fog drip and leaf wetness on Santa Rosa and Santa Cruz islands. This enabled spatial and temporal extrapolation to understand seasonal and inter-annual variations in cloud cover frequency and fog inundation and drip and will be important for future water balance modeling, studies of coastal vegetation distributions and for better identification of locations where native vegetation restoration efforts are likely to be most successful.

Rastogi, B.; Fischer, D. T.; Williams, P.; Iacobellis, S.; McEachern, K.; Still, C. J.

2013-12-01

54

Global patterns of solar influence on high cloud cover and role of sea surface temperature  

NASA Astrophysics Data System (ADS)

Climate change and global warming have become usual terms nowadays but mechanisms that could explain their causes are not understood. One of the main sources of uncertainty in climate projections is represented by clouds, which, due to various feedback, have an important influence on Earth's radiation budget. The cloud representation in General Circulation Models relies largely on constraints derived from observations. Solar impact on climate is largely unknown and some coupling mechanisms between solar and climate variability rely on the Sea Surface Temperature. We identified solar forced patterns in observed high cloud cover (HCC) based on associations with known fingerprints of the same forcing on cloud cover obtained from reanalysis data, on observed surface air temperature (SAT), sea level pressure (SLP) and sea surface temperature (SST) fields. The solar influence on HCC has maximum amplitudes over the Pacific basin, where high cloud cover anomalies are distributed in bands of alternating polarities, indicating a SST influence on high clouds through convection. The HCC structure induced by the solar cycle appears to be generated through both so-called "top-down" and "bottom-up" mechanisms of solar influence on climate. Clouds are dependent on the relative humidity which is strongly influenced by the dynamics and SST, thus we also review possible mechanisms connecting SST with clouds, solar radiation, cosmic rays, precipitations and aerosols.

Voiculescu, Mirela; Dima, Mihai; Constantin, Daniel

2014-05-01

55

Cloud Thickness and Satellite Images (title provided or enhanced by cataloger)  

NSDL National Science Digital Library

This applet explores how the thickness of a cloud changes the way it looks from a satellite. The image is in the visible part of the spectrum, and the radiant energy is a function of not just temperature, as in the case of infrared images. The cloud thickness, its effective brightness, and the surface temperature can be modified while observing the satellite image.

Whittaker, Tom; Ackerman, Steve

56

Jupiter's clouds - Equatorial plumes and other cloud forms in the Pioneer 10 images  

NASA Technical Reports Server (NTRS)

The imaging photopolarimeter experiment aboard the Pioneer 10 spacecraft produced two-dimensional maps of intensity and polarization in red and blue light at high resolution during flyby of Jupiter in December 1973. The present article describes cloud forms seen in the equatorial zone and compares them with rotational periods as a function of latitude derived from earth-based observations of features on Jupiter. A striking new feature consists of a bright, well-defined nucleus in the equatorial zone, with a plume apparently drawn out from the core of the nucleus.

Fountain, J. W.; Coffeen, D. L.; Doose, L. R.; Gehrels, T.; Swindell, W.; Tomasko, M. G.

1974-01-01

57

Clouds  

NSDL National Science Digital Library

Clouds comprise a wonderful focus for classroom study. They're ubiquitous, ever-changing, scientifically interesting and, most importantly for teachers, they're cheap. The material presented here includes sections on cloud formation, cloud types, cloud pictures, other cloud-related phenomena, and a glossary.

Wozniak, Carl

58

Multispectral near-IR imaging of Venus nightside cloud features  

NASA Astrophysics Data System (ADS)

Near-infrared imaging observations of the Venus nightside were made on May 17-23, 1996, at the Apache Point Observatory. The data were taken with an acousto-optic tunable filter camera (AOTF), which is a newly developed, RF-tunable imager with a spectral resolution of ?/??=422 at 2.3 ?m. The observations were made at several discrete wavelengths in the 2.3 ?m spectral window in the Venus atmosphere that correspond to molecular absorption minima and maxima of several species. These data are sensitive to properties of the lower cloud deck of Venus; we examined the zonal wind speeds near an altitude of 50 km and studied the implications of the brightness contrasts seen in the images. We confirmed the ~5-day rotational period of the cloud features previously seen at this altitude level. We also confirmed previously reported contrast ratios between the brightest and darkest regions of 20:1 and found that this contrast ratio corresponds to a variation in optical depth of at least 8. We demonstrated the new technology of the near-IR AOTF camera by illustrating one of its many applications for planetary science.

Chanover, Nancy J.; Glenar, David A.; Hillman, John J.

1998-12-01

59

Development of a cloud detection method from whole-sky color images  

NASA Astrophysics Data System (ADS)

A method is proposed for detecting clouds from whole-sky color images obtained with an all-sky camera (ASC) system. In polar regions, cloud detection using whole-sky images usually suffers from large uncertainties in fractional cloud cover retrievals because of large solar zenith angles (SZAs) and high surface albedo, which cause "whitening" in the images. These problems are addressed by using differences between real images and virtual clear-sky images for a particular observation time with the same SZA. The method is applied to ASC images obtained at Ny-Ålesund, Svalbard in May of 2005-2007, and the results are compared with Micro-Pulse Lidar (MPL) measurements. When no clouds were detected by MPL, the false cloud detection rate from ASC classification was 2.1% in total hours. Conversely, when clouds were detected by MPL, the ASC classification underestimated the clouds by 11.6%. In most cases, this occurred when MPL detected very optically thin clouds. Furthermore, the variability of cloud fractions estimated by MPL and ASC was roughly constant regardless of the SZA. Thus, it is confirmed that the method developed in this study is valid for cloud detection from whole-sky color images.

Yabuki, Masanori; Shiobara, Masataka; Nishinaka, Kimiko; Kuji, Makoto

2014-12-01

60

Image pattern recognition supporting interactive analysis and graphical visualization  

NASA Technical Reports Server (NTRS)

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Coggins, James M.

1992-01-01

61

Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation using CALIOP  

E-print Network

Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation detection and cloud top height (CTH) retrievals. Both CALIOP and MODIS are part of the NASA A for nonpolar daytime and the poorest agreement in the polar regions. Differences in cloud top heights depend

Sheridan, Jennifer

62

Statistical pattern recognition algorithms for autofluorescence imaging  

NASA Astrophysics Data System (ADS)

In cancer diagnostics the most important problems are the early identification and estimation of the tumor growth and spread in order to determine the area to be operated. The aim of the work was to design of statistical algorithms helping doctors to objectively estimate pathologically changed areas and to assess the disease advancement. In the research, algorithms for classifying endoscopic autofluorescence images of larynx and intestine were used. The results show that the statistical pattern recognition offers new possibilities for endoscopic diagnostics and can be of a tremendous help in assessing the area of the pathological changes.

Kulas, Zbigniew; Bere?-Pawlik, El?bieta; Wierzbicki, Jaros?aw

2009-02-01

63

Interpretation techniques. [image enhancement and pattern recognition  

NASA Technical Reports Server (NTRS)

The image enhancement and geometric correction and registration techniques developed and/or demonstrated on ERTS data are relatively mature and greatly enhance the utility of the data for a large variety of users. Pattern recognition was improved by the use of signature extension, feature extension, and other classification techniques. Many of these techniques need to be developed and generalized to become operationally useful. Advancements in the mass precision processing of ERTS were demonstrated, providing the hope for future earth resources data to be provided in a more readily usable state. Also in evidence is an increasing and healthy interaction between the techniques developers and the user/applications investigators.

Dragg, J. L.

1974-01-01

64

Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation using CALIOP  

Microsoft Academic Search

A global 2-month comparison is presented between the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Moderate Resolution Imaging Spectroradiometer (MODIS) for both cloud detection and cloud top height (CTH) retrievals. Both CALIOP and MODIS are part of the NASA A-Train constellation of satellites and provide continuous near-coincident measurements that result in over 28 million cloud detection comparisons and over

R. E. Holz; S. A. Ackerman; F. W. Nagle; R. Frey; S. Dutcher; R. E. Kuehn; M. A. Vaughan; B. Baum

2008-01-01

65

A Routing Mechanism for Cloud Outsourcing of Medical Imaging Repositories.  

PubMed

Web-based technologies have been increasingly used in Picture Archive and Communication Systems (PACS), in services related to storage, distribution and visualization of medical images. Nowadays, many healthcare institutions are outsourcing their repositories to the Cloud. However, managing communications between multiple geo-distributed locations is still challenging due to the complexity of dealing with huge volumes of data and bandwidth requirements. Moreover, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. In order to improve the performance of distributed medical imaging networks, a smart routing mechanism was developed. This includes an innovative cache system based on splitting and dynamic management of DICOM objects. The proposed solution was successfully deployed in a regional PACS archive. The results obtained proved that it is better than conventional approaches, as it reduces remote access latency and also the required cache storage space. PMID:25343773

Marques Godinho, Tiago; Viana-Ferreira, Carlos; Bastiao Silva, Luis; Costa, Carlos

2014-10-16

66

Aerosol patterns and aerosol-cloud-interactions off the West African Coast based on the A-train formation  

NASA Astrophysics Data System (ADS)

In this study, spatial and temporal aerosol patterns off the Western African coast are characterized and related to cloud properties, based on satellite data Atmospheric aerosols play a key role in atmospheric processes and influence our environmental system in a complex way. Their identification, characterization, transport patterns as well as their interactions with clouds pose major challenges. Especially the last aspect reveals major uncertainties in terms of the Earth's radiation budget as reported in the IPCC's Fourth Assessment Report (IPCC, 2007). Western and Southern Africa are dominated by two well-known source types of atmospheric aerosols. First, the Saharan Desert is the world's largest aeolian dust emitting source region. Second, biomass burning aerosol is commonly transported off-shore further south (Kaufman et al., 2005). Both aerosol types influence Earth's climate in different manners and can be detected by the MODIS (MODerate resolution Imaging Spectrometer) sensor onboard the EOS platforms as they propagate to the Central and Southern Atlantic. The motivation of this study was to reveal the seasonal pattern of the Saharan dust transport based on an observation period of 11 years and trying to explain the meteorological mechanisms. North African dust plumes are transported along a latitude of 19°N in July and 6°N in January. The seasonally fluctuating intensities adapt to the annual cycle of wind and precipitation regimes. A strong relationship is found between the spatial shift of the Azores High and the Saharan dust load over the middle Atlantic Ocean. Monthly Aerosol Optical Thickness products of Terra MODIS and NCEP-DOE (National Centers for Environmental Predictions) Reanalysis II data are used for this purpose. The relationship between aerosol and cloud droplet parameters is blurred by high sensitivities to aerosol size and composition (Feingold, 2003; McFiggans et al., 2006) as well as meteorological context (Ackerman et al., 2004). Satellite data from the A-train formation, including the Aqua, CloudSat and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) are used to analyze aerosol-cloud-interactions in detail, along with re-analysis data to constrain by meteorological conditions. Information about the vertical and geographical distribution of different aerosol types and cloud parameters will lead to a process-oriented understanding of these issues on a regional scale. Ackerman, A., Kirkpatrick, M., Stevens, D., & Toon, O. (2004). The impact of humidity above stratiform clouds on indirect aerosol climate forcing. Nature, 432(December), 1014-1017. doi:10.1038/nature03137.1. Feingold, G. (2003). First measurements of the Twomey indirect effect using ground-based remote sensors. Geophysical Research Letters, 30(6), 1287. doi:10.1029/2002GL016633 IPCC. (2007). Climate Change 2007: The Physical Science Basis. Contribution of Working group I to the Fourth Assessment Report of the Interfovernmental Panel on climate Change. Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Kaufman, Y. J., Koren, I., Remer, L. A., Tanré, D., Ginoux, P., & Fan, S. (2005). Dust transport and deposition observed from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) spacecraft over the Atlantic Ocean. Journal of Geophysical Research, 110(D10), 1-16. doi:10.1029/2003JD004436 McFiggans, G., Artaxo, P., Baltensperger, U., Coe, H., Facchini, M. C., Feingold, G., Fuzzi, S., et al. (2006). The effect of physical and chemical aerosol properties on warm cloud droplet activation. Atmospheric Chemistry and Physics, 6(9), 2593-2649. doi:10.5194/acp-6-2593-2006

Fuchs, Julia; Bendix, Jörg; Cermak, Jan

2013-04-01

67

Congruence analysis of point clouds from unstable stereo image sequences  

NASA Astrophysics Data System (ADS)

This paper deals with the correction of exterior orientation parameters of stereo image sequences over deformed free-form surfaces without control points. Such imaging situation can occur, for example, during photogrammetric car crash test recordings where onboard high-speed stereo cameras are used to measure 3D surfaces. As a result of such measurements 3D point clouds of deformed surfaces are generated for a complete stereo sequence. The first objective of this research focusses on the development and investigation of methods for the detection of corresponding spatial and temporal tie points within the stereo image sequences (by stereo image matching and 3D point tracking) that are robust enough for a reliable handling of occlusions and other disturbances that may occur. The second objective of this research is the analysis of object deformations in order to detect stable areas (congruence analysis). For this purpose a RANSAC-based method for congruence analysis has been developed. This process is based on the sequential transformation of randomly selected point groups from one epoch to another by using a 3D similarity transformation. The paper gives a detailed description of the congruence analysis. The approach has been tested successfully on synthetic and real image data.

Jepping, C.; Bethmann, F.; Luhmann, T.

2014-06-01

68

Cloud elevations in near real time. [from geosynchronous satellite stereographic imaging  

NASA Technical Reports Server (NTRS)

The paper shows how cloud elevations can be obtained from geosynchronous satellites within 15 min of an event and to an accuracy of less than 250 m. After careful consideration of pertinent factors, it is decided that a dual satellite system in parallel geosynchronous orbits would be the most feasible configuration for stereographic imaging of cloud systems. The discussion covers tracking accuracy, choice of imaging systems, data transmission and processing, image correlation, and proposed cloud heighting system. The described partially man-interactive system is substantially within the present state of the art and could be the basis for an interim system for cloud height determination.

Shull, C. W.; Stephens, J. M.

1977-01-01

69

High-resolution reconstruction of objects from cloud-covered infrared images  

NASA Astrophysics Data System (ADS)

FLIR images are essential for the detection and recognition of ground targets. Small targets can be enhanced using super-resolution techniques to improve the effective resolution of the target area using a sequence of low-resolution images. However, when there is significant cloud cover, several problems can arise: clouds can obscure a target (partially or fully), they can affect the accuracy of image registration algorithms, and they can reduce the contrast of the object against the background. To reconstruct an image in the presence of cloud cover, image correlation metrics from optical flow and a robust super-resolution algorithm have been used to compile a 'best' frame.

Wang, Jing; Ralph, Jason F.; Goulermas, John Y.

2009-05-01

70

Microwave Imager Measures Sea Surface Temperature Through Clouds  

NASA Technical Reports Server (NTRS)

This image was acquired over Tropical Atlantic and U.S. East Coast regions on Aug. 22 - Sept. 23, 1998. Cloud data were collected by the Geostationary Operational Environmental Satellite (GOES). Sea Surface Temperature (SST) data were collected aboard the NASA/NASDA Tropical Rainfall Measuring Mission (TRMM) satellite by The TRMM Microwave Imager (TMI). TMI is the first satellite microwave sensor capable of accurately measuring sea surface temperature through clouds, as shown in this scene. For years scientists have known there is a strong correlation between sea surface temperature and the intensity of hurricanes. But one of the major stumbling blocks for forecasters has been the precise measurement of those temperatures when a storm begins to form. In this scene, clouds have been made translucent to allow an unobstructed view of the surface. Notice Hurricane Bonnie approaching the Carolina Coast (upper left) and Hurricane Danielle following roughly in its path (lower right). The ocean surface has been falsely colored to show a map of water temperature--dark blues are around 75oF, light blues are about 80oF, greens are about 85oF, and yellows are roughly 90oF. A hurricane gathers energy from warm waters found at tropical latitudes. In this image we see Hurricane Bonnie cross the Atlantic, leaving a cooler trail of water in its wake. As Hurricane Danielle followed in Bonnie's path, the wind speed of the second storm dropped markedly, as available energy to fuel the storm dropped off. But when Danielle left Bonnie's wake, wind speeds increased due to temperature increases in surface water around the storm. As a hurricane churns up the ocean, it's central vortex draws surface heat and water into the storm. That suction at the surface causes an upwelling of deep water. At depth, tropical ocean waters are significantly colder than water found near the surface. As they're pulled up to meet the storm, those colder waters essentially leave a footprint in the storm's wake which might last as long as two weeks. Forecasters can quantify the difference in surface temperatures between this footprint and the surrounding temperatures and use that information to better predict storm intensity. If another storm intersects with this cold water trail, it is likely to lose significant strength due to the fact that the colder water does not contain as much potential energy as warm water. TRMM Fact Sheet Predicting Hurricane Intensity Far from Land Remote Sensing Systems Image courtesy TRMM Project, Remote Sensing Systems, and Scientific Visualization Studio, NASA Goddard Space Flight Center

2002-01-01

71

Astronomy In The Cloud: Using Mapreduce For Image Coaddition  

NASA Astrophysics Data System (ADS)

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computational challenges such as anomaly detection, classification, and moving object tracking. Since such studies require the highest quality data, methods such as image coaddition, i.e., registration, stacking, and mosaicing, will be critical to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources, e.g., asteroids, or transient objects, e.g., supernovae, these datastreams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this paper we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data is partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources, i.e., platforms where Hadoop is offered as a service. We report on our experience implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multi-terabyte imaging dataset provides a good testbed for algorithm development since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image coaddition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results compring their performance. This work is funded by the NSF and by NASA.

Wiley, Keith; Connolly, A.; Gardner, J.; Krughoff, S.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-01-01

72

Searching for Pulsars Using Image Pattern Recognition  

NASA Astrophysics Data System (ADS)

In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ~9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The performance of this system can be improved over time as more training data are accumulated. This AI system has been integrated into the PALFA survey pipeline and has discovered six new pulsars to date.

Zhu, W. W.; Berndsen, A.; Madsen, E. C.; Tan, M.; Stairs, I. H.; Brazier, A.; Lazarus, P.; Lynch, R.; Scholz, P.; Stovall, K.; Ransom, S. M.; Banaszak, S.; Biwer, C. M.; Cohen, S.; Dartez, L. P.; Flanigan, J.; Lunsford, G.; Martinez, J. G.; Mata, A.; Rohr, M.; Walker, A.; Allen, B.; Bhat, N. D. R.; Bogdanov, S.; Camilo, F.; Chatterjee, S.; Cordes, J. M.; Crawford, F.; Deneva, J. S.; Desvignes, G.; Ferdman, R. D.; Freire, P. C. C.; Hessels, J. W. T.; Jenet, F. A.; Kaplan, D. L.; Kaspi, V. M.; Knispel, B.; Lee, K. J.; van Leeuwen, J.; Lyne, A. G.; McLaughlin, M. A.; Siemens, X.; Spitler, L. G.; Venkataraman, A.

2014-02-01

73

High-resolution (375 m) cloud microstructure as seen from the NPP/VIIRS satellite imager  

NASA Astrophysics Data System (ADS)

VIIRS (Visible Infrared Imaging Radiometer Suite), onboard the Suomi NPP (National Polar-orbiting Partnership) satellite, has an improved resolution of 750 m with respect to the 1000 m of the Moderate Resolution Imaging Spectroradiometer for the channels that allow retrieving cloud microphysical parameters such as cloud drop effective radius (re). VIIRS also has an imager with five channels of double resolution of 375 m, which was not designed for retrieving cloud products. A methodology for a high-resolution retrieval of re and microphysical presentation of the cloud field based on the VIIRS imager was developed and evaluated with respect to MODIS in this study. The tripled microphysical resolution with respect to MODIS allows obtaining new insights for cloud-aerosol interactions, especially at the smallest cloud scales, because the VIIRS imager can resolve the small convective elements that are sub-pixel for MODIS cloud products. Examples are given for new insights into ship tracks in marine stratocumulus, pollution tracks from point and diffused sources in stratocumulus and cumulus clouds over land, deep tropical convection in pristine air mass over ocean and land, tropical clouds that develop in smoke from forest fires and in heavy pollution haze over densely populated regions in southeastern Asia, and for pyro-cumulonimbus clouds. It is found that the VIIRS imager provides more robust physical interpretation and refined information for cloud and aerosol microphysics as compared to MODIS, especially in the initial stage of cloud formation. VIIRS is found to identify significantly more fully cloudy pixels when small boundary layer convective elements are present. This, in turn, allows for a better quantification of cloud-aerosol interactions and impacts on precipitation-forming processes.

Rosenfeld, D.; Liu, G.; Yu, X.; Zhu, Y.; Dai, J.; Xu, X.; Yue, Z.

2014-03-01

74

High resolution (375 m) cloud microstructure as seen from the NPP/VIIRS Satellite imager  

NASA Astrophysics Data System (ADS)

The VIIRS (Visible Infrared Imaging Radiometer Suite) onboard the Suomi NPP (National Polar-Orbiting Partnership) satellite has improved resolution of 750 m with respect to 1000 m of the MODerate-resolution Imaging Spectroradiometer, for the channels that allow retrieving cloud microphysical parameters such as cloud drop effective radius (re). The VIIRS has also an imager with 5 channels of double resolution of 375 m, which was not designed for retrieving cloud products. A methodology for a high resolution retrieval of re and microphysical presentation of the cloud field based on the VIIRS imager was developed and evaluated with respect to MODIS in this study. The tripled microphysical resolution with respect to MODIS allows obtaining new insights for cloud aerosol interactions, especially at the smallest cloud scales, because the VIIRS imager can resolve the small convective elements that are sub-pixel for MODIS cloud products. Examples are given for new insights on ship tracks in marine stratocumulus, pollution tracks from point and diffused sources in stratocumulus and cumulus clouds over land, deep tropical convection in pristine air mass over ocean and land, tropical clouds that develop in smoke from forest fires and in heavy pollution haze over densely populated regions in southeast Asia, and for pyro-cumulonimbus clouds. It is found that the VIIRS imager provides more robust physical interpretation and refined information for cloud and aerosol microphysics as compared to MODIS, especially in the initial stage of cloud formation. VIIRS is found to identify much more full-cloudy pixels when small boundary layer convective elements are present. This, in turn, allows a better quantification of cloud aerosol interactions and impacts on precipitation forming processes.

Rosenfeld, D.; Liu, G.; Yu, X.; Zhu, Y.; Dai, J.; Xu, X.; Yue, Z.

2013-11-01

75

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques  

NASA Technical Reports Server (NTRS)

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Smith, William L.; Ebert, Elizabeth

1990-01-01

76

Investigation of vortex clouds and droplet sizes in heated water spray patterns generated by axisymmetric full cone nozzles.  

PubMed

The hot water sprays are an important part of many industrial processes, where the detailed knowledge of physical phenomena involved in jet transportation, interaction, secondary breakup, evaporation, and coalescence of droplets is important to reach more efficient processes. The objective of the work was to study the water spray jet breakup dynamics, vortex cloud formation, and droplet size distribution under varying temperature and load pressure. Using a high speed camera, the spray patterns generated by axisymmetric full cone nozzles were visualized as a function water temperature and load pressure. The image analysis confirmed that the spray cone angle and width do not vary significantly with increasing Reynolds and Weber numbers at early injection phases leading to increased macroscopic spray propagation. The formation and decay of semitorus like vortex clouds were also noticed in spray structures generated at near water boiling point temperature. For the nozzle with smallest orifice diameter (1.19 mm), these vortex clouds were very clear at 90°C heating temperature and 1 bar water load pressure. In addition, the sauter mean diameter (SMD) of the spray droplets was also measured by using Phase Doppler Anemometry (PDA) at different locations downstream of the nozzle exit. It was noticed that SMD varies slightly w.r.t. position when measured at room temperature whereas at higher temperature values, it became almost constant at distance of 55 mm downstream of the nozzle exit. PMID:24307881

Naz, M Y; Sulaiman, S A; Ariwahjoedi, B; Ku Shaari, Ku Zilati

2013-01-01

77

Investigation of Vortex Clouds and Droplet Sizes in Heated Water Spray Patterns Generated by Axisymmetric Full Cone Nozzles  

PubMed Central

The hot water sprays are an important part of many industrial processes, where the detailed knowledge of physical phenomena involved in jet transportation, interaction, secondary breakup, evaporation, and coalescence of droplets is important to reach more efficient processes. The objective of the work was to study the water spray jet breakup dynamics, vortex cloud formation, and droplet size distribution under varying temperature and load pressure. Using a high speed camera, the spray patterns generated by axisymmetric full cone nozzles were visualized as a function water temperature and load pressure. The image analysis confirmed that the spray cone angle and width do not vary significantly with increasing Reynolds and Weber numbers at early injection phases leading to increased macroscopic spray propagation. The formation and decay of semitorus like vortex clouds were also noticed in spray structures generated at near water boiling point temperature. For the nozzle with smallest orifice diameter (1.19?mm), these vortex clouds were very clear at 90°C heating temperature and 1 bar water load pressure. In addition, the sauter mean diameter (SMD) of the spray droplets was also measured by using Phase Doppler Anemometry (PDA) at different locations downstream of the nozzle exit. It was noticed that SMD varies slightly w.r.t. position when measured at room temperature whereas at higher temperature values, it became almost constant at distance of 55?mm downstream of the nozzle exit. PMID:24307881

Naz, M. Y.; Sulaiman, S. A.; Ariwahjoedi, B.; Ku Shaari, Ku Zilati

2013-01-01

78

3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields  

NASA Technical Reports Server (NTRS)

3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

2007-01-01

79

Methodology for estimating availability of cloud-free image composites: A case study for southern Canada  

NASA Astrophysics Data System (ADS)

Image composites are often used for earth surface phenomena studies at regional or national level. The compromise between residual clouds and the length of compositing period is a necessary corollary to the choice of satellite optical data for monitoring earth surface phenomena dynamics. This paper introduced a methodology for estimating availability of cloud-free image composites for optical sensors with various revisiting intervals, using MODIS MOD06 L2 cloud fraction product in the period of 2000-2008. The methodology starts with downscaling of the cloud fraction product to 1 km × 1 km cloud cover binary images. The binary images are then used for the exploration of spatial and temporal characteristics of cloud dynamics, and subsequently for the simulation of cloud-free composite availability with various revisiting intervals of optical sensors. Using Canada's southern provinces as an application case, the study explored several factors important for the design of environmental monitoring system using optical sensors of earth observation, in particular, cloud dynamics and its inter-annual variability, sensors' revisiting intervals, and cloud-free threshold for targeting composites. While the cloud images used in the analysis are at 1 km × 1 km resolution, our analysis suggests that the simulated availabilities of cloud-free image composites may also provide reasonable estimates for optical sensors with higher than 1 km × 1 km resolution, though the closer to 1 km × 1 km resolution the optical sensor, the more pertinent the application. Also, the methodology can be parameterised to different temporal period and different spatial region, depending on applications.

Zhou, Fuqun; Zhang, Aining

2013-04-01

80

A cloud pattern recognition algorithm to automate the estimation of mass eruption rates from an umbrella cloud or downwind plume observed via satellite imagery  

NASA Astrophysics Data System (ADS)

The eruption of Eyjafjallajökull, Iceland in April and May, 2010, brought to light the importance of Volcanic Ash Transport and Dispersion models (VATD) to the estimation of the position and concentration of ash with time, and how vital it is for Volcanic Ash Advisory Centers (VAACs) to be able to detect and track ash clouds with both observations and models. The VATD needs to get Eruption Source Parameters (ESP), including mass eruption rate through time, as input, which ultimately relies on the detection of the eruption regardless of the meteorological conditions. Volcanic cloud recognition is especially difficult when meteorological clouds are also present, which is typically the case in the tropics. Given the fact that meteorological clouds and volcanic clouds behave differently, we developed an agent-based pattern definition algorithm to detect and define volcanic clouds on satellite imagery. We have combined this with a plume growth rate methodology to automate the estimation of volumetric and mass growth with time using plume geometry provided by satellite imagery. This allows an estimation of the mass eruption rate (MER) with time. To test our approach, we used the examples of two eruptions of different source strength, in two different climatic regimes and for which therefore the weather during eruption was quite different: Grímsvötn (Iceland) May 21, 2011, which produced an umbrella cloud readily seen above the cloud deck, and Manam (Papua New Guinea) October 24, 2004, which produced a stratospheric umbrella cloud that rapidly turned into a downwind plume, and was difficult to distinguish from meteorological clouds. The new methods may in the future allow for fast, easy and automated detection of volcanic clouds as well as a remote assessment of the mass eruption rate with time, even for inaccessible volcanoes. The methods may thus provide an additional path to estimation of the ESP and the forecasting of ash cloud propagation.

Jansons, E.; Pouget, S.; Bursik, M. I.; Patra, A. K.; Pitman, E. B.; Tupper, A.

2013-12-01

81

Weekly Cycle of Lightning and Associated Patterns of Rainfall, Cloud, and Aerosols over Korea and Adjacent Oceans during Boreal Summer  

NASA Technical Reports Server (NTRS)

In this study, we analyze the weekly cycle of lightning over Korea and adjacent oceans and associated variations of aerosols, clouds, precipitation, and atmospheric circulations, using aerosol optical depth (AOD) from the NASA Moderate resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR), cloud properties from MODIS, precipitation and storm height from Tropical Rainfall Measuring Mission (TRMM) satellite, and lightning data from the Korean Lightning Detection Network (KLDN) during 9-year from 2002 to 2010. Lightning data was divided into three approximately equal areas, land area of Korea, and two adjacent oceans, Yellow Sea and South Sea. Preliminary results show that the number of lightning increases during the middle of the week over Yellow Sea. AOD data also shows moderately significant midweek increase at about the same time as lightning peaks. These results are consistent with the recent studies showing the invigoration of storms with more ice hydrometeors by aerosols, and subsequently wash out of aerosols by rainfall. Frequency of lightning strokes tend to peak at weekend in land area and over South Sea, indicating local weekly anomalous circulation between land and adjacent ocean. On the other hand, lightning frequency over Yellow Sea appears to have very strong weekly cycle with midweek peak on around Wednesday. It is speculated that the midweek peak of lightning over Yellow Sea was related with aerosol transport from adjacent land area. AOD data also suggests midweek peak over Yellow Sea, however, the weekly cycle of AOD was not statistically significant. Changes in weekly cycle of lightning from pre-monsoon to monsoon season, as well as associated clouds and circulation patterns are also discussed.

Kim, Ji-In; Kim, Kyu-Myong

2011-01-01

82

Accuracy assessment of building point clouds automatically generated from iphone images  

NASA Astrophysics Data System (ADS)

Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (?) and standard deviation (?) of roughness histograms are calculated as (?1 = 0.44 m., ?1 = 0.071 m.) and (?2 = 0.025 m., ?2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.

Sirmacek, B.; Lindenbergh, R.

2014-06-01

83

Patterns of satellite-viewed, subtropical, jet-stream clouds in relation to the observed wind field  

E-print Network

PATTERNS OF SATELLITE-VIEWED, SUBTROPICAL, JET- STREAM CLOUDS IN RELATION TO THE OBSERVED WIND FIELD A Thesis by RICHARD JOEL VOGT Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement... for the degree of MASTER OF SCIENCE December 1972 Major Subject: Meteorology PATTERNS OP SATELLITE-VIEWED, SUBTROPICAL, JET-STREAM CLOUDS IN RELATION TO THE OBSERVED WIND FIELD A Thesis by RICHARD JOEL VOGT Approved as to style and content by: (Chairman...

Vogt, Richard Joel

1972-01-01

84

Images of Hurricane Katrina (2005) below the cloud  

NASA Astrophysics Data System (ADS)

A remarkable coincidence of two independent satellite images from Radarsat-1 synthetic aperture radar (SAR) and SeaWinds/QuikSCAT scatterometer, depicting the state of the sea surface, and HRD/NOAA aircraft reconnaissance including a Stepped Frequency Microwave Radiometer (SFMR), occurred in Hurricane Katrina near the time of its maximum intensity on August 28th, 2005. The satellite images were acquired within 6 seconds of each other near 2345 UTC. The eye, primary and secondary eyewalls, and outer rainbands were traversed by the aircraft during the time of image acquisition, and all of these features are visible on the images, both of which captured most of the storm area. Comparison of SAR and scatterometer images indicates good agreement in the level of backscatter pixel-by-pixel when SAR pixels (~50 m) are averaged to match scatterometer pixels (~2.5 km). Comparison with airborne SFMR also indicates good agreement when the aircraft data are rotated slightly in azimuth to account for advection by the tangential surface winds over a period of 0-6 minutes. Seven independent measurements of horizontal wind are available in this unique situation: one from each satellite image, the airborne radiometer, in situ flight-level data, dropsondes, fuselage radar (for feature tracking of precipitation features) and tail Doppler radar (a 3D wind field synthesized over ~1 hour). Comparison of surface and flight level data in the primary eyewall indicates an outward tilt of the axis of maximum winds with height similar to that seen in the Doppler composite structure obtained around this time. Surface winds appear stronger than flight-level winds in the primary eyewall but not in a secondary eyewall farther out.. Tangential wind maxima are associated with both eyewalls -- each a ring of enhanced precipitation -- and both are superposed on a radial profile of rather strong winds, suggesting that significant microwave backscatter should be expected throughout the inner core, as observed. Nevertheless, the imprint of eye and eyewalls on the sea surface is clearly visible in the satellite backscatter images and in surface winds derived from their respective retrieval algorithms. Our coincidence of independent wind measurements provides an unprecedented opportunity for algorithm validation in an extreme wind/rainfall environment and to assess the impacts, if any, of cloud liquid water and raindrops on beam attenuation in the C and Ku bands used, respectively, by the SAR and scatterometer. A few suspiciously dark features in an outer rainband are detected in both satellite images, and an attempt is made to collocate with spots of maximum precipitation in a sequence of fuselage radar images in order to address this issue. Similar features are sometimes seen in SAR images of other hurricanes, suggesting small pockets or "seams" of relative calm. Comments are made on the utility of SAR imagery for ocean swell and sea spray in the hurricane inner-core environment, and for depiction of convective downdrafts in the outer bands.

Dunkerton, T. J.; Walter, B. A.; Perrie, W.; Long, D. G.; Zhang, J.; Black, P. G.; Rogers, R.

2006-12-01

85

Video imaging of debris clouds following penetration of lightweight spacecraft materials  

Microsoft Academic Search

The structure of debris clouds following hypervelocity penetration of thin materials is of special interest to spacecraft designers--it forms the basis for damage equations from meteoroids, orbital debris, and other kinetic energy threats. Today, video imaging offers the experimenter a new view into the structure and development of debris clouds following penetration of these thin materials. This technique is of

Joel Williamsen; Eric Howard

2001-01-01

86

Robust Message-Privacy Preserving Image Copy Detection for Cloud-based Systems  

E-print Network

that in turn are used to encrypt the source image and serve as a robust hash that can be queried for contentRobust Message-Privacy Preserving Image Copy Detection for Cloud-based Systems M. Diephuis, S verification, image-content identification, copy-detection, privacy and authentication perfectly. Additionally

Genève, Université de

87

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)  

NASA Technical Reports Server (NTRS)

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Platnick, Steven

2004-01-01

88

A Method for Compositing Polar MODIS Satellite Images to Remove Cloud Cover for Landfast Sea-Ice Detection  

Microsoft Academic Search

This paper presents details of techniques for generating thermal infrared and visible composite images from the cloud-free portions of temporally closely spaced MODerate resolution Imaging Spectroradiometer (MODIS) images, with a focus on studies of landfast sea ice along the East Antarctic coast. Composite image inclusion criteria are based on modified MODIS Earth Observing System cloud mask product results. The compositing

Alexander D. Fraser; Robert A. Massom; Kelvin J. Michael

2009-01-01

89

Matching clouds and shadows based on high-resolution satellite image  

NASA Astrophysics Data System (ADS)

Clouds are the obstruction of visual and infrared remote sensing and their shadows may also lead up to an intolerable bias of the true reflectance of the underlying terrain elements. Thus a reliable cloud and shadow mask is essential before the further processing. Clouds cast shadows on the earth's surface. On the high resolution remote sensing images, clouds' profiles and their shadows' are resemblant. Based on this truth, we employed a robust image matching algorithm called Modified Partial Hausforff Distance(MPHD) to find the match with every cloud and its shadow and finally calculated the pixel distance between them. Before the match task we took into account topologic relationships such as coverage and fragmentation to improve the match result. Not only were the match pairs detected but also the pixel distances from each cloud to its shadow were obtained. Then we can use a pixel distance to predict a shadow of a cloud by translating the cloud. Given sunbeam's direction and viewing angles we may get cloud height with simple geometry calculation.

Chen, Xiaodong; Chen, Jianyu; Pan, Delu; Mao, Zhihua; Huang, Haiqing

2006-12-01

90

Satellite retrieval of convective cloud base temperature based on the NPP/VIIRS Imager  

NASA Astrophysics Data System (ADS)

advent of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (NPP) satellite provided a quantum jump in the satellite capabilities of retrieving cloud properties, because it nearly tripled the resolution in the thermal channels (375 m). This allowed us to develop a methodology for retrieving convective cloud base temperature (Tb) and validate it over the Atmospheric System Research Southern Great Plains site for the satellite early afternoon overpass time. The standard error of the Tb retrieval was only 1.1°C. The knowledge of Tb allows the calculation of cloud base height and the depth of the boundary layer, as well as the boundary layer water vapor mixing ratio with an accuracy of about 10%. The feasibility of retrieving cloud base temperature and height is an essential component that is required for retrieving cloud condensation nuclei (CCN) from satellites by using convective clouds as natural CCN chambers.

Zhu, Yannian; Rosenfeld, Daniel; Yu, Xing; Liu, Guihua; Dai, Jin; Xu, Xiaohong

2014-02-01

91

Image processing for new optical pattern recognition encoders  

NASA Astrophysics Data System (ADS)

An all new type of absolute, optical encoder with ultra-high sensitivity has been developed at NASA's Goddard Space Flight Center. These position measuring encoders are unconventional in that they rely on computational pattern recognition of high speed, electronic images, made of a moving, backlit scale which carries absolute position information of either linear or rotary format. The pattern recognition algorithms combine edge detection, threshold level sensing, spatial compression, and centroiding along with fault recovery through scale image defect detection. Details of the encoder scale patterns and their design rules and the image processing algorithm which gives these encoders their unique and unparalleled performance characteristics are discussed.

Leviton, Douglas B.

2000-11-01

92

Watershed identification of polygonal patterns in noisy SAR images.  

PubMed

This paper describes a new approach to pattern recognition in synthetic aperture radar (SAR) images. A visual analysis of the images provided by NASA's Magellan mission to Venus has revealed a number of zones showing polygonal-shaped faults on the surface of the planet. The goal of the paper is to provide a method to automate the identification of such zones. The high level of noise in SAR images and its multiplicative nature make automated image analysis difficult and conventional edge detectors, like those based on gradient images, inefficient. We present a scheme based on an improved watershed algorithm and a two-scale analysis. The method extracts potential edges in the SAR image, analyzes the patterns obtained, and decides whether or not the image contains a "polygon area". This scheme can also be applied to other SAR or visual images, for instance in observation of Mars and Jupiter's satellite Europa. PMID:18237949

Moreels, Pierre; Smrekar, Suzanne E

2003-01-01

93

A Spitzer Imaging Survey of the Entire Taurus Molecular Cloud  

Microsoft Academic Search

The star-forming clouds nearest to our Sun are located 140 pc away in Taurus. Lacking young stellar clusters and luminous OB stars, Taurus hosts a distributed mode of star formation that has proven particularly amenable to observational and theoretical study. Yet despite its importance to the past two decades of star formation research, only fragments of the Taurus clouds are

Deborah Padgett; Lori Allen; Marc Audard; Jerome Bouvier; Tim Brooke; Sean Carey; Catherine Dougados; Neal Evans; Nicolas Grosso; Manuel Guedel; Paul Harvey; Lynne Hillenbrand; Dean Hines; Jocelyn Keene; Bill Latter; Carol Lonsdale; Francois Menard; Phil Myers; Alberto Noreiga-Crespo; Luisa Rebull; David Shupe; Steve Skinner; Karl Stapelfeldt; Steve Strom; Sebastian Wolf

2004-01-01

94

Analysis of dust cloud combustion using FAST Infrared Imaging  

NASA Astrophysics Data System (ADS)

Dust cloud combustion is unfortunately at risk in many working environments, jeopardizing several workers. The heat and shock waves resulting from the flame propagation into the dust cloud are harmful and lead to major endangerment or casualties. More precisely, dust cloud (small particles) explosions are even more malicious since they often result from ordinary materials such as coal, flour or pollen. Also, many metal powdered (such as aluminum oxide and magnesium) can form dangerous dust cloud when they are in suspensions in air. The understanding of this particular type of combustion is critical for the preventive care of sites and workers afflicted to such conditions. This paper presents the results of a dynamic flow analysis of metal particles combustion in a dust cloud. The ignition points, the flow rate as well as the propagation direction of the flow have been characterized using fast infrared imagery.

Marcotte, Frederick; Farley, Vincent; Savary, Simon

2013-05-01

95

The computation of cloud base height from paired whole-sky imaging cameras  

SciTech Connect

A major goal for global change studies is to improve the accuracy of general circulation models (GCMs) capable of predicting the timing and magnitude of greenhouse gas-induced global warming. Research has shown that cloud radiative feedback is the single most important effect determining the magnitude of possible climate responses to human activity. Of particular value to reducing the uncertainties associated with cloud-radiation interactions is the measurement of cloud base height (CBH), both because it is a dominant factor in determining the infrared radiative properties of clouds with respect to the earth`s surface and lower atmosphere and because CBHs are essential to measuring cloud cover fraction. We have developed a novel approach to the extraction of cloud base height from pairs of whole sky imaging (WSI) cameras. The core problem is to spatially register cloud fields from widely separated WSI cameras; this complete, triangulation provides the CBH measurements. The wide camera separation (necessary to cover the desired observation area) and the self-similarity of clouds defeats all standard matching algorithms when applied to static views of the sky. To address this, our approach is based on optical flow methods that exploit the fact that modern WSIs provide sequences of images. We will describe the algorithm and present its performance as evaluated both on real data validated by ceilometer measurements and on a variety of simulated cases.

Allmen, M.C.; Kegelmeyer, W.P. Jr.

1994-03-01

96

Optical Imaging of Flow Pattern and Phantom  

NASA Technical Reports Server (NTRS)

Time-resolved optical imaging technique has been used to image the spatial distribution of small droplets and jet sprays in a highly scattering environment. The snake and ballistic components of the transmitted pulse are less scattered, and contain direct information about the sample to facilitate image formation as opposed to the diffusive components which are due to multiple collisions as a light pulse propagates through a scattering medium. In a time-gated imaging scheme, these early-arriving, image-bearing components of the incident pulse are selected by opening a gate for an ultrashort period of time and a shadowgram image is detected. Using a single shot cooled CCD camera system, the formation of water droplets is monitored as a function of time. Picosecond time-gated image of drop in scattering cells, spray droplets as a function of let speed and gas pressure, and model calcification samples consisted of calcium carbonate particles of irregular shapes ranging in size from 0. 1 to 1.5 mm affixed to a microscope slide have been measured. Formation produced by an impinging jet will be further monitored using a CCD with 1 kHz framing illuminated with pulsed light. The desired image resolution of the fuel droplets is on the 20 pm scale using early light through a highly scattering medium. A 10(exp -6)m displacement from a jet spray with a flow speed of 100 m/sec introduced by the ns grating pulse used in the imaging is negligible. Early ballistic/snake light imaging offers nondestructive and noninvasive method to observe the spatial distribution of hidden objects inside a highly scattering environment for space, biomedical, and materials applications. In this paper, the techniques we will present are time-resolved K-F transillumination imaging and time-gated scattered light imaging. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.

Galland, Pierre A.; Liang, X.; Wang, L.; Ho, P. P.; Alfano, R. R.; Breisacher, K.

1999-01-01

97

Image processing for new optical pattern recognition encoders  

Microsoft Academic Search

An all new type of absolute, optical encoder with ultra-high sensitivity has been developed at NASA's Goddard Space Flight Center. These position measuring encoders are unconventional in that they rely on computational pattern recognition of high speed, electronic images, made of a moving, backlit scale which carries absolute position information of either linear or rotary format. The pattern recognition algorithms

Douglas B. Leviton

2000-01-01

98

Cloud Remote Sensing with Sideways-Looks : Theory and First Results Using Multispectral Thermal Imager Data  

SciTech Connect

In operational remote sensing, the implicit model for cloud geometry is a homogeneous plane-parallel slab of infinite horizontal extent. Each pixel is indeed processed as if it exchanged no radiant energy whatsoever with its neighbors. The shortcomings of this conceptual model have been well documented in the specialized literature but rarely mitigated. The worst-case scenario is probably high-resolution imagery where dense isolated clouds are visible, often both bright (reflective) and dark (transmissive) sides being apparent from the same satellite viewing angle: the low transmitted radiance could conceivably be interpreted in plane-parallel theory as no cloud at all. An alternative to the plane-parallel cloud model is introduced here that has the same appeal of being analytically tractable, at least in the diffusion limit: the spherical cloud. This new geometrical paradigm is applied to radiances from cumulus clouds captured by DOE's Multispectral Thermal Imager (MTI). Estimates of isolated cloud opacities are a necessary first step in correcting radiances from surface targets that are visible in the midst of a broken-cloud field. This type of advanced atmospheric correction is badly needed in remote sensing applications such as nonproliferation detection were waiting for a cloud-free look in the indefinite future is not a viable option.

Davis, A. B. (Anthony B.)

2002-01-01

99

Genetic refinement of cloud-masking algorithms for the multi-spectral thermal imager (MTI)  

SciTech Connect

The Multi-spectral Thermal Imager (MTI) is a high-performance remote-sensing satellite designed, owned and operated by the U.S. Department of Energy, with a dual mission in environmental studies and in nonproliferation. It has enhanced spatial and radiometric resolutions and state-of-the-art calibration capabilities. This instrumental development puts a new burden on retrieval algorithm developers to pass this accuracy on to the inferred geophysical parameters. In particular, the atmospheric correction scheme assumes the intervening atmosphere will be modeled as a plane-parallel horizontally-homogeneous medium. A single dense-enough cloud in view of the ground target can easily offset reality from the calculations, hence the need for a reliable cloud-masking algorithm. Pixel-scale cloud detection relies on the simple facts that clouds are generally whiter, brighter, and colder than the ground below; spatially, dense clouds are generally large on some scale. This is a good basis for searching multispectral datacubes for cloud signatures. However, the resulting cloud mask can be very sensitive to the choice of thresholds in whiteness, brightness, temperature, and connectivity. We have used a genetic algorithm trained on (MODIS Airborne Simulator-based) simulated MTI data to design a cloud-mask. Its performance is compared quantitatively to hand-drawn training data and to the EOS/Terra MODIS cloud mask.

Hirsch, K. L. (Karen L.); Davis, A. B. (Anthony B.); Harvey, N. R. (Neal R.); Rohde, C. A. (Charles A.); Brumby, Steven P.

2001-01-01

100

Range image segmentation through pattern analysis of multiscale difference information  

NASA Astrophysics Data System (ADS)

This work presents an image segmentation method for range data that uses multi-scale wavelet analysis in combination with statistical pattern recognition. We train a pattern- recognition system with scale-space data from the edge points of a training image. Once trained the system can determine the degree of edgeness of points in a new image. Before designing the segmentation system we set forth several goals. We desire that the system detect boundaries of small as well as large objects, be robust, and have few or no free parameters. Edges in an image respond to edge detectors at different scales; therefore combining edge detection information at multiple scales can create a more complete and robust edge detection. Scale-space refers to a family of derived signals where the fine-scale information is successively suppressed as scale increases. Edge points in images have a specific signature over scale space. We use a pattern recognition method to analyze these signatures as 1-D signals and therefore label edges in an image based on its multi-scale response to a wavelet transform. A fuzzy pattern classifier with one class determines the degree of membership in the edge class for each pixel in the image. Assigning this degree of membership to each pixel creates a fuzzy edge map. a watershed algorithm then creates a segmentation from this edge map. We use the wavelet transform to generate the scale space of a range image. We choose a spline wavelet used by Mallat. A simple, synthetic image with added noise and known edges provides a training set for the pattern recognition system. Known edge points from the image create a probability density function indicating membership in an edge class. The results from analyzing a complex real image are shown.

Burgiss, Samuel G., Jr.; Whitaker, Ross T.; Abidi, Mongi A.

1997-09-01

101

Variations of zonal wind speed at Venus cloud tops from Venus Monitoring Camera UV images  

NASA Astrophysics Data System (ADS)

7 years of continuous monitoring of Venus by ESA's Venus Express provided an opportunity to study dynamics of the atmosphere of Venus. Venus Monitoring Camera (VMC) [1] delivered the longest and the most complete so far set of UV images to study the cloud level circulation by tracking motion of the cloud features. We analyzed 130 orbits with manual cloud tracking and 600 orbits with digital correlation method. Here we present the latest update of our results. Total number of wind vectors derived in this work is approximately a half million. During Venus Express observations the mean zonal speed was in the range of 85-110 m/s. VMC observations indicated a long term trend for the zonal wind speed at low latitudes to increase. The origin of low frequency trend with a period about 3000 days is unclear. Fourier analysis [2-3] of revealed quasi-periodicities in the zonal circulation at low latitudes. Two groups of the periods were found. The first group is close to the period of superrotation at low latitudes (4.83±0.1 days) with the period 4.1-5.1 days and the amplitude ranging from ±4.2 to ±17.4 m/s. The amplitude and phase of oscillations demonstrates dependence from the latitude and also time variability with preserving stable parameters of oscillation during at least 70 days. Short term oscillations may be caused by wave processes in the mesosphere of Venus at the cloud top level. Wave number of the observed oscillations is 1. The second group is a long term periods caused by orbital motion of Venus (116 days, 224 days) and is related to the periodicity in VMC observations. Also VMC UV observations showed a clear diurnal pattern of the mean circulation. The zonal wind demonstrated semi-diurnal variations with minimum speed close to noon (11-14 h) and maxima in the morning (8-9 h) and in the evening (16-17 h). The meridional component clearly peaks in the early afternoon (13-15h) at latitudes near 50S. The minimum of the meridional wind is located at low latitudes in the morning (8-11h). References [1] Markiewicz W. J. et al.: Venus Monitoring Camera for Venus Express // Planet. Space Sci.. V.55(12). pp1701-1711. doi:10.1016/j.pss.2007.01.004, 2007. [2] Deeming T.J.: Fourier analysis with unequally-spaced data. Astroph. and Sp. Sci. V.36, pp137-158, 1975. [3] Terebizh, V.Yu. Time series analysis in astrophysics. Moscow: "Nauka," Glav. red. fiziko-matematicheskoi lit-ry, 1992. In Russian

Khatuntsev, Igor; Patsaeva, Marina; Ignatiev, Nikolai; Titov, Dmitri; Markiewicz, Wojciech J.

2013-04-01

102

Fresnel patterns insertion on image for data encoding and robust perceptual image hashing  

NASA Astrophysics Data System (ADS)

A piling of Fresnel patterns is inserted in an image for data encoding and image hashing synchronization, dedicated to local authentication. Beyond, the problem is to preserve both decoding and image content perception. Besides this, the insertion must not too much alter perceptual image hashing.

Fournel, T.; Rivoire, A.; Becker, J. M.; Javidi, B.

2010-04-01

103

Evaluating EUV mask pattern imaging with two EUV microscopes  

Microsoft Academic Search

Aerial image measurement plays a key role in the development of patterned reticles for each generation of lithography. Studying the field transmitted (reflected) from EUV masks provides detailed information about potential disruptions caused by mask defects, and the performance of defect repair strategies, without the complications of photoresist imaging. Furthermore, by measuring the continuously varying intensity distribution instead of a

Kenneth A. Goldberg; Kei Takase; Patrick P. Naulleau; Hakseung Han; Anton Barty; Hiroo Kinoshita; Kazuhiro Hamamoto

2008-01-01

104

Infrared cloud imaging in support of Earth-space optical communication.  

PubMed

The increasing need for high data return from near-Earth and deep-space missions is driving a demand for the establishment of Earth-space optical communication links. These links will require a nearly obstruction-free path to the communication platform, so there is a need to measure spatial and temporal statistics of clouds at potential ground-station sites. A technique is described that uses a ground-based thermal infrared imager to provide continuous day-night cloud detection and classification according to the cloud optical depth and potential communication channel attenuation. The benefit of retrieving cloud optical depth and corresponding attenuation is illustrated through measurements that identify cloudy times when optical communication may still be possible through thin clouds. PMID:19434118

Nugent, Paul W; Shaw, Joseph A; Piazzolla, Sabino

2009-05-11

105

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing  

NASA Technical Reports Server (NTRS)

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.; Smoot, James C.; Underwood, Lauren; Armstrong, C. Duane

2012-01-01

106

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

SciTech Connect

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.

Love, Steven P.; Davis, A. B. (Anthony B.); Rohde, C. A. (Charles A.); Ho, Cheng,

2001-01-01

107

Non-Precipitating Stratus Cloud Images Retrieval and Characterization Using a Ground-Based Dual-Wavelength  

E-print Network

Non-Precipitating Stratus Cloud Images Retrieval and Characterization Using a Ground-Based Dual at Amherst ABSTRACT Characterization of the microphysical properties of non-precipitating stratus clouds. INTRODUCTION Stratus clouds frequently cover much of the sky and play a key role in keeping Earth's surface

Cruz-Pol, Sandra L.

108

Typhoon center location algorithm based on fractal feature and gradient of infrared satellite cloud image  

NASA Astrophysics Data System (ADS)

An efficient algorithm for typhoon center location is proposed using fractal feature and gradient of infrared satellite cloud image. The centers are generally located in this region for a typhoon except the latter disappearing typhoon. The characteristics of dense cloud region are smoother texture and higher gray values than those of marginal clouds. So the window analysis method is used to select an appropriate cloud region. The window whose difference value between the sum of the gray-gradient co-occurrence matrix and fractal dimension is the biggest is chosen as the dense cloud region. The temperature gradient of the region, which is near typhoon center except typhoon eye, is small. Thus the gradient information is strengthened and is calculated by canny operator. Then we use a window to traverse the dense cloud region. If there is a closed curve, the region of curve is considered as the typhoon center region. Otherwise, the region in which there is the most texture intersection and the biggest density is considered as the typhoon center region. Finally, the geometric center of the center region is determined as the typhoon center location. The effectiveness is test by Chinese FY-2C stationary satellite cloud image. And the result is compared with the typhoon center location in the "tropical cyclone yearbook" which was compiled by Shanghai typhoon institute of China meteorological administration. Experimental results show that the high location accuracy can be obtained.

Zhang, Changjiang; Chen, Yuan; Lu, Juan

2014-11-01

109

Signature of clouds over Antarctic sea ice detected by the Special Sensor Microwave\\/Imager  

Microsoft Academic Search

A method to detect the cloud signature (mainly the cloud liquid water) over the sea ice-covered Weddell Sea in the Austral summer season is presented. By using the polarization differences at the two high frequency channels (i.e., 37 and 85 GHz) of the Special Sensor Microwave\\/Imager (SSM\\/I), a new quantity called R-factor is defined. Using the R-factor, the atmospheric signal

Jungang Miao; Klaus-Peter Johnsen; Stefan Kern; Georg Heygster; Klaus Kunzi

2000-01-01

110

Cloud Coverage Based on All-Sky Imaging and Its Impact on Surface Solar Irradiance  

SciTech Connect

In Lauder, Central Otago, two all-sky imaging systems have been operated for more than one year measuring the total, opaque, and thin cloud fraction as well as an indicator of whether the sun is obscured by clouds. The data provide a basis for investigating the impact of clouds on the surface radiation field. We aligned the all-sky cloud parameters with measurements of global, direct and diffuse surface solar irradiance over the spectral interval from 0.3 to 3 mm. Here we describe results of ongoing analysis of this data set. As a reference for the magnitude of the cloud influence, clear sky irradiance values are estimated as a simple function of solar zenith angle and Earth-Sun distance. The function is derived from a least-square fit to measurements taken when available cloud images show clear sky situations. Averaged over a longer time period, such as a month, cloud fraction and surface irradiance are clearly negatively correlated. Monthly means in the ratio of the measured surface irradiance to the clear-sky value had a correlation coefficient of about -0.9 with means of cloud fraction for the months July 2000 to June 2001. In the present work we analyze reductions in the surface irradiance and also situations where clouds cause radiation values to exceed the expected clear sky amount. Over one year of observations, 1-minute-average radiation measurements exceeding the expected clear sky value by more than 10% were observed with a frequency of 5%. In contrast, a reduction of more than 10% below estimated clear sky values occurred in 66% of the cases, while clear sky irradiances (measured irradiance within {+-}10% of estimated clear sky value) were observed 29% of the time. Low cloud fractions frequently lead to moderate enhancement, as the sun is often unobscured and the clouds are brighter than the sky that they hide. As cloud fraction increases the sun is likely to be obscured, causing irradiance values to fall well below clear sky values. However, in case of unobscured sun, there is a tendency for strongest enhancements when cloud fractions are highest. Enhancements, especially at high solar zenith angle, are also often observed in association with thin clouds.

Pfister, G.; McKenzie, R. L.; Liley, J. B.; Thomas, A.; Forgan, B. W.; Long, Charles N.

2003-10-31

111

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data  

NASA Technical Reports Server (NTRS)

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.

2004-01-01

112

A comparison of cloud motion winds from ATS 6 images with coinciding SMS 1 winds  

NASA Technical Reports Server (NTRS)

A methodology is developed for accurate measurement of cloud motion winds from the geosynchronous ATS 6 image data. Attitude changes between consecutive images (as a function of scan-line number) are accounted for in wind computations through measurement of the earth-edge displacements between the successive infrared images. Also, an image matching procedure is used to remove obvious and distracting image distortions. The availability of SMS imagery coinciding with ATS 6 imagery makes SMS an excellent reference against which the quality of ATS 6 winds can be tested. The resulting winds inferred from cloud displacement measurements taken from a sequence of the corrected images are found to agree better than 2 m/sec rms with winds measured from coincident SMS 1 imagery.

Kuhlow, W. W.; Chatters, G. C.

1978-01-01

113

Multiscale vector fields for image pattern recognition  

NASA Technical Reports Server (NTRS)

A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.

Low, Kah-Chan; Coggins, James M.

1990-01-01

114

An investigation of time variations in a subtropical jet stream and the associated cloud patterns as shown by TIROS I  

E-print Network

AN INVESTIGATION OF TIME VARIATIONS IN A SUBTROPICAL JET STREAM AND THE ASSOCIATED CLOUD PATTERNS AS SHOWN BY TIROS I A Thesis By PETER FRANCIS LESTER Submitted to the Graduate College of the Texas A6M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE August 1964 Ma( or Sub] ect: METEOROLOGY AN INVESTIGATION OF TIME VARIATIONS IN A SUBTROPICAL JET STREAM AND THE ASSOCIATED CLOUD PATTERNS AS SHOWN BY TIROS I A Thesis By PETER FRANCIS LESTER Approved...

Lester, Peter Francis

1964-01-01

115

Watershed image segmentation and cloud classification from multispectral MSG–SEVIRI imagery  

Microsoft Academic Search

In this work a technique for cloud detection and classification from MSG–SEVIRI (Meteosat Second Generation–Spinning Enhanced Visible and Infra-red Imager) imagery is presented. It is based on the segmentation of the multispectral images using order-invariant watershed algorithms, which are applied to the corresponding gradient images, computed by a multi-dimensional morphological operator. To reduce the over-segmentation produced by the watershed method,

Albano González; Juan C. Pérez; Jonathan Munoz; Zebensui Méndez; Montserrat Armas Padilla

2008-01-01

116

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition  

NASA Technical Reports Server (NTRS)

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

117

Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks  

PubMed Central

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

118

Automatic registration of Iphone images to LASER point clouds of the urban structures using shape features  

NASA Astrophysics Data System (ADS)

Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from different sensor sources. As we use iPhone camera images which are taken in front of the interested urban structure by the application user and the high resolution LIDAR point clouds of the acquired by an airborne laser sensor. After finding the photo capturing position and orientation from the iPhone photograph metafile, we automatically select the area of interest in the point cloud and transform it into a range image which has only grayscale intensity levels according to the distance from the image acquisition position. We benefit from local features for registering the iPhone image to the generated range image. In this article, we have applied the registration process based on local feature extraction and graph matching. Finally, the registration result is used for facade texture mapping on the 3D building surface mesh which is generated from the LIDAR point cloud. Our experimental results indicate possible usage of the proposed algorithm framework for 3D urban map updating and enhancing purposes.

Sirmacek, B.; Lindenbergh, R. C.; Menenti, M.

2013-10-01

119

A method for modelling IR images of sky and clouds  

Microsoft Academic Search

Thermal radiation of objects is often used as its discriminative feature by the systems of automatic target recognition (ATR). In such case to develop effective detection algorithms it is essential to know radiation characteristics not only of the detected objects but also its surroundings. The paper presents a method of numerical modelling of clouds radiation in infrared spectral range. The

R. Dulski; T. Sosnowski; H. Polakowski

2011-01-01

120

Modelling of IR images of sky and clouds  

Microsoft Academic Search

A phenomenon of thermal radiation of real objects is used in systems of automatic target recognition (ATR). To develop effective algorithms, it is essential to know both radiation characteristics of the detected objects and characteristics of their surroundings. The paper presents a method of numerical modeling of clouds radiation and their environment in IR range. Experimental data registered with short

T. Sosnowski; R. Dulski; H. Polakowski

121

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Imager Data over the Atmospheric Radiation Measurement Sites  

SciTech Connect

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 {micro}m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-{micro}m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60{sup o}N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

Trepte, Q.Z.; Minnis, P.; Heck, P.W.; Palikonda, R.

2005-03-18

122

The effects of orography on cloud and rainfall patterns during typhoon Ketsana (2009)  

NASA Astrophysics Data System (ADS)

The objective of this study is to investigate the effects of orography on the rainfall, wind, and cloud systems of the TCs in Malaysia and Indochina. To determine the relationship of the typhoon with the orographic effect, remote sensing techniques such as the Global Digital Elevation Model (GDEM) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite, rainfall data from the Fengyun 2D (FY-2D), and radiosonde data were applied in this study. From this study, the following conclusions can be drawn: 1) rainfall tends to be distributed over high mountain regions; 2) wind flow will change its direction upon encountering any restrictions, especially those of high terrain regions; and 3) cloud patterns are deformed by high mountains and tend to flow with the mountains' structure because of the orographic effects. The regions most affected by Typhoon Ketsana in the study area were Vietnam in Indochina, Sabah in East Malaysia (EM), Kelantan and Terengganu in Peninsular Malaysia (PM). From the comparison among the study areas, it was found that Indochina had the most significant results for the orographic effects on typhoon activity, followed by the tail effects in EM. This phenomenon was found in PM, although it was not as significant as the other study areas. This remote sensing technique allows tropical cyclones to be forecasted and their impacts to be defined, and it allows disaster zones to be determined.

Fuyi, Tan; MatJafri, Mohd Zubir; Lim, Hwee-San; Abdullah, Khiruddin

2012-10-01

123

Automated estimation of mass eruption rate of volcanic eruption on satellite imagery using a cloud pattern recognition algorithm  

NASA Astrophysics Data System (ADS)

The need to detect and track the position of ash in the atmosphere has been highlighted in the past few years following the eruption Eyjafjallajokull. As a result, Volcanic Ash Advisory Centers (VAACs) are using Volcanic Ash Transport and Dispersion models (VATD) to estimate and predict the whereabouts of the ash in the atmosphere. However, these models require inputs of eruption source parameters, such as the mass eruption rate (MER), and wind fields, which are vital to properly model the ash movements. These inputs might change with time as the eruption enters different phases. This implies tracking the ash movement as conditions change, and new satellite imagery comes in. Thus, ultimately, the eruption must be detectable, regardless of changing eruption source and meteorological conditions. Volcanic cloud recognition can be particularly challenging, especially when meteorological clouds are present, which is typically the case in the tropics. Given the fact that a large fraction of the eruptions in the world happen in a tropical environment, we have based an automated volcanic cloud recognition algorithm on the fact that meteorological clouds and volcanic clouds behave differently. As a result, the pattern definition algorithm detects and defines volcanic clouds as different object types from meteorological clouds on satellite imagery. Following detection and definition, the algorithm then estimates the area covered by the ash. The area is then analyzed with respect to a plume growth rate methodology to get estimation of the volumetric and mass growth with time. This way, we were able to get an estimation of the MER with time, as plume growth is dependent on MER. To test our approach, we used the examples of two eruptions of different source strength, in two different climatic regimes, and for which therefore the weather during the eruption was quite different: Manam (Papua New Guinea) January 27 2005, which produced a stratospheric umbrella cloud and was difficult to distinguish from meteorological clouds, and Okmok (Alaska) July 12 2008, which was also an umbrella cloud, but started as an ash-rich cloud before getting a vapor rich pulse into the cloud. The new methods may in the future allow for fast, easy and automated detection of volcanic clouds as well as remote assessment of the MER with time, even for inaccessible volcanoes. The methods may thus provide an additional path to estimation of the ESP and the forecasting of ash cloud propagation with time as the eruption changes.

Pouget, Solene; Jansons, Emile; Bursik, Marcus; Tupper, Andrew; Patra, Abani; Pitman, Bruce; Carn, Simon

2014-05-01

124

Characterizing spatial and temporal patterns of cloud cover and fog inundation for the Northern Channel islands of California  

NASA Astrophysics Data System (ADS)

The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in a variety of ecosystems in different climates. This is especially true for California's Channel Islands, where forests are frequently shaded by low-lying clouds or immersed in fog during warm and dry summer months. Previous studies suggest that clouds strongly modulate forest distributions as well as carbon and water budgets in these semi-arid environments by reducing solar insolation and raising relative humidity and thus reducing evapotranspiration, while also potentially supplying water directly to the landscape from fog-drip. While summertime fog and stratus cover in California's Channel Islands can ameliorate summer drought stress and enhance soil water budgets, they often have different spatial and temporal patterns. These differing patterns and the resulting shifts in relative ecological importance of fog and stratus are understudied. The overall objective of this study is to map spatial and temporal distributions of daytime cloud cover frequency for the California Channel Islands, and to predict probabilities of surface cloud (fog) contact and immersion for these islands. The results of this research are significant for water balance modeling, help explain vegetation patterns on the islands, and better identify locations where native vegetation restoration efforts are likely to be most successful.

Rastogi, Bharat

125

Pattern based 3D image Steganography  

NASA Astrophysics Data System (ADS)

This paper proposes a new high capacity Steganographic scheme using 3D geometric models. The novel algorithm re-triangulates a part of a triangle mesh and embeds the secret information into newly added position of triangle meshes. Up to nine bits of secret data can be embedded into vertices of a triangle without causing any changes in the visual quality and the geometric properties of the cover image. Experimental results show that the proposed algorithm is secure, with high capacity and low distortion rate. Our algorithm also resists against uniform affine transformations such as cropping, rotation and scaling. Also, the performance of the method is compared with other existing 3D Steganography algorithms. [Figure not available: see fulltext.

Thiyagarajan, P.; Natarajan, V.; Aghila, G.; Prasanna Venkatesan, V.; Anitha, R.

2013-03-01

126

Hex-square moire patterns in imagers using microchannel plates  

NASA Technical Reports Server (NTRS)

In electronic imaging detectors using microchannel plates, the mismatch between the pixels on a square mesh and the microchannels on a hexagonal mesh produces moire image defects. Theoretical statistical estimates of the sizes of the microposition offsets and the flat field intensity errors are calculated, showing the trade-off between resolution and position accuracy. A distinction is made between moments of spot images and moments of the single-pixel-response functions. As the resolution between the hex and square meshes is improved, the detector resolution is improved, but at the expense of an about 10 percent moire pattern. These moire patterns will not be properly corrected by dividing by the flat field image.

Lawrence, George M.

1989-01-01

127

Active probing of cloud thickness and optical depth using wide-angle imaging LIDAR.  

SciTech Connect

At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60{sup o} full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Section 2 covers the up-to-date evolution of the nighttime WAIL instrument at LANL. Section 3 reports our progress towards daytime capability for WAIL, an important extension to full diurnal cycle monitoring by means of an ultra-narrow magneto-optic atomic line filter. Section 4 describes briefly how the important cloud properties can be inferred from WAIL signals.

Love, Steven P.; Davis, A. B. (Anthony B.); Rohde, C. A. (Charles A.); Tellier, L. L. (Larry L.); Ho, Cheng,

2002-01-01

128

Progressive image transmission using pyramid structure and pattern matching coding  

NASA Astrophysics Data System (ADS)

A pyramidal data structure suited for coding and progressive transmission of images is proposed in this work. A mean pyramid representation of an image is first built up by forming a sequence of reduced-size images. A pyramid of difference images is then generated by subtracting the previous coded image from the original image at each level of the pyramid. Progressive transmission is achieved by sending all the nodes in the difference pyramid starting from the top level and ending at the bottom level. To gain efficiency, a pattern matching- based coding algorithm is applied to the difference pyramid of the image on a level-by-level basis. The proposed coding method, compresses the difference images by using a set of parameters computed based the visual activity of individual image blocks. The coding efficiency of the proposed technique along with the low computational complexity and simple parallel implementation of the pyramid approach allows for a high compression ratio as well as a good image quality. Satisfactory coded images have been obtained at bit rates in the range of 0.30 - 0.33 bits per pixel (bpp).

Keissarian, F.

2011-06-01

129

Machine learning patterns for neuroimaging-genetic studies in the cloud  

PubMed Central

Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines. PMID:24782753

Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand

2014-01-01

130

Machine learning patterns for neuroimaging-genetic studies in the cloud.  

PubMed

Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines. PMID:24782753

Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand

2014-01-01

131

Hiding a checkered-pattern carrier-screen image in a camouflaged halftone image  

NASA Astrophysics Data System (ADS)

As carrier-screen images, we have developed checkered-pattern carrier-screen images, which can be physically decoded by superimposing a checkered pattern. We also proposed a decoding method by image sampling with an ordinary compact digital camera. To obtain a better decoding result, each carrier-screen image should be output at a low resolution. However, secret information can be detected when you observe the image carefully. Thus, a hiding process is an important technique. In this paper, we propose an advanced hiding method by embedding the carrier-screen image into another significant image to generate a camouflaged halftone image. The proposed embedding method can be performed through a simple sequential process of blending and halftoning.

Shogenji, Rui; Ohtsubo, Junji

2014-05-01

132

Direct imaging of a massive dust cloud around R Coronae Borealis  

NASA Astrophysics Data System (ADS)

We present recent polarimetric images of the highly variable star R CrB using ExPo and archival WFPC2 images from the HST. We observed R CrB during its current dramatic minimum where it decreased more than 9 mag due to the formation of an obscuring dust cloud. Since the dust cloud is only in the line-of-sight, it mimics a coronograph allowing the imaging of the star's circumstellar environment. Our polarimetric observations surprisingly show another scattering dust cloud at approximately 1.3'' or 2000 AU from the star. We find that to obtain a decrease in the stellar light of 9 mag and with 30% of the light being reemitted at infrared wavelengths (from R CrB's SED) the grains in R CrB's circumstellar environment must have a very low albedo of approximately 0.07%. We show that the properties of the dust clouds formed around R CrB are best fitted using a combination of two distinct populations of grains size. The first are the extremely small 5 nm grains, formed in the low density continuous wind, and the second population of large grains (~0.14 ?m) which are found in the ejected dust clouds. The observed scattering cloud, not only contains such large grains, but is exceptionally massive compared to the average cloud. Based on observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias.

Jeffers, S. V.; Min, M.; Waters, L. B. F. M.; Canovas, H.; Rodenhuis, M.; de Juan Ovelar, M.; Chies-Santos, A. L.; Keller, C. U.

2012-03-01

133

A Pattern Classification Approach to DNA Microarray Image Segmentation  

NASA Astrophysics Data System (ADS)

A new method for DNA microarray image segmentation based on pattern recognition techniques is introduced. The method performs an unsupervised classification of pixels using a clustering algorithm, and a subsequent supervised classification of the resulting regions. Additional fine tuning includes detecting region edges and merging, and morphological operators to eliminate noise from the spots. The results obtained on various microarray images show that the proposed technique is quite promising for segmentation of DNA microarray images, obtaining a very high accuracy on background and noise separation.

Rueda, Luis; Rojas, Juan Carlos

134

First Spectacular Panoramic UV Images of the Magellanic Clouds from GALEX  

NASA Astrophysics Data System (ADS)

We present the first complete, panoramic ultraviolet maps of the Large and Small Magellanic Clouds obtained from by the Galaxy Evolution Explorer (GALEX) near the end of its mission. These are the deepest and highest quality UV images yet obtained for the Clouds. We present first scientific results including measurements of total and local star formation rates across the Clouds and their outskirts, and a detailed view of specific star-forming regions and the interplay of gas, dust and young stars. We also discuss the novel techniques used to build these maps — a challenge for the standard GALEX — pipeline with observations that routinely far exceeded the GALEX bright source limits. These images provide a powerful legacy data set for the GALEX mission. This work was supported by NASA ADAP grant NNX14AF81G.

Schiminovich, David; Seibert, Mark; GALEX Science Team

2015-01-01

135

Global pattern analysis and classification of dermoscopic images using textons  

NASA Astrophysics Data System (ADS)

Detecting and classifying global dermoscopic patterns are crucial steps for detecting melanocytic lesions from non-melanocytic ones. An important stage of melanoma diagnosis uses pattern analysis methods such as 7-point check list, Menzies method etc. In this paper, we present a novel approach to investigate texture analysis and classification of 5 classes of global lesion patterns (reticular, globular, cobblestone, homogeneous, and parallel pattern) in dermoscopic images. Our statistical approach models the texture by the joint probability distribution of filter responses using a comprehensive set of the state of the art filter banks. This distribution is represented by the frequency histogram of filter response cluster centers called textons. We have also examined other two methods: Joint Distribution of Intensities (JDI) and Convolutional Restricted Boltzmann Machine (CRBM) to learn the pattern specific features to be used for textons. The classification performance is compared over the Leung and Malik filters (LM), Root Filter Set (RFS), Maximum Response Filters (MR8), Schmid, Laws and our proposed filter set as well as CRBM and JDI. We analyzed 375 images of the 5 classes of the patterns. Our experiments show that the joint distribution of color (JDC) in the L*a*b* color space outperforms the other color spaces with a correct classification rate of 86.8%.

Sadeghi, Maryam; Lee, Tim K.; McLean, David; Lui, Harvey; Atkins, M. Stella

2012-02-01

136

Augmenting Reality via Client/Cloud Video and Image Processing Lab  

E-print Network

11 Augmenting Reality via Client/Cloud Platforms Video and Image Processing Lab University. - Jimmy Wang, John Ristevski 2 #12;Outline What is Augmented Reality (AR)? Why now? Current examples;What is Augmented Reality? Enhance or augment real/actual world to create a more satisfying user

California at Irvine, University of

137

Fluorescence Imaging for Visualization of the Ion Cloud in a Quadrupole Ion Trap Mass Spectrometer  

NASA Astrophysics Data System (ADS)

Laser-induced fluorescence is used to visualize populations of gaseous ions stored in a quadrupole ion trap (QIT) mass spectrometer. Presented images include the first fluorescence image of molecular ions collected under conditions typically used in mass spectrometry experiments. Under these "normal" mass spectrometry conditions, the radial ( r) and axial ( z) full-width at half maxima (FWHM) of the detected ion cloud are 615 and 214 ?m, respectively, corresponding to ~6 % of r 0 and ~3 % of z 0 for the QIT used. The effects on the shape and size of the ion cloud caused by varying the pressure of helium bath gas, the number of trapped ions, and the Mathieu parameter q z are visualized and discussed. When a "tickle voltage" is applied to the exit end-cap electrode, as is done in collisionally activated dissociation, a significant elongation in the axial, but not the radial, dimension of the ion cloud is apparent. Finally, using spectroscopically distinguishable fluorophores of two different m/ z values, images are presented that illustrate stratification of the ion cloud; ions of lower m/ z (higher q z ) are located in the center of the trapping region, effectively excluding higher m/ z (lower q z ) ions, which form a surrounding layer. Fluorescence images such as those presented here provide a useful reference for better understanding the collective behavior of ions in radio frequency (rf) trapping devices and how phenomena such as collisions and space-charge affect ion distribution.

Talbot, Francis O.; Sciuto, Stephen V.; Jockusch, Rebecca A.

2013-12-01

138

Sub-Nyquist Medical Ultrasound Imaging: En Route to Cloud Processing  

E-print Network

Sub-Nyquist Medical Ultrasound Imaging: En Route to Cloud Processing Alon Eilam, Tanya Chernyakova@ee.technion.ac.il GE Healthcare, Haifa, Israel Email: arcady.kempinski@med.ge.com Abstract--In medical ultrasound is feasible for medical ultrasound, leading to potential of considerable reduction in future ultrasound

Eldar, Yonina

139

The analisis of Gis software engineering pattern under the cloud computing environment  

Microsoft Academic Search

This paper introduces the basic concepts of cloud computing and the characteristics of GIS software engineering, and analyzes the impact of cloud computing on the GIS software development. It discusses the GIS software engineering design method under the cloud computing environment from the aspect of GIS software architecture, development organizations and deployment management, and proposes some suggestions for problems that

Zhou Peng; Li Mei; Wang Fei; Yin Feil

2010-01-01

140

Evaluating EUV mask pattern imaging with two EUV microscopes  

SciTech Connect

Aerial image measurement plays a key role in the development of patterned reticles for each generation of lithography. Studying the field transmitted (reflected) from EUV masks provides detailed information about potential disruptions caused by mask defects, and the performance of defect repair strategies, without the complications of photoresist imaging. Furthermore, by measuring the continuously varying intensity distribution instead of a thresholded, binary resist image, aerial image measurement can be used as feedback to improve mask and lithography system modeling methods. Interest in EUV, at-wavelength, aerial image measurement lead to the creation of several research tools worldwide. These tools are used in advanced mask development work, and in the evaluation of the need for commercial at-wavelength inspection tools. They describe performance measurements of two such tools, inspecting the same EUV mask in a series of benchmarking tests that includes brightfield and darkfield patterns. One tool is the SEMATECH Berkeley Actinic Inspection Tool (AIT) operating on a bending magnet beamline at Lawrence Berkeley National Laboratory's Advanced Light Source. The AIT features an EUV Fresnel zoneplate microscope that emulates the numerical aperture of a 0.25-NA stepper, and projects the aerial image directly onto a CCD camera, with 700x magnification. The second tool is an EUV microscope (EUVM) operating at the NewSUBARU synchrotron in Hyogo, Japan. The NewSUBARU tool projects the aerial image using a reflective, 30x Schwarzschild objective lens, followed by a 10-200x x-ray zooming tube. The illumination conditions and the imaging etendue are different for the two tools. The benchmarking measurements were used to determine many imaging and performance properties of the tools, including resolution, modulation transfer function (MTF), aberration magnitude, aberration field-dependence (including focal-plane tilt), illumination uniformity, line-edge roughness, and flare. These measurements reveal the current state of the art in at-wavelength inspection performance, and will be a useful reference as performance improves over time.

Goldberg, Kenneth A.; Takase, Kei; Naulleau, Patrick P.; Han, Hakseung; Barty, Anton; Kinoshita, Hiroo; Hamamoto, Kazuhiro

2008-02-26

141

Effects of clouds on the Earth radiation budget; Seasonal and inter-annual patterns  

NASA Technical Reports Server (NTRS)

Seasonal and regional variations of clouds and their effects on the climatological parameters were studied. The climatological parameters surface temperature, solar insulation, short-wave absorbed, long wave emitted, and net radiation were considered. The data of climatological parameters consisted of about 20 parameters of Earth radiation budget and clouds of 2070 target areas which covered the globe. It consisted of daily and monthly averages of each parameter for each target area for the period, Jun. 1979 - May 1980. Cloud forcing and black body temperature at the top of the atmosphere were calculated. Interactions of clouds, cloud forcing, black body temperature, and the climatological parameters were investigated and analyzed.

Dhuria, Harbans L.

1992-01-01

142

Imaging diffuse clouds: bright and dark gas mapped in CO  

NASA Astrophysics Data System (ADS)

Aims: We wish to relate the degree scale structure of galactic diffuse clouds to sub-arcsecond atomic and molecular absorption spectra obtained against extragalactic continuum background sources. Methods: We used the ARO 12 m telescope to map J = 1-0 CO emission at 1' resolution over 30' fields around the positions of 11 background sources occulted by 20 molecular absorption line components, of which 11 had CO emission counterparts. We compared maps of CO emission to sub-arcsec atomic and molecular absorption spectra and to the large-scale distribution of interstellar reddening. Results: 1) The same clouds, identified by their velocity, were seen in absorption and emission and atomic and molecular phases, not necessarily in the same direction. Sub-arcsecond absorption spectra are a preview of what is seen in CO emission away from the continuum. 2) The CO emission structure was amorphous in 9 cases, quasi-periodic or wave-like around B0528+134 and tangled and filamentary around BL Lac. 3) Strong emission, typically 4-5 K at EB - V ? 0.15 mag and up to 10-12 K at EB - V ? 0.3 mag was found, much brighter than toward the background targets. Typical covering factors of individual features at the 1 K km s-1 level were 20%. 4) CO-H2 conversion factors as much as 4-5 times below the mean value N(H2)/WCO = 2 × 1020 H2 cm-2 (K km s-1)-1 are required to explain the luminosity of CO emission at/above the level of 1 K km s-1. Small conversion factors and sharp variability of the conversion factor on arcminute scales are due primarily to CO chemistry and need not represent unresolved variations in reddening or total column density. Conclusions: Like Fermi and Planck we see some gas that is dark in CO and other gas in which CO is overluminous per H2. A standard CO-H2 conversion factor applies overall owing to balance between the luminosities per H2 and surface covering factors of bright and dark CO, but with wide variations between sightlines and across the faces of individual clouds. Based on observations obtained with the ARO Kitt Peak 12 m telescope.Appendices are available in electronic form at http://www.aanda.org

Liszt, H. S.; Pety, J.

2012-05-01

143

Direct imaging of a massive dust cloud around R Coronae Borealis  

E-print Network

We present recent polarimetric images of the highly variable star R CrB using ExPo and archival WFPC2 images from the HST. We observed R CrB during its current dramatic minimum where it decreased more than 9 mag due to the formation of an obscuring dust cloud. Since the dust cloud is only in the line-of-sight, it mimics a coronograph allowing the imaging of the star's circumstellar environment. Our polarimetric observations surprisingly show another scattering dust cloud at approximately 1.3" or 2000 AU from the star. We find that to obtain a decrease in the stellar light of 9 mag and with 30% of the light being reemitted at infrared wavelengths (from R CrB's SED) the grains in R CrB's circumstellar environment must have a very low albedo of approximately 0.07%. We show that the properties of the dust clouds formed around R CrB are best fitted using a combination of two distinct populations of grains size. The first are the extremely small 5 nm grains, formed in the low density continuous wind, and the second...

Jeffers, S V; Waters, L B F M; Canovas, H; Rodenhuis, M; Ovelar, M De Juan; Chies-Santos, A L; Keller, C U; 10.1051/0004-6361/201117138

2012-01-01

144

Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern  

DOEpatents

Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.

Doerry, Armin W.

2013-04-30

145

Images of Hurricane Katrina (2005) below the cloud  

Microsoft Academic Search

A remarkable coincidence of two independent satellite images from Radarsat-1 synthetic aperture radar (SAR) and SeaWinds\\/QuikSCAT scatterometer, depicting the state of the sea surface, and HRD\\/NOAA aircraft reconnaissance including a Stepped Frequency Microwave Radiometer (SFMR), occurred in Hurricane Katrina near the time of its maximum intensity on August 28th, 2005. The satellite images were acquired within 6 seconds of each

T. J. Dunkerton; B. A. Walter; W. Perrie; D. G. Long; J. Zhang; P. G. Black; R. Rogers

2006-01-01

146

Multi-Scale Fractal Analysis of Image Texture and Pattern  

NASA Technical Reports Server (NTRS)

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.

1998-01-01

147

Component pattern analysis of chemicals using multispectral THz imaging system  

NASA Astrophysics Data System (ADS)

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.

Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

2004-04-01

148

Imaging Patterns of Brain Development and their Relationship to Cognition.  

PubMed

We present a brain development index (BDI) that concisely summarizes complex imaging patterns of structural brain maturation along a single dimension using a machine learning methodology. The brain was found to follow a remarkably consistent developmental trajectory in a sample of 621 subjects of ages 8-22 participating in the Philadelphia Neurodevelopmental Cohort, reflected by a cross-validated correlation coefficient between chronologic age and the BDI of r = 0.89. Critically, deviations from this trajectory related to cognitive performance. Specifically, subjects whose BDI was higher than their chronological age displayed significantly superior cognitive processing speed compared with subjects whose BDI was lower than their actual age. These results indicate that the multiparametric imaging patterns summarized by the BDI can accurately delineate trajectories of brain development and identify individuals with cognitive precocity or delay. PMID:24421175

Erus, Guray; Battapady, Harsha; Satterthwaite, Theodore D; Hakonarson, Hakon; Gur, Raquel E; Davatzikos, Christos; Gur, Ruben C

2014-01-27

149

Diurnal cloud-to-ground lightning patterns in Arizona during the southwest monsoon  

SciTech Connect

Cloud-to-ground (CG) lightning shows great variability across Arizona from one year to the next as well as from one day to the next. Availability of moisture, location of the subtropical ridge axis, transitory troughs in both the westerlies and easterlies, and low-level moisture surges from the Gulf of California can affect thunderstorm occurrence, which, in turn, will affect lightning production. Diurnal CG lightning patterns in Arizona are also determined by daily heating cycles and topography. Six years of Bureau of Land Management CG flash data are used in this investigation. In Arizona, lightning usually starts first, on a daily basis, in the plateau region and extends in an arc from the White Mountains of eastern Arizona westward across the Mogollon Rim and then northward onto the Kaibab Plateau of northern Arizona. Flash activity moves in a more or less continuous fashion off the plateau, south and westward down the topography gradient, and enters the lower desert by early evening. At the same time, flash activity develops in the highlands of southeast Arizona and moves west-northwestward, reaching the lower desert by late afternoon. Precipitation and lightning are well correlated, except that precipitation seems to linger longer than lightning, probably due to the occasional development of mesoscale convective systems, which produce light stratiform precipitation during their dissipation stage.

Watson, A.I.; Lopez, R.E.; Holle, R.L. [NOAA, Norman, OK (United States)] [NOAA, Norman, OK (United States)

1994-08-01

150

Influence of clouds on the parameters of images measured by IACT at very high energies  

NASA Astrophysics Data System (ADS)

Observations with the Cherenkov telescopes are in principle limited to clear sky conditions due to significant absorption of Cherenkov light by clouds. If the cloud level is high enough or the atmospheric transmission of the cloud is high, then high energy showers (with TeV energies) can still produce enough Cherenkov photons allowing detection by telescopes with large sizes and cameras with large field of view (FOV). In this paper, we study the possibility of observations of showers, induced by high-energy particles in the atmosphere, in the presence of clouds that are completely or partially opaque for Cherenkov radiation. We show how the image parameters of the Cherenkov light distribution on the telescope camera are influenced for different opacity and altitude of the cloud. By applying the Monte Carlo simulations, we calculate the scaled LENGTH and WIDTH parameters with the purpose to separate ?-ray and proton initiated showers in real data. We show, that the high level of the night sky background effects the selection efficiency of the ?-ray initiated showers. However, application of the higher image-cleaning level significantly improves expected quality factors. The estimated ?-ray selection efficiency for the detector with the camera field of view (FOV) limited to 8{^\\circ } is slightly better than for the camera with an unlimited FOV, although the number of identified ?-ray events is lower. We conclude that large Cherenkov telescopes with large FOV cameras can be used for observations of very high energy ?-rays in the presence of clouds. Consequently, the amount of useful data can be significantly enlarged.

Sobczy?ska, Dorota; Bednarek, W?odek

2014-12-01

151

Synergistic combination of clinical and imaging features predicts abnormal imaging patterns of pulmonary infections  

PubMed Central

We designed and tested a novel hybrid statistical model that accepts radiologic image features and clinical variables, and integrates this information in order to automatically predict abnormalities in chest computed-tomography (CT) scans and identify potentially important infectious disease biomarkers. In 200 patients, 160 with various pulmonary infections and 40 healthy controls, we extracted 34 clinical variables from laboratory tests and 25 textural features from CT images. From the CT scans, pleural effusion (PE), linear opacity (or thickening) (LT), tree-in-bud (TIB), pulmonary nodules, ground glass opacity (GGO), and consolidation abnormality patterns were analyzed and predicted through clinical, textural (imaging), or combined attributes. The presence and severity of each abnormality pattern was validated by visual analysis of the CT scans. The proposed biomarker identification system included two important steps: (i) a coarse identification of an abnormal imaging pattern by adaptively selected features (AmRMR), and (ii) a fine selection of the most important features from the previous step, and assigning them as biomarkers, depending on the prediction accuracy. Selected biomarkers were used to classify normal and abnormal patterns by using a boosted decision tree (BDT) classifier. For all abnormal imaging patterns, an average prediction accuracy of 76.15% was obtained. Experimental results demonstrated that our proposed biomarker identification approach is promising and may advance the data processing in clinical pulmonary infection research and diagnostic techniques. PMID:23930819

Bagci, Ulas; Jaster-Miller, Kirsten; Olivier, Kenneth N.; Yao, Jianhua; Mollura, Daniel J.

2013-01-01

152

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing  

NASA Astrophysics Data System (ADS)

Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

2011-03-01

153

Hubble Space Telescope Imaging of Neptune's Cloud Structure in 1994.  

PubMed

Images of Neptune taken at six wavelengths with the Hubble Space Telescope in October and November 1994 revealed several atmospheric features not present at the time of the Voyager spacecraft encounter in 1989. Furthermore, the largest feature seen in 1989, the Great Dark Spot, was gone. A dark spot of comparable size had appeared in the northern hemisphere, accompanied by discrete bright features at methane-band wavelengths. At visible wavelengths, Neptune's banded structure appeared similar to that seen in 1989. PMID:17834994

Hammel, H B; Lockwood, G W; Mills, J R; Barnet, C D

1995-06-23

154

BOREAS AFM-6 NOAA/ETL 35 GHz Cloud/Turbulence Radar GIF Images  

NASA Technical Reports Server (NTRS)

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-6 team from the National Oceanic and Atmospheric Administration/Environment Technology Laboratory (NOAA/ETL) operated a 35-GHz cloud-sensing radar in the Northern Study Area (NSA) near the Old Jack Pine (OJP) tower from 16 Jul 1994 to 08 Aug 1994. This data set contains a time series of GIF images that show the structure of the lower atmosphere. The NOAA/ETL 35-GHz cloud/turbulence radar GIF images are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Martner, Brooks E.; Newcomer, Jeffrey A. (Editor); Hall, Forrest G.; Smith, David E. (Technical Monitor)

2000-01-01

155

Photometric Calibration of the Barium Cloud Image in a Space Active Experiment: Determining the Release Efficiency  

NASA Astrophysics Data System (ADS)

The barium release experiment is an effective method to explore the near-earth environment and to study all kinds of space physics processes. The first space barium release experiment in China was successfully carried out by a sounding rocket on April 5, 2013. This work is devoted to calculating the release efficiency of the barium release by analyzing the optical image observed during the experiment. First, we present a method to calibrate the images grey value of barium cloud with the reference stars to obtain the radiant fluxes at different moments. Then the release efficiency is obtained by a curve fitting with the theoretical evolution model of barium cloud. The calculated result is basically consistent with the test value on ground.

Xie, Liang-Hai; Li, Lei; Wang, Jing-Dong; Tao, Ran; Cheng, Bing-Jun; Zhang, Yi-Teng

2014-01-01

156

A dynamic and generic cloud computing model for glaciological image processing  

NASA Astrophysics Data System (ADS)

As satellite imaging is quite expensive, and because of poor weather conditions including common heavy cloud cover at polar latitudes, daily satellite imaging is not always accessible or suitable to observe fast temporal evolutions. We complement satellite imagery with a set of ground based autonomous automated digital cameras which take three pictures a day. With these pictures we build a mosaic with their projection and apply a classification to define the temporal evolution of the snow cover. As the pictures are subject to heavy disturbance, some processing is needed to build the mosaic. Once the processes are defined, we present our model. This model is built upon a cloud computing environment using Web services workflow. Then we present how the processes are dynamically organized using a scheduler. This scheduler chooses the order and the processes to apply to every picture to build the mosaic. Once we obtain a mosaic we can study the variation of the snow cover.

Ranisavljevi?, Élisabeth; Devin, Florent; Laffly, Dominique; Le Nir, Yannick

2014-04-01

157

Near-Infrared Polarization Images of The Orion Molecular Cloud 1 South Region  

E-print Network

We present the polarization images in the $J$, $H$, & $Ks$ bands of the Orion Molecular Cloud 1 South region. The polarization images clearly show at least six infrared reflection nebulae (IRNe) which are barely seen or invisible in the intensity images. Our polarization vector images also identify the illuminating sources of the nebulae: IRN 1 & 2, IRN 3, 4, & 5, and IRN 6 are illuminated by three IR sources, Source 144-351, Source 145-356, and Source 136-355, respectively. Moreover, our polarization images suggest the candidate driving sources of the optical Herbig-Haro objects for the first time; HH529, a pair of HH202 and HH528 or HH 203/204, HH 530 and HH269 are originated from Source 144-351, Source 145-356, and Source 136-355, respectively.

Jun Hashimoto; Motohide Tamura; Ryo Kandori; Nobuhiko Kusakabe; Yasushi Nakajima; Shuji Sato; Chie Nagashima; Mikio Kurita; Tetsuya Nagata; Takahiro Nagayama; Jim Hough

2006-12-18

158

Infrared Cloud Imager Development for Atmospheric Optical Communication Characterization, and Measurements at the JPL Table Mountain Facility  

NASA Astrophysics Data System (ADS)

The continuous demand for high data return in deep space and near-Earth satellite missions has led NASA and international institutions to consider alternative technologies for high-data-rate communications. One solution is the establishment of wide-bandwidth Earth-space optical communication links, which require (among other things) a nearly obstruction-free atmospheric path. Considering the atmospheric channel, the most common and most apparent impairments on Earth-space optical communication paths arise from clouds. Therefore, the characterization of the statistical behavior of cloud coverage for optical communication ground station candidate sites is of vital importance. In this article, we describe the development and deployment of a ground-based, long-wavelength infrared cloud imaging system able to monitor and characterize the cloud coverage. This system is based on a commercially available camera with a 62-deg diagonal field of view. A novel internal-shutter-based calibration technique allows radiometric calibration of the camera, which operates without a thermoelectric cooler. This cloud imaging system provides continuous day-night cloud detection with constant sensitivity. The cloud imaging system also includes data-processing algorithms that calculate and remove atmospheric emission to isolate cloud signatures, and enable classification of clouds according to their optical attenuation. Measurements of long-wavelength infrared cloud radiance are used to retrieve the optical attenuation (cloud optical depth due to absorption and scattering) in the wavelength range of interest from visible to near-infrared, where the cloud attenuation is quite constant. This article addresses the specifics of the operation, calibration, and data processing of the imaging system that was deployed at the NASA/JPL Table Mountain Facility (TMF) in California. Data are reported from July 2008 to July 2010. These data describe seasonal variability in cloud cover at the TMF site, with cloud amount (percentage of cloudy pixels) peaking at just over 51 percent during February, of which more than 60 percent had optical attenuation exceeding 12 dB at wavelengths in the range from the visible to the near-infrared. The lowest cloud amount was found during August, averaging 19.6 percent, and these clouds were mostly optically thin, with low attenuation.

Nugent, P. W.; Shaw, J. A.; Piazzolla, S.

2013-02-01

159

On dictionary adaptation for recurrent pattern image coding.  

PubMed

In this paper, we exploit a recently introduced coding algorithm called multidimensional multiscale parser (MMP) as an alternative to the traditional transform quantization-based methods. MMP uses approximate pattern matching with adaptive multiscale dictionaries that contain concatenations of scaled versions of previously encoded image blocks. We propose the use of predictive coding schemes that modify the source's probability distribution, in order to favour the efficiency of MMP's dictionary adaptation. Statistical conditioning is also used, allowing for an increased coding efficiency of the dictionaries' symbols. New dictionary design methods, that allow for an effective compromise between the introduction of new dictionary elements and the reduction of codebook redundancy, are also proposed. Experimental results validate the proposed techniques by showing consistent improvements in PSNR performance over the original MMP algorithm. When compared with state-of-the-art methods, like JPEG2000 and H.264/AVC, the proposed algorithm achieves relevant gains (up to 6 dB) for nonsmooth images and very competitive results for smooth images. These results strongly suggest that the new paradigm posed by MMP can be regarded as an alternative to the one traditionally used in image coding, for a wide range of image types. PMID:18701400

Rodrigues, Nuno M M; da Silva, Eduardo A B; de Carvalho, Murilo B; de Faria, Sérgio M M; da Silva, Vitor M M

2008-09-01

160

Faxed document image restoration method based on local pixel patterns  

NASA Astrophysics Data System (ADS)

A method for restoring degraded faxed document images using the patterns of pixels that construct small areas in a document is proposed. The method effectively restores faxed images that contain the halftone textures and/or density salt-and-pepper noise that degrade OCR system performance. The halftone image restoration process, white-centered 3 X 3 pixels, in which black-and-white pixels alternate, are identified first using the distribution of the pixel values as halftone textures, and then the white center pixels are inverted to black. To remove high-density salt- and-pepper noise, it is assumed that the degradation is caused by ill-balanced bias and inappropriate thresholding of the sensor output which results in the addition of random noise. Restored image can be estimated using an approximation that uses the inverse operation of the assumed original process. In order to process degraded faxed images, the algorithms mentioned above are combined. An experiment is conducted using 24 especially poor quality examples selected from data sets that exemplify what practical fax- based OCR systems cannot handle. The maximum recovery rate in terms of mean square error was 98.8 percent.

Akiyama, Teruo; Miyamoto, Nobuo; Oguro, Masami; Ogura, Kenji

1998-04-01

161

Magnetic resonance imaging pattern recognition in hypomyelinating disorders  

PubMed Central

Hypomyelination is observed in the context of a growing number of genetic disorders that share clinical characteristics. The aim of this study was to determine the possible role of magnetic resonance imaging pattern recognition in distinguishing different hypomyelinating disorders, which would facilitate the diagnostic process. Only patients with hypomyelination of known cause were included in this retrospective study. A total of 112 patients with Pelizaeus–Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus–Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis, Salla disease and fucosidosis were included. The brain scans were rated using a standard scoring list; the raters were blinded to the diagnoses. Grouping of the patients was based on cluster analysis. Ten clusters of patients with similar magnetic resonance imaging abnormalities were identified. The most important discriminating items were early cerebellar atrophy, homogeneity of the white matter signal on T2-weighted images, abnormal signal intensity of the basal ganglia, signal abnormalities in the pons and additional T2 lesions in the deep white matter. Eight clusters each represented mainly a single disorder (i.e. Pelizaeus–Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, infantile GM1 and GM2 gangliosidosis, Pelizaeus–Merzbacher-like disease and fucosidosis); only two clusters contained multiple diseases. Pelizaeus–Merzbacher-like disease was divided between two clusters and Salla disease did not cluster at all. This study shows that it is possible to separate patients with hypomyelination disorders of known cause in clusters based on magnetic resonance imaging abnormalities alone. In most cases of Pelizaeus–Merzbacher disease, hypomyelination with congenital cataract, hypomyelination with hypogonadotropic hypogonadism and hypodontia, Pelizaeus–Merzbacher-like disease, infantile GM1 and GM2 gangliosidosis and fucosidosis, the imaging pattern gives clues for the diagnosis. PMID:20881161

Steenweg, Marjan E.; Vanderver, Adeline; Blaser, Susan; Bizzi, Alberto; de Koning, Tom J.; Mancini, Grazia M. S.; van Wieringen, Wessel N.; Barkhof, Frederik; Wolf, Nicole I.

2010-01-01

162

Clouds as Seen by Satellite Sounders (3I) and Imagers (ISCCP). Part I: Evaluation of Cloud Parameters.  

NASA Astrophysics Data System (ADS)

The improved initialization inversion (3I) algorithms convert TIROS-N Operational Vertical Sounder observations from the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting environmental satellites into atmospheric temperature and water vapor profiles, together with cloud and surface properties. Their relatively good spectral resolution and coverage make IR sounders a very useful tool for the determination of cloud properties both day and night. The iterative process of detailed comparisons between cloud parameters obtained from this global dataset, which is available in the framework of the NOAA-National Aeronautics and Space Administration Pathfinder Program, with time-space-collocated observations of clouds from the recently reprocessed International Satellite Cloud Climatology Project (ISCCP) dataset has led to an improved 3I cloud analysis scheme based on a weighted-2 method described in the second article of this series. This process also provides a first evaluation of the ISCCP reanalysis. The new 3I cloud scheme obtains cloud properties very similar to those from ISCCP for homogeneous cloud scenes. Improvement is especially notable in the stratocumulus regimes where the new 3I scheme detects much more of the low-level cloudiness. Remaining discrepancies in cloud classification can now be explained by differences in cloud detection sensitivity, differences in temperature profiles used, and inhomogeneous or partly cloudy fields. Cirrus cloud identification during the daytime in the recent ISCCP dataset is improved relative to the first version of ISCCP, but is still an underestimate. At night only multispectral IR analyses like 3I can provide cirrus information. The reprocessed ISCCP dataset also shows considerable improvement in cloud cover at higher latitudes. Differences in 3I and ISCCP summertime cloud cover over deserts may be caused by different sensitivities to dust storms.

Stubenrauch, C. J.; Rossow, W. B.; Chéruy, F.; Chédin, A.; Scott, N. A.

1999-08-01

163

Hubble Space Telescope Imaging of Decoupled Dust Clouds in the Ram Pressure Stripped Virgo Spirals NGC 4402 and NGC 4522  

NASA Astrophysics Data System (ADS)

We present the highest-resolution study to date of the interstellar medium (ISM) in galaxies undergoing ram pressure stripping, using Hubble Space Telescope BVI imaging of NGC 4522 and NGC 4402, Virgo Cluster spirals that are well known to be experiencing intracluster medium (ICM) ram pressure. We find that throughout most of both galaxies, the main dust lane has a fairly well-defined edge, with a population of giant molecular cloud (GMC) sized (tens- to hundreds-of-pc scale), isolated, highly extincting dust clouds located up to ~1.5 kpc radially beyond it. Outside of these dense clouds, the area has little or no diffuse dust extinction, indicating that the clouds have decoupled from the lower-density ISM material that has already been stripped. Several of the dust clouds have elongated morphologies that indicate active ram pressure, including two large (kpc scale) filaments in NGC 4402 that are elongated in the projected ICM wind direction. We calculate a lower limit on the H I + H2 masses of these clouds based on their dust extinctions and find that a correction factor of ~10 gives cloud masses consistent with those measured in CO for clouds of similar diameters, probably due to the complicating factors of foreground light, cloud substructure, and resolution limitations. Assuming that the clouds' actual masses are consistent with those of GMCs of similar diameters (~104-105 M ?), we estimate that only a small fraction (~1%-10%) of the original H I + H2 remains in the parts of the disks with decoupled clouds. Based on H? images, a similar fraction of star formation persists in these regions, 2%-3% of the estimated pre-stripping star formation rate. We find that the decoupled cloud lifetimes may be up to 150-200 Myr.

Abramson, Anne; Kenney, Jeffrey D. P.

2014-03-01

164

Adaptive pattern-based image compression for ultra-low bandwidth weapon seeker image communication  

NASA Astrophysics Data System (ADS)

The effectiveness of autonomous munitions systems can be enhanced by transmitting target images to a man-in-the-loop (MITL) as the system deploys. Based on the transmitted images, the MITL could change target priorities or conduct damage assessment in real-time. One impediment to this enhancement realization is the limited bandwidth of the system data-link. In this paper, an innovative pattern-based image compression technology is presented for enabling efficient image transmission over the ultra-low bandwidth system data link, while preserving sufficient details in the decompressed images for the MITL to perform the required assessments. Based on a pattern-driven image model, our technology exploits the structural discontinuities in the image by extracting and prioritizing edge segments with their geometric and intensity profiles. Contingent on the bit budget, only the most salient segments are encoded and transmitted, therefore achieving scalable bit-streams. Simulation results corroborate the technology efficiency and establish its subjective quality superiority over JPEG/JPEG2000 as well as feasibility for real-time implementation. Successful technology demonstrations were conducted using images from surrogate seekers in an aircraft and from a captive-carry test-bed system. The developed technology has potential applications in a broad range of network-enabled weapon systems.

Wei, Hai; Zabuawala, Sakina; Varadarajan, Karthik M.; Yadegar, Jacob; Yadegar, Joseph; Gray, David; McCalmont, John; Utt, James

2009-05-01

165

An adaptive OPD and dislocation prediction used characteristic of interference pattern for interference hyperspectral image compression  

Microsoft Academic Search

According to the imaging principle and characteristic of LASIS (Large Aperture Static Interference Imaging Spectrometer), we discovered that the 3D (three dimensional) image sequences formed by different interference pattern frames, which were formed in the imaging process of LASIS Interference hyperspectral image, had much stronger correlation than the original interference hyperspectral image sequences, either in 2D (two dimensional) spatial domain

Jia Wen; Caiwen Ma; Penglang Shui

2011-01-01

166

Investigating the Effects of Water Ice Cloud Radiative Forcing on the Predicted Patterns and Strength of Dust Lifting on Mars  

NASA Astrophysics Data System (ADS)

The dust cycle is critical for the current Mars climate system because airborne dust significantly influences the thermal and dynamical structure of the atmosphere. The atmospheric dust loading varies with season and exhibits variability on a range of spatial and temporal scales. Until recently, interactive dust cycle modeling studies that include the lifting, transport, and sedimentation of radiatively active dust have not included the formation or radiative effects of water ice clouds. While the simulated patterns of dust lifting and global dust loading from these investigations of the dust cycle in isolation reproduce some characteristics of the observed dust cycle, there are also marked differences between the predictions and the observations. Water ice clouds can influence when, where, and how much dust is lifted from the surface by altering the thermal structure of the atmosphere and the character and strength of the general circulation. Using an updated version of the NASA Ames Mars Global Climate Model (GCM), we show that including water ice cloud formation and their radiative effects affect the magnitude and spatial extent of dust lifting, particularly in the northern hemisphere during the pre- and post- winter solstitial seasons. Feedbacks between dust lifting, cloud formation, circulation intensification and further dust lifting are isolated and shown to be important for improving the behavior of the simulated dust cycle.

Kahre, Melinda A.; Hollingsworth, Jeffery L.; Haberle, Robert M.

2014-11-01

167

Deep Uranus Cloud Structure and Methane Mixing Ratio as Constrained by Keck AO Imaging Observations.  

NASA Astrophysics Data System (ADS)

Keck AO imaging of Uranus in 2004 with H and H-continuum filters provide deep views of scattered light in the Uranian atmosphere with different sensitivities to methane absorption and collision-induced absorption by Hydrogen. After deconvolution, these images provide accurate low-latitude center-to-limb (east-west) profiles out to view angles of nearly 80 degrees, permitting solutions for both cloud properties and the methane mixing ratio. After accounting for a very small high-altitude haze contribution, the observed central disk I/F values for H and H-continuum filters can be modeled using an opaque semi-infinite cloud of very low albedo (near 0.04), a broken cloud of high albedo (fractional coverage near 0.04-.06), or a continuous cloud of low optical depth (0.2-1.0) containing particles of high single-scattering albedo. For low methane mixing ratios (0.5-1 percent) the central disk I/F values require a deep cloud (near 8 bars), while for the high methane mixing ratios (2-4 percent) a higher altitude solution is possible (near 3 bars). However, the observed slightly limb-brightened and relatively flat center-to-limb H-continuum profile is only consistent with an optically thin cloud. The best-fit solution is a low methane mixing ratio (0.75-1.0 percent vmr), and a deep low opacity cloud (optical depth ranging from 0.2 to 0.4 for scattering asymmetry parameters ranging from 0 to 0.3). This CH4 mixing ratio is slightly below the lower limit of the Baines et al. (1995, Icarus 114, 328-340) result of 1.6(+0.7/-0.5) percent. This work was supported by NASA's Planetary Astronomy and Planetary Atmospheres programs and the W.M. Keck Observatory. We thank those of Hawaiian ancestry whose generous hospitality in allowing use of their sacred mountain made the observations possible.

Sromovsky, Lawrence A.; Fry, P. M.

2006-09-01

168

Ice Cloud Optical and Microphysical Properties from the CALIPSO Imaging Infrared Radiometer  

NASA Astrophysics Data System (ADS)

We will present cirrus cloud optical and microphysical properties as retrieved from the operational analysis of the Imaging Infrared Radiometer (IIR) data in synergy with the CALIOP lidar co-located observations collected in the framework of the CALIPSO mission. The IIR data provides nighttime and daytime independent retrievals of optical depth and effective diameter, from which the cloud layer ice water path is inferred. The technique takes advantage of the vertical information provided by CALIOP to select suitable scenes and compute effective emissivity and optical depth. Effective diameters are retrieved through microphysical indices defined as the ratio of the effective infrared optical depths in the two pairs of channels 10.6-12.05 ?m and 8.65-12.05 ?m, and are related to the ice crystal effective diameter and shape through pre-computed Look-Up Tables. Sources of uncertainty are discussed and possible biases are assessed through internal consistency checks. Comparisons of IIR and CALIOP cirrus optical depths show the very good sensitivity of the IIR retrievals, down to 0.05 visible optical depth. It is shown that particle effective diameter and cloud layer ice water path of single-layered cirrus clouds can be retrieved over ocean, land, as well as over low opaque clouds, for thin to dense clouds of visible optical depth ranging between 0.1 and 6 and of ice water path found typically between 1 and 150 g.m-2. Taking advantage of the cloud boundaries simultaneously derived by CALIOP, IIR power law relationships between mean ice water content (IWC, in g.m-3) and mean extinction coefficient (?, in m-1) are established for cloud temperatures between 190 and 233 K. An average global power law relationship IWC = 75. ?1.23 is obtained, which compares well with parameterizations derived from in-situ observations at mid-latitude and in the tropics. However, the IWCs reported in our study are lower by about 40% than those derived from the power law relationship used in the CALIOP Version 3 algorithm. The IIR and CALIOP Level 2 operational products (currently Version 3) are publicly available at NASA Langley ASDC and ICARE data center.

Garnier, A.; Pelon, J.; Dubuisson, P.; Yang, P.; Vaughan, M.; Avery, M. A.; Winker, D. M.

2013-12-01

169

Multi Spectral Pushbroom Imaging Radiometer (MPIR) for remote sensing cloud studies  

SciTech Connect

A Multi Spectral Pushbroom Imaging Radiometer (MPIR) has been developed as are relatively inexpensive ({approximately}$IM/copy), well-calibrated,imaging radiometer for aircraft studies of cloud properties. The instrument is designed to fly on an Unmanned Aerospace Vehicle (UAV) platform at altitudes from the surface up to 20 km. MPIR is being developed to support the Unmanned Aerospace Vehicle portion of the Department of Energy`s Atmospheric Radiation Measurements program (ARM/UAV). Radiation-cloud interactions are the dominant uncertainty in the current General Circulation Models used for atmospheric climate studies. Reduction of this uncertainty is a top scientific priority of the US Global Change Research Program and the ARM program. While the DOE`s ARM program measures a num-ber of parameters from the ground-based Clouds and Radiation Testbed sites, it was recognized from the outset that other key parameters are best measured by sustained airborne data taking. These measurements are critical in our understanding of global change issues as well as for improved atmospheric and near space weather forecasting applications.

Phipps, G.S.; Grotbeck, C.L.

1995-10-01

170

Forecasting for Grid and Cloud Computing On-Demand Resources Based on Pattern Matching  

Microsoft Academic Search

Abstract: The Cloud phenomenon,brings along the cost-saving benefit of dynamic scaling. Knowledge in advance is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose a new approach to the problem of workload prediction based on identifying similar past occurrences to the current short-term workload history. We present in detail the

Eddy Caron; Frédéric Desprez; Adrian Muresan

2010-01-01

171

Horizontal structure of planetary-scale waves at the cloud top of Venus deduced from Galileo SSI images with an improved cloud-tracking technique  

NASA Astrophysics Data System (ADS)

An improved cloud tracking method for deriving wind velocities from successive planetary images was developed. The new method incorporates into the traditional cross-correlation method an algorithm that corrects for erroneous cloud motion vectors by re-determining the most plausible correlation peak among all of the local maxima on the correlation surface by comparing each vector with its neighboring vectors. The newly developed method was applied to the Venusian violet images obtained by the Solid State Imaging system (SSI) onboard the Galileo spacecraft during its Venus flyby. Although the results may be biased by the choice of spatial scale of atmospheric features, the cloud tracking is the most practical mean of estimating the wind velocities with extensive spatial and temporal coverage. The two-dimensional distribution of the horizontal wind vector field over 5 days was obtained. It was found from these wind maps that the solar-fixed component in 1990 was similar to that in 1982 obtained by the Pioneer Venus orbiter. The deviation of the instantaneous zonal wind field from the solar-fixed component shows a distinct wavenumber-1 structure in the equatorial region. On the assumption that this structure is a manifestation of an equatorial Kelvin wave, the phase relationship between the zonal wind and the cloud brightness suggests a short photochemical lifetime of the violet absorber. The momentum deposition by this Kelvin wave, which is subject to radiative damping, would induce a westward mean-wind acceleration of ?0.3 m s-1 per Earth day.

Kouyama, Toru; Imamura, Takeshi; Nakamura, Masato; Satoh, Takehiko; Futaana, Yoshihumi

2012-01-01

172

Measurement of Aerosol and Cloud Particles with PACS and HARP Hyperangular Imaging Polarimeters  

NASA Astrophysics Data System (ADS)

PACS is new hyper-angular imaging polarimeter for aeorosol and cloud measurerents designed to meet the requirements of the proposed ACE decadal survey mission. The full PACS system consists of three wide field of view (110deg cross track) telescopes covering the UV, VNIR, and SWIR spectral ranges with angular coverage between +55 deg forward to -55deg backwards. The angular density can be selected to cover up to 100 different viewing angles at selected wavelengths. PACS_VNIR is a prototype airborne instrument designed to demonstrate PACS capability by deploying just one of the three wavelength modules of the full PACS. With wavelengths at 470, 550, 675, 760 and 875nm, PACS_VNIR flew for the first time during the PODEX experiment in January/February 2013 aboard the NASA ER-2 aircraft. PACS SWIR (1.64, 1.88, 2.1, and 2.25um) is currently under construction and should be operational in the lab by Fall/2013. PACS_ UV has been fully designed, but is not yet under construction. During the PODEX flights PACS_VNIR collected data for aerosol and clouds over variable surface types including, water, vegetation, urban areas, and snow. The data is currently being calibrated, geolocated and prepared for the inversion of geophysical parameters including water cloud size distribution and aerosol microphysical parameters. The large density of angles in PACS allows for the characterization of cloudbow features in relatively high spatial resolution in a pixel to pixel basis. This avoids the need for assumptions of cloud homogeneity over any distance. The hyperangle capability also allows detailed observation of cloud ice particles, surface characterization, and optimum selection of the number of angles desired for aerosol retrievals. The aerosol and cloud retrieval algorithms under development for the retrieval of particle microphysical properties from the PACS data will be discussed in this presentation. As an extension of the PACS concept we are currently developing the HARP (Hyper-Angular Rainbow Polarimeter) Cubesat satellite funded by the NASA/ESTO/InVEST program. HARP will demonstrate the PACS concept from space and will allow for high resolution angular measurements of polarized radiances over different aerosol and cloud scenarios. The HARP concept and strategy will be presented and discussed as part of the general PACS measurement strategy.

Martins, J.; Fernandez-Borda, R.; Remer, L. A.; Sparr, L.; Buczkowski, S.; Munchak, L. A.

2013-12-01

173

Spatial-temporal change in precipitation patterns based on the cloud model across the Wei River Basin, China  

NASA Astrophysics Data System (ADS)

It is of significant importance to investigate the spatial-temporal change in precipitation patterns due to its great effects on droughts, floods, soil erosion and water resource management. A complete investigation of precipitation structure and its distribution pattern based on daily precipitation covering 1960-2005 at 21 meteorological stations in the Wei River Basin has been performed. In order to comprehensively and objectively describe the changing pattern of precipitation, the cloud model is employed to quantitatively analyse the average, uniformity and stability of precipitation. Results indicate the following: (1) the occurrence of different precipitation durations exhibits a positive exponential curve with the decrease in precipitation durations, and 1-3-day events are the predominant precipitation events which have an increasing trend; (2) precipitation and its non-uniformity is increasingly reducing, while its stability increases initially then decreases; (3) mean precipitation reduces from southeast to northwest, and the precipitation of the Guanzhong Plain has a low uniformity and stability due to its location and increasingly intensifying human activities. The cloud model provides a new idea and quantitative measure for the evaluation of the uniformity and stability of precipitation.

Huang, Shengzhi; Hou, Beibei; Chang, Jianxia; Huang, Qiang; Chen, Yutong

2014-05-01

174

Bistatic imaging lidar measurements of aerosols, fogs, and clouds in the lower atmosphere  

NASA Astrophysics Data System (ADS)

We have been developing a bistatic imaging lidar using a high sensitive CCD camera with an image intensifier as a high speed shutter for measuring spatial distributions of aerosols, fogs and clouds in the lower atmosphere at daytime as well as at nighttime. The bistatic imaging lidar was applied to two field observation campaigns. One was made cooperatively with a wind profiler and a radiosonde at Moriya (36 km north of Tokyo) for five days from May 26 to 30, 1997 and another cooperatively with a monostatic lidar at Hakuba alpine ski area of Nagano for 10 days from February 7 to 16, 1998 during the period of the 18th Winter Olympic Games in Japan. We report the results obtained at both campaigns and discuss the ability of this system in measuring the meteorological features of the local lower atmosphere under different conditions.

Lin, Jinming; Mishima, Hidetsugu; Kawahara, Takuya D.; Saito, Yasunori; Nomura, Akio; Yamaguchi, Kenji; Morikawa, Kimio

1998-08-01

175

Imaging Dot Patterns for Measuring Gossamer Space Structures  

NASA Technical Reports Server (NTRS)

A paper describes a photogrammetric method for measuring the changing shape of a gossamer (membrane) structure deployed in outer space. Such a structure is typified by a solar sail comprising a transparent polymeric membrane aluminized on its Sun-facing side and coated black on the opposite side. Unlike some prior photogrammetric methods, this method does not require an artificial light source or the attachment of retroreflectors to the gossamer structure. In a basic version of the method, the membrane contains a fluorescent dye, and the front and back coats are removed in matching patterns of dots. The dye in the dots absorbs some sunlight and fluoresces at a longer wavelength in all directions, thereby enabling acquisition of high-contrast images from almost any viewing angle. The fluorescent dots are observed by one or more electronic camera(s) on the Sun side, the shade side, or both sides. Filters that pass the fluorescent light and suppress most of the solar spectrum are placed in front of the camera(s) to increase the contrast of the dots against the background. The dot image(s) in the camera(s) are digitized, then processed by use of commercially available photogrammetric software.

Dorrington, A. A.; Danehy, P. M.; Jones, T. W.; Pappa, R. S.; Connell, J. W.

2005-01-01

176

Characterizing Spatial Patterns of Cloud Cover and Fog Inundation in the Northern Channel Islands Using Satellite Datasets and Comparison to Ground Measurements  

NASA Astrophysics Data System (ADS)

Coastal forests in Mediterranean climates are frequently covered by clouds or immersed in fog. Previous studies suggest that clouds strongly modulate forest distributions as well as carbon budgets in these semi-arid environments. Both low level stratocumulus cloud cover and fog can enhance the water status of vegetation along the Californian coast and the Channel Islands by reducing solar insolation, raising relative humidity and supplying water directly to the landscape during otherwise warm and rainless summers. While summertime fog and stratus cover in California's Channel Islands can ameliorate summer drought stress and enhance soil water budgets, they have different spatial patterns. These differing spatial patterns and the resulting shifts in relative ecological importance of fog and stratus are largely unknown. The overall objective of this project was to map spatial distributions of daytime cloud cover frequency for the California Channel Islands, and to predict probabilities of surface cloud (fog) contact and immersion for these islands. Daytime cloud cover maps were generated for the Channel Islands using data from GOES satellite imagery. Cloud frequency maps were compared and found to be in agreement with solar insolation data collected at several sites on Santa Cruz and Santa Rosa islands for the summer of 2005. These cloud frequency maps were then combined with airport cloud height data and topographic data to map estimated weekly and monthly fog inundation. The fog inundation maps were then compared to fog drip data collected at several sites on the two islands. Correlation between fog inundation and fog drip accumulation enabled spatial and temporal extrapolation to understand seasonal and inter-annual variations in cloud cover frequency and fog inundation and drip. Future studies will use these cloud and fog distributions for water balance modeling and studies of plant geography and forest distributions.

Rastogi, B.; Still, C. J.; Fischer, D. T.; Iacobellis, S. F.; Toomey, M. P.; Greer, B.; Baguskas, S. A.; Williams, P.; McEachern, K.

2012-12-01

177

A novel method of intelligent analysis of weave pattern based on image processing technology  

Microsoft Academic Search

This paper proposed a new method based on image processing and pattern recognition technology to recognize the pattern of woven fabric. The method disposed the information of both the top and bottom fabric images. The result of analyzing the regularity of the intensity variation of the horizontal and vertical direction of image can be used to determine the interlacing position

Xinxing Tu; Ping Zhong; Binjie Xin; Shile Wang

2011-01-01

178

High-resolution imaging and target designation through clouds or smoke  

DOEpatents

A method and system of combining gated intensifiers and advances in solid-state, short-pulse laser technology, compact systems capable of producing high resolution (i.e., approximately less than 20 centimeters) optical images through a scattering medium such as dense clouds, fog, smoke, etc. may be achieved from air or ground based platforms. Laser target designation through a scattering medium is also enabled by utilizing a short pulse illumination laser and a relatively minor change to the detectors on laser guided munitions.

Perry, Michael D. (Downy, CA)

2003-01-01

179

Computationally efficient approach to three-dimensional point cloud reconstruction from video image sequences  

NASA Astrophysics Data System (ADS)

This paper presents a computationally efficient solution to three-dimensional point cloud reconstruction from video image sequences that are captured by a hand-held camera. Our solution starts with a frame selection step to remove frames that cause physically nonrealizable reconstruction outcomes. Then, a computationally efficient approach for obtaining the absolute camera pose is introduced based on pairwise relative camera poses. This is followed by a computationally efficient rotation registration to update the absolute camera pose. The reconstruction results obtained based on actual video sequences indicate lower computation times and lower reprojection errors of the introduced approach compared to the conventional approach.

Chang, Chih-Hsiang; Kehtarnavaz, Nasser

2014-05-01

180

3D imaging of antenna fields from electronically synthesised scalar intensity patterns  

Microsoft Academic Search

This work describes a new technique for the determination of antenna far field radiation patterns and the imaging of antenna fields from holographic intensity patterns. These intensity patterns are obtained by combining the sampled antenna near field with an electronically synthesised offset reference plane wave. The resultant intensity pattern can be recorded in a fast and inexpensive manner. This work

D. Smith; M. Leach

2003-01-01

181

Using Geotags to Derive Rich Tag-Clouds for Image Annotation  

NASA Astrophysics Data System (ADS)

Geotagging has become popular for many multimedia applications. In this chapter, we present an integrated and intuitive system for location-driven tag suggestion, in the form of tag-clouds, for geotagged photos. Potential tags from multiple sources are extracted and weighted. Sources include points of interest (POI) tags from a public Geographic Names Information System (GNIS) database, community tags from Flickr® pictures, and personal tags shared through users' own, family, and friends' photo collections. To increase the effectiveness of GNIS POI tags, bags of place-name tags are first retrieved, clustered, and then re-ranked using a combined tf-idf and spatial distance criteria. The community tags from photos taken in the vicinity of the input geotagged photo are ranked according to distance and visual similarity to the input photo. Personal tags from other personally related photos inherently carry a significant weight due more to their high relevance than to both the generic place-name tags and community tags, and are ranked by weights that decay over time and distance differences. Finally, a rich set of the most relevant location-driven tags is presented to the user in the form of individual tag clouds under the three mentioned source categories. The tag clouds act as intuitive suggestions for tagging an input image. We also discuss quantitative and qualitative findings from a user study that we conducted. Evaluation has revealed the respective benefits of the three categories toward the effectiveness of the integrated tag suggestion system.

Joshi, Dhiraj; Luo, Jiebo; Yu, Jie; Lei, Phoury; Gallagher, Andrew

182

A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud.  

PubMed

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)-Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks. PMID:23970943

Seenivasagam, V; Velumani, R

2013-01-01

183

A QR Code Based Zero-Watermarking Scheme for Authentication of Medical Images in Teleradiology Cloud  

PubMed Central

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks. PMID:23970943

Seenivasagam, V.; Velumani, R.

2013-01-01

184

A Time-Series Pattern Based Noise Generation Strategy for Privacy Protection in Cloud Computing  

Microsoft Academic Search

Cloud computing promises an open environment where customers can deploy IT services in a pay-as-you-go fashion while saving huge capital investment in their own IT infrastructure. Due to the openness, various malicious service providers may exist. Such service providers may record service information in a service process from a customer and then collectively deduce the customer's private information. Therefore, from

Gaofeng Zhang; Yun Yang; Xiao Liu; Jinjun Chen

2012-01-01

185

Calibration and Laboratory Test of the Department of Energy Cloud Particle Imager  

SciTech Connect

Calibration parameters from the Connolly et al. (2007) algorithm cannot be applied to the Department of Energy's (DOE) CPI because the DOE CPI is version 2.0. Thus, Dr. Junshik Um and Prof. Greg McFarquhar brought the DOE CPI to the University of Manchester, UK, where facilities for calibrating it were available. In addition, two other versions of CPIs (1.0 and 1.5) were available on-site at the University of Manchester so that an intercomparison of three different versions of the CPI was possible. The three CPIs (versions 1.0, 1.5, and 2.0) were calibrated by moving glass calibration beads and ice analogues of known size parallel to the object plane. The distance between the object plane and a particle, the particle's focus, its apparent maximum dimension, and a background image were measured in order to derive calibration parameters for each CPI version. The calibration parameters are used in two empirical equations that are applied to in situ CPI data to determine particle size and depth of field, and hence particle size distributions (PSDs). After the tests with the glass calibration beads to derive the calibration parameters, the three CPIs were installed at the base of the Manchester Ice Cloud Chamber and connected to air pumps that drew cloud through the sample volume. Warm liquid clouds at a temperature of 1-2 C and ice clouds at a temperature of -5 C were generated, and the resulting PSDs for each of the CPIs were determined by applying the results of each calibration.

McFarquhar, GM; Um, J

2012-02-17

186

Analysis of watershed landscape pattern change based on TM images  

NASA Astrophysics Data System (ADS)

Based on analysis of remote sensing images, statistic data of Yuqiao watershed in Tianjin from 1999 to 2009, and with the technology of Remote Sensing (abbr. RS) and Geographic Information System (abbr. GIS), At the same time, according to Maximum Likelihood Classifier (MLC) , Support Vector Machines (SVM) classifier ,statistical analysis and correlation analysis, we can quantitatively analyze landscape pattern change of Yuqiao watershed by calculating its Landscape diversity index, landscape shape index, Patch density, Edge density and contagion, etc. As a result, significant land-use changes have taken place in the Yuqiao watershed over during the ten years due to urbanization. Farmland has a notable increase. Meanwhile; there is a remarkable decrease in grass and shrub land. The farmland landscape's LSI from 145.72 increased 207.89 from 1999 to 2009, according to the complex and anomalous of farmland, which indicates that the way people cultivate the farmland, not only causes farmland quantity increase, but also makes the shape becomes complex. In the end, some advice will be given that human beings should adjust land-use structure in lake districts. The study of the integration of TM images and GIS technique is an effective approach to analyze the landscape changes in the watershed.

Li, Chongwei; Wang, Sa; Zhao, Yongli

2011-06-01

187

Coordinated Imaging and Lidar measurements of Noctilucent Cloud Dynamics over Poker Flat, Alaska, August 2005.  

NASA Astrophysics Data System (ADS)

In conjunction with the 2005 Polar Aeronomy and Radio Science (PARS) Summer School coordinated observations of noctilucent clouds (NLC) were made from central Alaska during August 2005 using imaging and lidar instrumentation. The image measurements was made from a field site near Donnelly Dome (63° N, 145° W) to record NLC over the lidar facility located at Poker Flat Research Range (PFRR) approximately 160 km to the north. A combination of two low-light digital color video cameras and several digital SLR cameras were used to image the NLC field over PFRR using wide and narrow field optics. At the same time NLC observations were made using the NICT Rayleigh lidar to investigate their altitude, structure and backscatter strength. Strong NLC were imaged from Donnelly Dome on three consecutive nights (August 8-10). These events were extensive, filling the northern twilight sky and were observed for over 4 hours. In particular the display of August 9 was very bright and was observed to extend well to the south of PFRR. The lidar measurements on this night were the strongest NLC signal yet recorded at PFRR. In this talk we will present a comparison between the imaging and lidar data focusing on August 9 display which was highly dynamic and observed to split into two distinct layers separated by approximately 1 km after local midnight. The two data sets will be used to study the dynamics of this display.

Nielsen, K.; Taylor, M. J.; Jensen, P. F.; Collins, R. L.; Su, L.; Thurairajah, B.; McDonald, J. G.; Marlow, Z. J.

2005-12-01

188

A method of using commercial virtual satellite image to check the pattern painting spot effect  

NASA Astrophysics Data System (ADS)

A method of using commercial virtual satellite image to check the pattern painting spot effect contrast with the satellite images before painting and after painting have been discussed. Using a housetop as the testing platform analyses and discusses the factors' influence such as resolution of satellite image, spot size and color of pattern painting spot and pattern painting camouflage method choosing to the plan implement. The pattern painting design and spot size used in the testing has been ensured, and housetop pattern painting has been painted. Finally, the small spot pattern painting camouflage effect of engineering using upon painting pattern size, color and texture have been checked, contrasting with the satellite image before painting and after painting.

Wang, Zheng-gang; Kang, Qing; Shen, Zhi-qiang; Cui, Chang-bin

2014-02-01

189

Detecting Digital Image Forgeries Using Sensor Pattern Noise Jan Luks, Jessica Fridrich, and Miroslav Goljan  

E-print Network

Detecting Digital Image Forgeries Using Sensor Pattern Noise Jan Lukás, Jessica Fridrich-6000 ABSTRACT We present a new approach to detection of forgeries in digital images under the assumption forgeries and on non-forged images. We also investigate how further image processing applied to the forged

Fridrich, Jessica

190

Color image segmentation considering the human sensitivity for color pattern variations  

E-print Network

Color image segmentation considering the human sensitivity for color pattern variations Kuk image segmentation plays an important role in the computer vision and image processing area. In this paper, we propose a novel color image segmentation algorithm in consideration of human visual

Yoon, Kuk-Jin

191

Characterizing growth patterns in longitudinal MRI using image contrast  

NASA Astrophysics Data System (ADS)

Understanding the growth patterns of the early brain is crucial to the study of neuro-development. In the early stages of brain growth, a rapid sequence of biophysical and chemical processes take place. A crucial component of these processes, known as myelination, consists of the formation of a myelin sheath around a nerve fiber, enabling the effective transmission of neural impulses. As the brain undergoes myelination, there is a subsequent change in the contrast between gray matter and white matter as observed in MR scans. In this work, gray-white matter contrast is proposed as an effective measure of appearance which is relatively invariant to location, scanner type, and scanning conditions. To validate this, contrast is computed over various cortical regions for an adult human phantom. MR (Magnetic Resonance) images of the phantom were repeatedly generated using different scanners, and at different locations. Contrast displays less variability over changing conditions of scan compared to intensity-based measures, demonstrating that it is less dependent than intensity on external factors. Additionally, contrast is used to analyze longitudinal MR scans of the early brain, belonging to healthy controls and Down's Syndrome (DS) patients. Kernel regression is used to model subject-specific trajectories of contrast changing with time. Trajectories of contrast changing with time, as well as time-based biomarkers extracted from contrast modeling, show large differences between groups. The preliminary applications of contrast based analysis indicate its future potential to reveal new information not covered by conventional volumetric or deformation-based analysis, particularly for distinguishing between normal and abnormal growth patterns.

Vardhan, Avantika; Prastawa, Marcel; Vachet, Clement; Piven, Joseph; Gerig, Guido

2014-03-01

192

Active probing of cloud multiple scattering, optical depth, vertical thickness, and liquid water content using wide-angle imaging LIDAR.  

SciTech Connect

At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60-degree full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer, and, from there, estimate the volume-averaged liquid water content. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Here we present recent WAIL data oti various clouds and discuss the extension of WAIL to full diurnal monitoring by means of an ultra-narrow magneto-optic atomic line filter for daytime measurements.

Love, Steven P.; Davis, A. B. (Anthony B.); Rohde, C. A. (Charles A.); Tellier, L. L. (Larry L.); Ho, Cheng,

2002-01-01

193

Astronomy in the Cloud: Using MapReduce for Image Co-Addition  

NASA Astrophysics Data System (ADS)

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection and classification and moving-object tracking. Since such studies benefit from the highest-quality data, methods such as image co-addition, i.e., astrometric registration followed by per-pixel summation, will be a critical preprocessing step prior to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources such as potentially hazardous asteroids or transient objects such as supernovae, these data streams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this article we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data are partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources: i.e., platforms where Hadoop is offered as a service. We report on our experience of implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multiterabyte imaging data set provides a good testbed for algorithm development, since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image co-addition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results comparing their performance.

Wiley, K.; Connolly, A.; Gardner, J.; Krughoff, S.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-03-01

194

Thermal neutron image intensifier tube provides brightly visible radiographic pattern  

NASA Technical Reports Server (NTRS)

Vacuum-type neutron image intensifier tube improves image detection in thermal neutron radiographic inspection. This system converts images to an electron image, and with electron acceleration and demagnification between the input target and output screen, produces a bright image viewed through a closed circuit television system.

Berger, H.; Kraska, I.; Niklas, W.; Schmidt, A.

1967-01-01

195

Multi-provider architecture for cloud outsourcing of medical imaging repositories.  

PubMed

Over the last few years, the extended usage of medical imaging procedures has raised the medical community attention towards the optimization of their workflows. More recently, the federation of multiple institutions into a seamless distribution network has brought hope of increased quality healthcare services along with more efficient resource management. As a result, medical institutions are constantly looking for the best infrastructure to deploy their imaging archives. In this scenario, public cloud infrastructures arise as major candidates, as they offer elastic storage space, optimal data availability without great requirements of maintenance costs or IT personnel, in a pay-as-you-go model. However, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. This document proposes a multi-provider architecture for integration of outsourced archives with in-house PACS resources, taking advantage of foreign providers to store medical imaging studies, without disregarding security. It enables the retrieval of images from multiple archives simultaneously, improving performance, data availability and avoiding the vendor-locking problem. Moreover it enables load balancing and cache techniques. PMID:25160163

Godinho, Tiago Marques; Bastião Silva, Luís A; Costa, Carlos; Oliveira, José Luís

2014-01-01

196

Hyperspectral Reflectance Signatures and Point Clouds for Precision Agriculture by Light Weight Uav Imaging System  

NASA Astrophysics Data System (ADS)

The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, which is based on support vector regression machine. It was concluded that the central factors influencing on the accuracy of the estimation process were the quality of the image data, the quality of the image processing and digital surface model generation, and the performance of the regressor. In the wider perspective, our investigation showed that very low-weight, low-cost, hyperspectral, stereoscopic and spectrodirectional 3D UAV-remote sensing is now possible. This cutting edge technology is powerful and cost efficient in time-critical, repetitive and locally operated remote sensing applications.

Honkavaara, E.; Kaivosoja, J.; Mäkynen, J.; Pellikka, I.; Pesonen, L.; Saari, H.; Salo, H.; Hakala, T.; Marklelin, L.; Rosnell, T.

2012-07-01

197

Water vapor motion signal extraction from FY-2E longwave infrared window images for cloud-free regions: The temporal difference technique  

NASA Astrophysics Data System (ADS)

The aim of this study is to calculate the low-level atmospheric motion vectors (AMVs) in clear areas with FY-2E IR2 window (11.59-12.79 ?m) channel imagery, where the traditional cloud motion wind technique fails. A new tracer selection procedure, which we call the temporal difference technique, is demonstrated in this paper. This technique makes it possible to infer low-level wind by tracking features in the moisture pattern that appear as brightness temperature ( T B) differences between consecutive sequences of 30-min-interval FY-2E IR2 images over cloud-free regions. The T B difference corresponding to a 10% change in water vapor density is computed with the Moderate Resolution Atmospheric Transmission (MODTRAN4) radiative transfer model. The total contribution from each of the 10 layers is analyzed under four typical atmospheric conditions: tropical, midlatitude summer, U.S. standard, and midlatitude winter. The peak level of the water vapor weighting function for the four typical atmospheres is assigned as a specific height to the T B "wind". This technique is valid over cloud-free ocean areas. The proposed algorithm exhibits encouraging statistical results in terms of vector difference (VD), speed bias (BIAS), mean vector difference (MVD), standard deviation (SD), and root-mean-square error (RMSE), when compared with the wind field of NCEP reanalysis data and rawinsonde observations.

Yang, Lu; Wang, Zhenhui; Chu, Yanli; Zhao, Hang; Tang, Min

2014-11-01

198

Workshop on Standards for Image Pattern Recognition. Computer Seience & Technology Series.  

ERIC Educational Resources Information Center

Automatic image pattern recognition techniques have been successfully applied to improving productivity and quality in both manufacturing and service applications. Automatic Image Pattern Recognition Algorithms are often developed and tested using unique data bases for each specific application. Quantitative comparison of different approaches and…

Evans, John M. , Ed.; And Others

199

Comparing simultaneously retrieved horizontal and vertical structures of Polar Mesospheric Clouds from Odin/OSIRIS tomography with AIM/CIPS imaging  

NASA Astrophysics Data System (ADS)

The Optical Spectrograph and InfraRed Imager System (OSIRIS) onboard Odin and the Cloud Imager and Particle Size instrument (CIPS) onboard AIM provide complementary scattered light measurements of polar mesospheric clouds. While OSIRIS applies limb geometry and spectral analysis, CIPS applies downward observations and phase function analysis. On a total of twelve days during the northern hemisphere summers 2010 and 2011, Odin was operated in a special mesospheric mode with short limb scans limited to the altitude range of polar mesospheric clouds. For OSIRIS this provides multiple views through a given cloud volume and, thus, a basis for tomographic analysis of the vertical/horizontal cloud structure. Here we present retrieved cloud structures by Odin/OSIRIS and compare these with common volume measurements by AIM/CIPS.; Simultaneously retrieved vertical and horizontal structures of a Polar Mesospheric Cloud layer.

Hultgren, K.

2012-12-01

200

Local binary patterns for stromal area removal in histology images  

NASA Astrophysics Data System (ADS)

Nuclei counting in epithelial cells is an indication for tumor proliferation rate which is useful to rank tumors and select an appropriate treatment schedule for the patient. However, due to the high interand intra- observer variability in nuclei counting, pathologists seek a deterministic proliferation rate estimate. Histology tissue contains epithelial and stromal cells. However, nuclei counting is clinically restricted to epithelial cells because stromal cells do not become cancerous themselves since they remain genetically normal. Counting nuclei existing within the stromal tissue is one of the major causes of the proliferation rate non-deterministic estimation. Digitally removing stromal tissue will eliminate a major cause in pathologist counting variability and bring the clinical pathologist a major step closer toward a deterministic proliferation rate estimation. To that end, we propose a computer aided diagnosis (CAD) system for eliminating stromal cells from digital histology images based on the local binary patterns, entropy measurement, and statistical analysis. We validate our CAD system on a set of fifty Ki-67-stained histology images. Ki-67-stained histology images are among the clinically approved methods for proliferation rate estimation. To test our CAD system, we prove that the manual proliferation rate estimation performed by the expert pathologist does not change before and after stromal removal. Thus, stromal removal does not affect the expert pathologist estimation clinical decision. Hence, the successful elimination of the stromal area highly reduces the false positive nuclei which are the major confusing cause for the less experienced pathologists and thus accounts for the non-determinism in the proliferation rate estimation. Our experimental setting shows statistical insignificance (paired student t-test shows ? = 0.74) in the manual nuclei counting before and after our automated stromal removal. This means that the clinical decision of the expert pathologist is not affected by our CAD system which is what we want to prove. However, the usage of our CAD system substantially account for the reduced inter- and intra- proliferation rate estimation variability and especially for less-experienced pathologists.

Alomari, Raja S.; Ghosh, Subarna; Chaudhary, Vipin; Al-Kadi, Omar

2012-03-01

201

Analysis of spatio-temporal brain imaging patterns by Hidden Markov Models and serial MRI images.  

PubMed

Brain changes due to development and maturation, normal aging, or degenerative disease are continuous, gradual, and variable across individuals. To quantify the individual progression of brain changes, we propose a spatio-temporal methodology based on Hidden Markov Models (HMM), and apply it on four-dimensional structural brain magnetic resonance imaging series of older individuals. First, regional brain features are extracted in order to reduce image dimensionality. This process is guided by the objective of the study or the specific imaging patterns whose progression is of interest, for example, the evaluation of Alzheimer-like patterns of brain change in normal individuals. These regional features are used in conjunction with HMMs, which aim to measure the dynamic association between brain structure changes and progressive stages of disease over time. A bagging framework is used to obtain models with good generalization capability, since in practice the number of serial scans is limited. An application of the proposed methodology was to detect individuals with the risk of developing MCI, and therefore it was tested on modeling the progression of brain atrophy patterns in older adults. With HMM models, the state-transition paths corresponding to longitudinal brain changes were constructed from two completely independent datasets, the Alzheimer Disease Neuroimaging Initiative and the Baltimore Longitudinal Study of Aging. The statistical analysis of HMM-state paths among the normal, progressive MCI, and MCI groups indicates that, HMM-state index 1 is likely to be a predictor of the conversion from cognitively normal to MCI, potentially many years before clinical symptoms become measurable. PMID:24706564

Wang, Ying; Resnick, Susan M; Davatzikos, Christos

2014-09-01

202

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.  

PubMed

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

203

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera  

PubMed Central

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

204

Computerized Classification of Mammary Gland Patterns in Whole Breast Ultrasound Images  

Microsoft Academic Search

Several whole breast ultrasound (US) scanners have recently been developed for breast cancer screening. In ultrasonographic\\u000a screening techniques that utilize scanners, assessment of the mammary gland pattern in US images by a radiologist is required.\\u000a We developed a method of mammary gland analysis to automatically classify whole breast US images into three categories: mottled\\u000a pattern (MP), intermediate pattern (IP), and

Yuji Ikedo; Takako Morita; Daisuke Fukuoka; Takeshi Hara; Hiroshi Fujita; Etsuo Takada; Tokiko Endo

2008-01-01

205

Near-IR Imaging Polarimetry toward a Bright-rimmed Cloud: Magnetic Field in SFO 74  

NASA Astrophysics Data System (ADS)

We have made near-infrared (JHK s) imaging polarimetry of a bright-rimmed cloud (SFO 74). The polarization vector maps clearly show that the magnetic field in the layer just behind the bright rim is running along the rim, quite different from its ambient magnetic field. The direction of the magnetic field just behind the tip rim is almost perpendicular to that of the incident UV radiation, and the magnetic field configuration appears to be symmetric as a whole with respect to the cloud symmetry axis. We estimated the column and number densities in the two regions (just inside and far inside the tip rim) and then derived the magnetic field strength, applying the Chandrasekhar-Fermi method. The estimated magnetic field strength just inside the tip rim, ~90 ?G, is stronger than that far inside, ~30 ?G. This suggests that the magnetic field strength just inside the tip rim is enhanced by the UV-radiation-induced shock. The shock increases the density within the top layer around the tip and thus increases the strength of the magnetic field. The magnetic pressure seems to be comparable to the turbulent one just inside the tip rim, implying a significant contribution of the magnetic field to the total internal pressure. The mass-to-flux ratio was estimated to be close to the critical value just inside the tip rim. We speculate that the flat-topped bright rim of SFO 74 could be formed by the magnetic field effect.

Kusune, Takayoshi; Sugitani, Koji; Miao, Jingqi; Tamura, Motohide; Sato, Yaeko; Kwon, Jungmi; Watanabe, Makoto; Nishiyama, Shogo; Nagayama, Takahiro; Sato, Shuji

2015-01-01

206

An Investigation of the Detectability of Cloud-to-Ground Strokes by the Lightning Imaging Sensor  

NASA Astrophysics Data System (ADS)

Lightning data from the Lightning Imaging Sensor (LIS) is compared with several ground based sensing networks in order to determine the percentage of cloud-to-ground lightning strokes detected from space. Diverging from previous research, stroke level data from the National Lightning Detection Network (NLDN) is compared to LIS groups. A LIS group is considered a match if it lies within 10 ms and 50 km of the NLDN stroke. In addition, VLF/LF sources detected by the Huntsville Alabama Marx Meter Array (HAMMA) and VHF sources detected by the North Alabama Lightning Mapping Array (NALMA) are used to differentiate between lightning events detected or not detected by LIS. The electric field change measurements from HAMMA allow for the analysis of individual electric field waveforms of both intracloud and cloud-to-ground lightning. We investigate if and how properties such as the peak current, height, and stroke type determine whether or not an event is detected by LIS. Additionally, examining the timing and location differences between the ground based sensors and LIS provides a better understanding of which component of the discharge is detected by each.

Franklin, V.; Bitzer, P. M.; Christian, H. J.

2012-12-01

207

Application of Cloude's target decomposition theorem to polarimetric imaging radar data  

NASA Technical Reports Server (NTRS)

In this paper we applied Cloude's decomposition to imaging radar polarimetry. We show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multifrequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a frosted area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. However, the scattering for the forested area is still dominated by scattering from randomly oriented cylinders. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominates in this case.

Vanzyl, Jakob J.

1993-01-01

208

Assessing the performance of the Lightning Imaging Sensor (LIS) using Deep Convective Clouds  

NASA Astrophysics Data System (ADS)

The stability of the LIS instrument is examined during a 13 year period (1998-2010) by examining LIS background radiance observations of Deep Convective Clouds (DCCs) which are identified by their cold IR brightness temperature. Pixels in the LIS background image associated with DCCs are identified and analyzed during July and August of each year in the 13 year period. The resulting LIS DCC radiances are found to be stable throughout the period, varying at most by 0.8% from the 13 year mean July August value of 358.1 W sr- 1 m- 2 ?m- 1. The DCC method in this study provides a good approach for evaluating the stability of the future GOES-R Geostationary Lightning Mapper (GLM).

Buechler, Dennis E.; Koshak, William J.; Christian, Hugh J.; Goodman, Steven J.

2014-01-01

209

Pattern matching and adaptive image segmentation applied to plant reproduction by tissue culture  

NASA Astrophysics Data System (ADS)

This paper shows the results obtained in a system vision applied to plant reproduction by tissue culture using adaptive image segmentation and pattern matching algorithms, this analysis improves the number of tissue obtained and minimize errors, the image features of tissue are considered join to statistical analysis to determine the best match and results. Tests make on potato plants are used to present comparative results with original images processed with adaptive segmentation algorithm and non adaptive algorithms and pattern matching.

Vazquez Rueda, Martin G.; Hahn, Federico

1999-03-01

210

Fast Occlusion and Shadow Detection for High Resolution Remote Sensing Image Combined with LIDAR Point Cloud  

NASA Astrophysics Data System (ADS)

The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM) directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU) is much more powerful than central processing unit (CPU). We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

Hu, X.; Li, X.

2012-08-01

211

* gbb@ipac.caltech.edu; phone 1 626 395-1817; fax 1 626 395-6666; astrocompute.wordpress.com The Application of Cloud Computing to the Creation of Image  

E-print Network

.wordpress.com The Application of Cloud Computing to the Creation of Image Mosaics and Management of Their Provenance G. Bruce). Keywords: Image processing, image mosaics, cloud computing, computational performance, provenance, high, grids, parallel file systems; see [2] for a thorough account of the state of the art. Cloud computing

Deelman, Ewa

212

Remote sensing of cloud, aerosol and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS)  

NASA Technical Reports Server (NTRS)

The Moderate Resolution Imaging Spectrometer (MODIS) is an Earth-viewing sensor being developed as a facility instrument for the Earth Observing System (EOS) to be launched in the late 1990s. MODIS consists of two separate instruments that scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, Sun-synchronous, platform at an altitude of 705 km. Of primary interest for studies of atmospheric physics is the MODIS-N (nadir) instrument which will provide images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resoulutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean and atmosperhic processes. The intent of this lecture is to describe the current status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning radiometer with 32 uniformly spaced channels between 0.410 and 0.875 micrometers, and to describe the physical principles behind the development of MODIS for the remote sensing of atmospheric properties. Primary emphasis will be placed on the main atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles form spectral-reflection and thermal-emission measurements. In addition to cloud and aerosol properties, MODIS-N will be utilized for the determination of the total precipitable water vapor over land and atmospheric stability. The physical principles behind the determination of each of these atmospheric products will be described herein.

King, M. D.

1992-01-01

213

Cloud Games  

NSDL National Science Digital Library

Play these two matching games from the Web Weather for Kids site to pair cloud images with their names/types! Developed by the University Corporation for Atmospheric Research, this site requires Java.

Programs, University C.

2010-01-01

214

Image-based correlation of Laser Scanning point cloud time series for landslide monitoring  

NASA Astrophysics Data System (ADS)

Very high resolution monitoring of landslide kinematics is an important aspect for a physical understanding of the failure mechanisms and for quantifying the associated hazard. In the last decade, the potential of Terrestrial Laser Scanning (TLS) to monitor slow-moving landslides has been largely demonstrated but accurate processing methods are still needed to extract useful information available in point cloud time series. This work presents an approach to measure the 3D deformation and displacement patterns from repeated TLS surveys. The method is based on the simplification of a 3D matching problem in a 2D matching problem by using a 2D statistical normalized cross-correlation function. The computed displacement amplitudes are compared to displacements (1) calculated with the classical approach of Iterative Closest Point and (2) measured from repeated dGPS observations. The performance of the method is tested on a 3 years dataset acquired at the Super-Sauze landslide (South French Alps). The observed landslide displacements are heterogeneous in time and space. Within the landslide, sub-areas presenting different deformation patterns (extension, compression) are detected by a strain analysis. It is demonstrated that pore water pressure changes within the landslide is the main controlling factor of the kinematics.

Travelletti, Julien; Malet, Jean-Philippe; Delacourt, Christophe

2014-10-01

215

Embedding Imperceptible Patterns into Projected Images for Simultaneous Acquisition and Display  

Microsoft Academic Search

We introduce a method to imperceptibly embed arbitrary binary patterns into ordinary color images displayed by unmodified off-the-shelf Digital Light Processing (DLP) projectors. The encoded images are visible only to cameras synchronized with the projectors and exposed for a short interval, while the original images appear only minimally degraded to the human eye. To achieve this goal, we ana- lyze

Daniel Cotting; Martin Naef; Markus H. Gross; Henry Fuchs

2004-01-01

216

The Seasonal and Diurnal Patterns of net Ecosystem CO2 Exchange in a Subtropical Montane Cloud Forest.  

NASA Astrophysics Data System (ADS)

CO2 fluxes were measured by an open/closed path eddy covariance system at a natural regenerated 50-years-old yellow cypress (Chamaecyparis obtusa var. formosana) forest at Chi-Lan Mountain site (CLM site, 24°35'N, 121°25'E, 1650 m elevation), north-eastern Taiwan. CLM site is located at a relative uniform south-eastern-facing valley slope (15°) characterized with year round fog occurrence and diurnal mountain-valley wind and can be classified as subtropical montane cloud forest. Based on measurement from July 2007 to June 2008, seasonal and diurnal patterns of CO2 fluxes were described and patterns under different cloudiness and foggy conditions were presented. Comparing with other cypress forests in temperate region, there is only a weak seasonal pattern of the CO2 fluxes at CLM site. Throughout the year, average incident photosynthetically active radiation in summer was almost the double of that in winter, whereas the difference of mean daytime CO2 fluxes among seasons was much less than the seasonal light difference. During summer when light intensity was higher, mean daytime CO2 fluxes reached -7.5 ?mol/m2/s in July and -8.8 ?mol/m2/s in August. As heavy fog accounted for 64% and 67% of the time in November and February, mean daytime CO2 fluxes dropped to -6.9 and -6.1 ?mol/m2/s respectively. With comparable higher incident radiation intensity (>1000 ?mol/m2/s), the CO2 fluxes were higher in overcast days than in clear days. In July 2007, clear days accounted for 30% of the month, light intensity reached its peak at midday, and however, CO2 fluxes didn't reach its highest value in the meanwhile. Canopy conductance calculated from the Penman-Monteith equation and measured latent heat fluxes both showed a midday depression at clear days, which indicated the regulation of transpiration by plant physiological mechanism. With comparable lower incident radiation intensity (<1000 ?mol/m2/s), the CO2 fluxes were higher in overcast days than in foggy days. The difference suggested that water droplets deposited on leaves might partially block the pathway of the gas exchange through stomata as canopy immersed in the very humid air. However, CO2 fluxes did not cease during foggy periods, as also supported by sap flow and leaf chamber measurements, the morphological characteristics of leaf or/and canopy structure might contribute to the well adaptability of this subtropical montane cloud forest to the humid environment.

Chu, H.; Lai, C.; Wu, C.; Hsia, Y.

2008-12-01

217

Multidimensional Cloud Images Retrieval From Dual-Frequency Millimeter-Wave Radar  

E-print Network

meteorological and climate prediction models [1, 5, 6, 9]. In this work, stratus clouds are studied using dual- frequency radar. Liquid stratus clouds are found in the lower part of the atmosphere and have a profound extinction rate. In this work, we retrieve stratus cloud properties in two dimensions using a dual

Cruz-Pol, Sandra L.

218

Multi-Scale Fractal Analysis of Image Texture and Pattern  

NASA Technical Reports Server (NTRS)

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

1999-01-01

219

Multi-Scale Fractal Analysis of Image Texture and Pattern  

NASA Technical Reports Server (NTRS)

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

1999-01-01

220

Infrared Imaging of the Large Magellanic Cloud Star-forming Region Henize 206  

NASA Astrophysics Data System (ADS)

Henize 206 is a region of star formation in the Large Magellanic Cloud of the approximate scale of the Orion belt and sword. Our Spitzer Space Telescope infrared images and Cerro Tololo Inter-American Observatory (CTIO) optical images show that the region is experiencing very energetic star formation. The radiation from young stars has excited strong polycyclic aromatic hydrocarbon (PAH) emission throughout Henize 206, except on the side of the nebula with the prominent young supernova remnant. As is also seen in early Spitzer observations of M81, star formation rates calculated from H? for Henize 206 may miss the deeply embedded young stars, compared with star formation rates calculated from far infrared emission. For one of the highest surface brightness regions of Henize 206, we obtained snapshot exposures with the Thermal-Region Camera Spectrograph on Gemini South to explore the complex structure. A few percent of the total flux from this brightest region in Henize 206 emanates from infrared peaks of subparsec scale.

Gorjian, V.; Werner, M. W.; Mould, J. R.; Gordon, K. D.; Muzzerole, J.; Morrison, J.; Surace, J. M.; Rebull, L. M.; Hurt, R. L.; Smith, R. C.; Points, S. D.; Aguilera, C.; De Buizer, J. M.; Packham, C.

2004-09-01

221

ABrIL - Advanced Brain Imaging lab.: A cloud based computation environment for cooperative neuroimaging projects.  

PubMed

Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup. This setup and learning process is replicated in every lab, even if a strong collaboration among several groups is going on. In this paper we present a new cloud service model - Brain Imaging Application as a Service (BiAaaS) - and one of its implementation - Advanced Brain Imaging Lab (ABrIL) - in the form of an ubiquitous virtual desktop remote infrastructure that offers a set of neuroimaging computational services in an interactive neuroscientist-friendly graphical user interface (GUI). This remote desktop has been used for several multi-institution cooperative projects with different neuroscience objectives that already achieved important results, such as the contribution to a high impact paper published in the January issue of the Neuroimage journal. The ABrIL system has shown its applicability in several neuroscience projects with a relatively low-cost, promoting truly collaborative actions and speeding up project results and their clinical applicability. PMID:25570014

Neves Tafula, Sergio M; Moreira da Silva, Nadia; Rozanski, Verena E; Silva Cunha, Joao Paulo

2014-08-01

222

Reduction effect of the accumulated number of ghost imaging by circulatory pattern  

NASA Astrophysics Data System (ADS)

In this paper, we present experimental results concerning the reduction effect of the accumulated number of computational ghost imaging (CGI) under different light intensities. By using circulatory illumination pattern, the CGI is possible to directly reduce the accumulated number. In addition, for improvement of the spatial resolution of CGI, the illumination pattern scale is reduced illumination to the object by applying microscopic illumination system. Thereby, the propose method can be achieved high spatial resolution imaging that permitted image of microscopic object. Moreover, the proposed method provided image of the biological cell by fluorescence signal detection. As a result, we demonstrated the potential of CGI for applying measurements field of the cell biology.

Shibuya, Kyuki; Nakae, Katsuhiro; Mizutani, Yasuhiro; Iwata, Tetsuo

2014-10-01

223

Basic research planning in mathematical pattern recognition and image analysis  

NASA Technical Reports Server (NTRS)

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

Bryant, J.; Guseman, L. F., Jr.

1981-01-01

224

Data management in pattern recognition and image processing systems  

NASA Technical Reports Server (NTRS)

Data management considerations are important to any system which handles large volumes of data or where the manipulation of data is technically sophisticated. A particular problem is the introduction of image-formatted files into the mainstream of data processing application. This report describes a comprehensive system for the manipulation of image, tabular, and graphical data sets which involve conversions between the various data types. A key characteristic is the use of image processing technology to accomplish data management tasks. Because of this, the term 'image-based information system' has been adopted.

Zobrist, A. L.; Bryant, N. A.

1976-01-01

225

Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis  

NASA Technical Reports Server (NTRS)

The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

Guseman, L. F., Jr.

1983-01-01

226

Image-level and group-level models for Drosophila gene expression pattern annotation  

PubMed Central

Background Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison. Results We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach. Conclusion In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation. PMID:24299119

2013-01-01

227

A PATTERN MATCHING APPROACH TO IMAGE COMPRESSION Mikhail J. Atallah and Wojciech Szpankowski  

E-print Network

­ proximate pattern matching, that we name Pattern Match­ ing Image Compression (PMIC). We give new, efficient ratios experimentally obtained. The main idea is a lossy extension of the Lempel­ Ziv data compression probabilistic assumption con­ cerning a sequence, the compression ratio is asymptot­ ically equal to the so

Szpankowski, Wojciech

228

Speckle reduction in THz imaging systems with multiple phase patterns  

NASA Astrophysics Data System (ADS)

THz technology makes possible imaging of phenomena, inaccessible to both visible and infrared radiation, but the imaging is still in its early stages of development. This paper draws attention to the aspects of speckle reduction to improve the image quality. Because all existing THz sources are coherent - speckle is an ultimate limiting factor of the free-space imaging techniques. Speckle arises when coherent light scattered from a rough surface is detected by an intensity detector with a finite aperture, hiding the image information. This problem is of special importance for THz imaging, because surface roughness is closer to the object dimension as in optical imaging. The reduction of speckle is highly desirable and we propose here a Hadamard matrix solution. Hadamard diffuser for mm-wave frequency range have been designed, built and tested. We report 50% speckle reduction measurements using a free-space vector network analyzer over the full W-band (75-110 GHz). The advantage of the mm-wave Hadamard technology over optical: the diffuser doesn't have to be moved (vibrated) any more to accomplish the technology of speckle reduction. Temporal optical effect is substituted here by spatial quasi-optical: Hadamard coding in each scan pixel. Second method delivers realistic system parameters for the speckle reduction with polychromatic light for aviation security.

Jaeger, Irina; Stiens, Johan; Koers, Gaetan; Poesen, Gert; Vounckx, Roger

2006-04-01

229

New Class Of Features For Pattern Recognition And Image Analysis  

NASA Astrophysics Data System (ADS)

A class of features, called "edge features," has been developed and applied to several problems of practical interest in image processing. These features are derived from a vector-valued function of the image called the "edge spectrum-" The edge spectrum at coordinate (x.,y) of the image describes the distribution of edge directions near (x,y). Several applications of edge features are discussed. One is considered in some detail. This application is to identify friendly aircraft descending for landing on an aircraft carrier. Identification is achieved by measuring wingspan - a good discriminant between the A6, A7, E2C and F.14. aircraft. For this purpose an edge feature was designed for locating the wing tips in the image. Wingspan was converted to physical dimension using range information and the known parameters of the optical system.

Choate, W. Clay

1985-07-01

230

Patterned Resonance Plasmonic Microarrays for High-Performance SPR Imaging  

PubMed Central

We report a novel optical platform based on SPR generation and confinement inside a defined 3-dimensional microwell geometry that leads to background resonance-free SPR images. The array shows an exceptionally high signal-to-noise ratio (S/N>80) for imaging analysis and subnanometric thickness resolution. An angular sensitivity of 1 degree/0.01 RIU has been achieved and the signal to background ratio (S/B) improves to 20, one order of magnitude higher than best literature results. The design proves effective for probing supported lipid membrane arrays in real time with a thickness resolution of 0.24 nm and allows for imaging analysis of microfluidic circuits where resonant spots are separated by only one pixel (~ 7 ?m). The high image quality and unique chip geometry open up new avenues for array screening and biomicrofluidics using SPRi detection. PMID:21417424

Abbas, Abdennour; Linman, Matthew J.; Cheng, Quan

2011-01-01

231

Multi-Scale Fractal Analysis of Image Texture and Pattern  

NASA Technical Reports Server (NTRS)

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely scale-independent. Self-similarity is a property of curves or surfaces where each part is indistinguishable from the whole. The fractal dimension D of remote sensing data yields quantitative insight on the spatial complexity and information content contained within these data. Analyses of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed(l0 to 80 meters). The forested scene behaves as one would expect-larger pixel sizes decrease the complexity of the image as individual clumps of trees are averaged into larger blocks. The increased complexity of the agricultural image with increasing pixel size results from the loss of homogeneous groups of pixels in the large fields to mixed pixels composed of varying combinations of NDVI values that correspond to roads and vegetation. The same process occur's in the urban image to some extent, but the lack of large, homogeneous areas in the high resolution NDVI image means the initially high D value is maintained as pixel size increases. The slope of the fractal dimension-resolution relationship provides indications of how image classification or feature identification will be affected by changes in sensor resolution.

Emerson, Charles W.; Quattrochi, Dale A.; Luvall, Jeffrey C.

1997-01-01

232

Application of Cloude's target decomposition theorem to polarimetric imaging radar data  

NASA Technical Reports Server (NTRS)

We apply Cloude's decomposition to imaging radar polarimetry. We derive the general expressions for the eigenvalues and eigenvectors for the case of terrain with reflection symmetry, and show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multi-frequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a forested area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. The scattering for the forested area is still dominated by scattering from randomly oriented cylinders, however. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominate in this case.

Vanzyl, Jakob J.

1993-01-01

233

Assessing geoaccuracy of structure from motion point clouds from long-range image collections  

NASA Astrophysics Data System (ADS)

Automatically extracted and accurate scene structure generated from airborne platforms is a goal of many applications in the photogrammetry, remote sensing, and computer vision fields. This structure has traditionally been extracted automatically through the structure-from-motion (SfM) workflows. Although this process is very powerful, the analysis of error in accuracy can prove difficult. Our work presents a method of analyzing the georegistration error from SfM derived point clouds that have been transformed to a fixed Earth-based coordinate system. The error analysis is performed using synthetic airborne imagery which provides absolute truth for the ray-surface intersection of every pixel in every image. Three methods of georegistration are assessed; (1) using global positioning system (GPS) camera centers, (2) using pose information directly from on-board navigational instrumentation, and (3) using a recently developed method that utilizes the forward projection function and SfM-derived camera pose estimates. It was found that the georegistration derived from GPS camera centers and the direct use of pose information from on-board navigational instruments is very sensitive to noise from both the SfM process and instrumentation. The georegistration transform computed using the forward projection function and the derived pose estimates prove to be far more robust to these errors.

Nilosek, David; Walvoord, Derek J.; Salvaggio, Carl

2014-11-01

234

Genetic Algorithm-Based Relevance Feedback for Image Retrieval Using Local Similarity Patterns.  

ERIC Educational Resources Information Center

Proposes local similarity pattern (LSP) as a new method for computing digital image similarity. Topics include optimizing similarity computation based on genetic algorithm; relevance feedback; and an evaluation of LSP on five databases that showed an increase in retrieval precision over other methods for computing image similarity. (Author/LRW)

Stejic, Zoran; Takama, Yasufumi; Hirota, Kaoru

2003-01-01

235

Z .Pattern Recognition Letters 18 1997 12531259 Image compression and encryption using tree structures 1  

E-print Network

a high compression ratio. With a mobile sys- tem, compression and encryption must be handled by limited .� is efficient in terms of time and space ; � performs image compression, and � performs dataZ .Pattern Recognition Letters 18 1997 1253­1259 Image compression and encryption using tree

Cheng, Howard

236

Improving Cloud Detection in Satellite Images of Coral Reef Environments Using Space Shuttle Photographs and High-Definition Television  

NASA Technical Reports Server (NTRS)

Coral reefs worldwide are suffering from severe and rapid degradation (Bryant et A, 1998; Hoegh-Guldberg, 1999). Quick, consistent, large-scale assessment is required to assess and monitor their status (e.g., USDOC/NOAA NESDIS et al., 1999). On-going systematic collection of high resolution digital satellite data will exhaustively complement the relatively small number of SPOT, Landsat 4-5, and IRS scenes acquired for coral reefs the last 20 years. The workhorse for current image acquisition is the Landsat 7 ETM+ Long Term Acquisition Plan (Gasch et al. 2000). Coral reefs are encountered in tropical areas and cloud contamination in satellite images is frequently a problem (Benner and Curry 1998), despite new automated techniques of cloud cover avoidance (Gasch and Campana 2000). Fusion of multidate acquisitions is a classical solution to solve the cloud problems. Though elegant, this solution is costly since multiple images must be purchased for one location; the cost may be prohibitive for institutions in developing countries. There are other difficulties associated with fusing multidate images as well. For example, water quality or surface state can significantly change through time in coral reef areas making the bathymetric processing of a mosaiced image strenuous. Therefore, another strategy must be selected to detect clouds and improve coral reefs mapping. Other supplemental data could be helpful and cost-effective for distinguishing clouds and generating the best possible reef maps in the shortest amount of time. Photographs taken from the 1960s to the present from the Space Shuttle and other human-occupied spacecraft are one under-used source of alternative multitemporal data (Lulla et al. 1996). Nearly 400,000 photographs have been acquired during this period, an estimated 28,000 of these taken to date are of potential value for reef remote sensing (Robinson et al. 2000a). The photographic images can be digitized into three bands (red, green and blue) and processed for various applications (e.g., Benner and Curry 1998, Nedeltchev 1999, Glasser and Lulla 2000, Robinson et al. 2000c, Webb et al, in press).

Andrefeouet, Serge; Robinson, Julie

2000-01-01

237

CERES CLoud Effects  

NSDL National Science Digital Library

This computer-generated animation depicts the Clouds and the Earth's Radiant Energy System (CERES) instrument in operation. CERES measures the energy at the top of the atmosphere and estimates energy levels in the atmosphere and at the Earth's surface. Using information from very high resolution cloud-imaging instruments on the same spacecraft, CERES also will determine cloud properties, including cloud amount, altitude, thickness, and the size of the cloud particles.

1997-06-06

238

Measurement of cervical multifidus contraction pattern with ultrasound imaging  

Microsoft Academic Search

Deep muscle training has become the focus of research and exercise for patients with chronic neck pain. The objective of this in vivo study was to establish a non-invasive assessment tool for the activation of deep cervical muscles. The pattern of the change in the thickness of the cervical multifidus is described with a mathematical equation and used to compare

Jo-Ping Lee; Chung-Li Wang; Yio-Wha Shau; Shwu-Fen Wang

2009-01-01

239

Fine Pattern Replication Using ETS-1 Three-Aspherical Mirror Imaging System  

NASA Astrophysics Data System (ADS)

The engineering test stand ETS-1 three-aspherical-mirror imaging system has been developed. In the fine pattern replication using a Cr mask in static exposure, the resist pattern is replicated in the exposure area of 10 mm× 2 mm with the line and space pattern width of 60 nm, the isolated line pattern width of 40 nm, and the hole pattern width of 150 nm. For the scanning exposure, the resist pattern is replicated with the line and space pattern width of 60 nm in an exposure area of 10 mm× 10 mm. We have also constructed a multilayer reflectivity measurement system at the BL10 beamline of the NewSUBARU facility. The full field of ULE6025 mask reflectivity can be measured. Furthermore, the low-outgassing chemically amplified resist EUV010 has been developed based on KrF chemically amplified resist.

Watanabe, Takeo; Kinoshita, Hiroo; Hamamoto, Kazuhiro; Hosoya, Morio; Shoki, Tsutomu; Hada, Hideo; Komano, Hiroshi; Okazaki, Shinji

2002-06-01

240

Transient Response and Fixed Pattern Noise in Logarithmic CMOS Image Sensors  

Microsoft Academic Search

Logarithmic CMOS image sensors are appealing for their high-contrast and high-speed response but they require postprocessing to achieve high-quality images. Previously published work has explained the fixed pattern noise (FPN) in these image sensors using a steady-state analysis. This paper explains how the transient response of the readout circuit may also contribute to FPN. Thus, the performance of these CMOS

Dileepan Joseph; Steve Collins

2007-01-01

241

Automatic Assessment and Reduction of Noise using Edge Pattern Analysis in Non-Linear Image Enhancement  

NASA Technical Reports Server (NTRS)

Noise is the primary visibility limit in the process of non-linear image enhancement, and is no longer a statistically stable additive noise in the post-enhancement image. Therefore novel approaches are needed to both assess and reduce spatially variable noise at this stage in overall image processing. Here we will examine the use of edge pattern analysis both for automatic assessment of spatially variable noise and as a foundation for new noise reduction methods.

Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.; Hines, Glenn D.

2004-01-01

242

Integration of Color and Local Derivative Pattern Features for Content-Based Image Indexing and Retrieval  

NASA Astrophysics Data System (ADS)

This paper presents two new feature descriptors for content based image retrieval (CBIR) application. The proposed two descriptors are named as color local derivative patterns (CLDP) and inter color local derivative pattern (ICLDP). In order to reduce the computational complexity the uniform patterns are applied to both CLDP and ICLDP. Further, uniform CLDP (CLDPu2) and uniform ICLDP (ICLDPu2) are generated respectively. The proposed descriptors are able to exploit individual (R, G and B) spectral channel information and co-relating pair (RG, GB, BR, etc.) of spectral channel information. The retrieval performances of the proposed descriptors (CLDP and ICLDP) are tested by conducting two experiments on Corel-5000 and Corel-10000 benchmark databases. The results after investigation show a significant improvement in terms of precision, average retrieval precision (ARP), recall and average retrieval rate (ARR) as compared to local binary patterns (LBP), local derivative patterns (LDP) and other state-of-the-art techniques for image retrieval.

Vipparthi, Santosh Kumar; Nagar, Shyam Krishna

2014-09-01

243

Remote sensing of cloud droplet size distributions in DC3 with the UMBC-LACO Rainbow Polarimetric Imager (RPI)  

NASA Astrophysics Data System (ADS)

The UMBC Rainbow Polarimetric Imager is a small form factor VIS imaging polarimeter suitable for use on a number of platforms. An optical system based on a Phillips prism with three Bayer filter color detectors, each detecting a separate polarization state, allows simultaneous detection of polarization and spectral information. A Mueller matrix-like calibration scheme corrects for polarization artifacts in the optical train and allows retrieval of the polarization state of incoming light to better than 0.5%. Coupled with wide field of view optics (~90°), RPI can capture images of cloudbows over a wide range of aircraft headings and solar zenith angles for retrieval of cloud droplet size distribution (DSD) parameters. In May-June 2012, RPI was flown in a nadir port on the NASA DC-8 during the DC3 field campaign. We will show examples of cloudbow DSD parameter retrievals from the campaign to demonstrate the efficacy of such a system to terrestrial atmospheric remote sensing. RPI image from DC3 06/15/2012 flight. Left panel is raw image from the RPI 90° camera. Middle panel is Stokes 'q' parameter retrieved from full three camera dataset. Right panel is a horizontal cut in 'q' through the glory. Both middle and right panels clearly show cloudbow features which can be fit to infer cloud DSD parameters.

Buczkowski, S.; Martins, J.; Fernandez-Borda, R.; Cieslak, D.; Hall, J.

2013-12-01

244

An adaptive OPD and dislocation prediction used characteristic of interference pattern for interference hyperspectral image compression  

NASA Astrophysics Data System (ADS)

According to the imaging principle and characteristic of LASIS (Large Aperture Static Interference Imaging Spectrometer), we discovered that the 3D (three dimensional) image sequences formed by different interference pattern frames, which were formed in the imaging process of LASIS Interference hyperspectral image, had much stronger correlation than the original interference hyperspectral image sequences, either in 2D (two dimensional) spatial domain or in the spectral domain. We put this characteristic into image compression and proposed an adaptive OPD (optical path difference) and dislocation prediction algorithm for interference hyperspectral image compression. Compared the new algorithm proposed in this paper with Dual-Direction Prediction [1] proposed in 2009, lots of experimental results showed that the prediction error entropy of the new algorithm was much smaller. In the prediction step of lifting wavelet transform, this characteristic would also reduce the entropy of coefficients in high frequency significantly, which would be more advantageous for quantification coding [2].

Wen, Jia; Ma, Caiwen; Shui, Penglang

2011-09-01

245

Cloud Screening and Quality Control Algorithm for Star Photometer Data: Assessment with Lidar Measurements and with All-sky Images  

NASA Technical Reports Server (NTRS)

This paper presents the development and set up of a cloud screening and data quality control algorithm for a star photometer based on CCD camera as detector. These algorithms are necessary for passive remote sensing techniques to retrieve the columnar aerosol optical depth, delta Ae(lambda), and precipitable water vapor content, W, at nighttime. This cloud screening procedure consists of calculating moving averages of delta Ae() and W under different time-windows combined with a procedure for detecting outliers. Additionally, to avoid undesirable Ae(lambda) and W fluctuations caused by the atmospheric turbulence, the data are averaged on 30 min. The algorithm is applied to the star photometer deployed in the city of Granada (37.16 N, 3.60 W, 680 ma.s.l.; South-East of Spain) for the measurements acquired between March 2007 and September 2009. The algorithm is evaluated with correlative measurements registered by a lidar system and also with all-sky images obtained at the sunset and sunrise of the previous and following days. Promising results are obtained detecting cloud-affected data. Additionally, the cloud screening algorithm has been evaluated under different aerosol conditions including Saharan dust intrusion, biomass burning and pollution events.

Ramirez, Daniel Perez; Lyamani, H.; Olmo, F. J.; Whiteman, D. N.; Navas-Guzman, F.; Alados-Arboledas, L.

2012-01-01

246

Identification of psychopathic individuals using pattern classification of MRI images  

Microsoft Academic Search

Background: Psychopathy is a disorder of personality characterized by severe impairments of social conduct, emotional experience, and interpersonal behavior. Psychopaths consistently violate social norms and bring considerable financial, emotional, or physical harm to others and to society as a whole. Recent developments in analysis methods of magnetic resonance imaging (MRI), such as voxel-based-morphometry (VBM), have become major tools to understand

João R. Sato; Ricardo de Oliveira-Souza; Carlos E. Thomaz; Rodrigo Basílio; Ivanei E. Bramati; Edson Amaro Jr; Fernanda Tovar-Moll; Robert D. Hare; Jorge Moll

2011-01-01

247

Multispectral cloud-clearing using IASI sounding and collocated AVHRR imager measurements  

NASA Astrophysics Data System (ADS)

E. S. Maddy2, T. S. King2, H. Sun2, W. W. Wolf1, C. D. Barnet1, A. Heidinger1,Z. Cheng2, and A. Gambacorta2 1NOAA/NESDIS/Center for Satellite Applications and Research, Camp Springs, Maryland, USA 2Dell, Fairfax, Virginia, USA There are several approaches for handling the effect of clouds in the IR, the most common of which include: avoiding the clouds by screening for clear-sky footprints; directly modeling the radiative effect of the clouds using sophisticated radiative transfer and cloud microphysical models; and, estimating the clear-sky portion of an IR scene by using a number of adjacent and variably cloudy footprints coupled with an estimate of the clear-sky radiance from a forecast model or collocated satellite instrument less likely to be affected by clouds. The last approach, termed cloud-clearing, is currently used at NOAA/NESDIS for operational IASI processing. NOAA currently operationally processes 100% of IASI data from calibrated and apodized L1C spectral measurements to geophysical L2 products and distributes these products to the NOAA/Comprehensive Large Array-data Stewardship System (CLASS) (available at http://class.ngdc.noaa.gov). The current algorithm used to produce the L2 products from IASI is largely based on the AIRS science team (AST) algorithm including the fast Radiative Transfer Algorithm (RTA), fast eigenvector regression, as well as cloud-clearing and physical retrieval methodologies which rely on microwave measurements from collocated AMSU to handle the effects of clouds in the IR. We will describe future upgrades to the operational cloud-clearing algorithm being used for IASI processing within NOAA/NESDIS. Specifically, our new cloud-clearing algorithm leverages off of the MetOp-A AVHRR Clouds from AVHRR (CLAVR-x) cloud mask to provide high quality, high spatial resolution InfraRed (IR) window clear-sky scene radiance estimates required for cloud-clearing inputs and quality assurance. The direct use of AVHRR clear-sky measurements decreases limitations of the current algorithm to provide high quality clear-sky radiance estimates throughout the atmospheric column, and especially near the surface to a high degree of accuracy. In turn, this enables the IASI sounder to provide high quality and high vertical and spatial resolution soundings temperature and trace gases for the study of weather and climate processes.

Maddy, E. S.; King, T. S.; Sun, H.; Wolf, W.; Barnet, C.; Heidinger, A. K.; Cheng, Z.; Gambacorta, A.

2010-12-01

248

Spatial uncertainty modeling of fuzzy information in images for pattern classification.  

PubMed

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction. PMID:25157744

Pham, Tuan D

2014-01-01

249

Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification  

PubMed Central

The modeling of the spatial distribution of image properties is important for many pattern recognition problems in science and engineering. Mathematical methods are needed to quantify the variability of this spatial distribution based on which a decision of classification can be made in an optimal sense. However, image properties are often subject to uncertainty due to both incomplete and imprecise information. This paper presents an integrated approach for estimating the spatial uncertainty of vagueness in images using the theory of geostatistics and the calculus of probability measures of fuzzy events. Such a model for the quantification of spatial uncertainty is utilized as a new image feature extraction method, based on which classifiers can be trained to perform the task of pattern recognition. Applications of the proposed algorithm to the classification of various types of image data suggest the usefulness of the proposed uncertainty modeling technique for texture feature extraction. PMID:25157744

Pham, Tuan D.

2014-01-01

250

Saturn’s Zonal Winds at Cloud Level between 2004-2013 from Cassini ISS Images  

NASA Astrophysics Data System (ADS)

We examine images of Saturn returned by Cassini orbiter’s Imaging Science Subsystem (ISS) camera between 2004 to 2013 to analyze the temporal evolution of the zonal mean wind speed as a function of latitude. Our study primarily examines the images captured in the 752-nm continuum band using the CB2 filter. Images captured using the CB2 filter sense the upper troposphere of Saturn between 350 mbar and 500 mbar (Pérez-Hoyos and Sánchez-Lavega, 2006; Sánchez-Lavega et al, 2006; García-Melendo et al, 2009). We measure the wind speed using a two-dimensional Correlation Imaging Velocimetry (CIV) technique. The wind vectors are computed using pairs of images separated in time by up to two planetary rotations, and binned in latitude to determine the zonal mean wind profile, which typically covers a limited range of latitude. To achieve pole-to-pole coverage, we systematically merge all the wind measurements during each of the calendar years in order to compile a yearly, near-global record of Saturn's zonal wind structure. Using our wind measurements, we analyze the temporal evolution of the zonal wind. We specifically focus on changes in the wind profile after the 2009 equinox; we predict that changes in the insolation pattern caused by the shifting ring shadows affect the horizontal temperature gradient, and change the zonal mean wind through the thermal wind relationship. Furthermore, we also extend the zonal wind analysis by Sayanagi et al (2013), who detected changes in the zonal wind related to the Great Storm of 2010-2011, to study the subsequent evolution of the region affected by the storm. We compare our results with previously published zonal wind profiles obtained from Voyager 1 and 2 (Sánchez-Lavega et al, 2000) and Cassini (García-Melendo et al, 2011). Out study is supported by the Cassini Project, and our investigation is funded by NASA Outer Planets Research Program grant NNX12AR38G and NSF Astronomy and Astrophysics grant 1212216 to KMS.

Blalock, John J.; Sayanagi, Kunio M.; Dyudina, Ulyana A.; Ewald, Shawn P.; Ingersoll , Andrew P.

2014-11-01

251

Local binary pattern texture-based classification of solid masses in ultrasound breast images  

NASA Astrophysics Data System (ADS)

Breast cancer is one of the leading causes of cancer mortality among women. Ultrasound examination can be used to assess breast masses, complementarily to mammography. Ultrasound images reveal tissue information in its echoic patterns. Therefore, pattern recognition techniques can facilitate classification of lesions and thereby reduce the number of unnecessary biopsies. Our hypothesis was that image texture features on the boundary of a lesion and its vicinity can be used to classify masses. We have used intensity-independent and rotation-invariant texture features, known as Local Binary Patterns (LBP). The classifier selected was K-nearest neighbors. Our breast ultrasound image database consisted of 100 patient images (50 benign and 50 malignant cases). The determination of whether the mass was benign or malignant was done through biopsy and pathology assessment. The training set consisted of sixty images, randomly chosen from the database of 100 patients. The testing set consisted of forty images to be classified. The results with a multi-fold cross validation of 100 iterations produced a robust evaluation. The highest performance was observed for feature LBP with 24 symmetrically distributed neighbors over a circle of radius 3 (LBP24,3) with an accuracy rate of 81.0%. We also investigated an approach with a score of malignancy assigned to the images in the test set. This approach provided an ROC curve with Az of 0.803. The analysis of texture features over the boundary of solid masses showed promise for malignancy classification in ultrasound breast images.

Matsumoto, Monica M. S.; Sehgal, Chandra M.; Udupa, Jayaram K.

2012-03-01

252

Local affine image matching and synthesis based on structural patterns.  

PubMed

A general purpose block-to-block affine transformation estimator is described. The estimator is based on Fourier slice analysis and Fourier spectral alignment. It shows encouraging performance in terms of both speed and accuracy compared to existing methods. The key elements of its success are attributed to the ability to: 1) locate an arbitrary number of affine invariant points in the spectrum that latch onto significant structural features; 2) match the estimated invariant points with the target spectrum by the slicewise phase-correlation; and 3) use affine invariant points to directly compute all linear parameters of the full affine transform by spectral alignment. Experimental results using a wide range of textures are presented. Potential applications include affine invariant image segmentation, registration, affine symmetric image coding, and motion analysis. PMID:20236890

Park, Heechan; Martin, Graham R; Bhalerao, Abhir

2010-08-01

253

Computer-aided diagnosis of splenic enlargement using wave pattern of spleen in abdominal CT images  

NASA Astrophysics Data System (ADS)

It is known that the spleen accompanied by liver cirrhosis is hypertrophied or enlarged. We have examined a wave pattern at the left boundary of spleen on the abdominal CT images having liver cirrhosis, and found that they are different from those on the images having a normal liver. It is noticed that the abdominal CT images of patient with liver cirrhosis shows strong bending in the wave pattern. In the case of normal liver, the images may also have a wave pattern, but its bends are not strong. Therefore, the total waving area of the spleen with liver cirrhosis is found to be greater than that of the spleen with a normal liver. Moreover, we found that the waves of the spleen from the image with liver cirrhosis have the higher degree of circularity compared to the normal liver case. Based on the two observations above, we propose an automatic method to diagnose splenic enlargement by using the wave pattern of the spleen in abdominal CT images. The proposed automatic method improves the diagnostic performance compared with the conventional process based on the size of spleen.

Seong, Won; Cho, June-Sik; Noh, Seung-Moo; Park, Jong Won

2006-03-01

254

Cloud Computing for radiologists.  

PubMed

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future. PMID:23599560

Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

2012-07-01

255

Cloud Computing for radiologists  

PubMed Central

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future. PMID:23599560

Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

2012-01-01

256

Bayer patterned high dynamic range image reconstruction using adaptive weighting function  

NASA Astrophysics Data System (ADS)

It is not easy to acquire a desired high dynamic range (HDR) image directly from a camera due to the limited dynamic range of most image sensors. Therefore, generally, a post-process called HDR image reconstruction is used, which reconstructs an HDR image from a set of differently exposed images to overcome the limited dynamic range. However, conventional HDR image reconstruction methods suffer from noise factors and ghost artifacts. This is due to the fact that the input images taken with a short exposure time contain much noise in the dark regions, which contributes to increased noise in the corresponding dark regions of the reconstructed HDR image. Furthermore, since input images are acquired at different times, the images contain different motion information, which results in ghost artifacts. In this paper, we propose an HDR image reconstruction method which reduces the impact of the noise factors and prevents ghost artifacts. To reduce the influence of the noise factors, the weighting function, which determines the contribution of a certain input image to the reconstructed HDR image, is designed to adapt to the exposure time and local motions. Furthermore, the weighting function is designed to exclude ghosting regions by considering the differences of the luminance and the chrominance values between several input images. Unlike conventional methods, which generally work on a color image processed by the image processing module (IPM), the proposed method works directly on the Bayer raw image. This allows for a linear camera response function and also improves the efficiency in hardware implementation. Experimental results show that the proposed method can reconstruct high-quality Bayer patterned HDR images while being robust against ghost artifacts and noise factors.

Kang, Hee; Lee, Suk Ho; Song, Ki Sun; Kang, Moon Gi

2014-12-01

257

Cardiac electrophysiological activation pattern estimation from images using a patient-specific database of synthetic image sequences.  

PubMed

While abnormal patterns of cardiac electrophysiological activation are at the origin of important cardiovascular diseases (e.g., arrhythmia, asynchrony), the only clinically available method to observe detailed left ventricular endocardial surface activation pattern is through invasive catheter mapping. However, this electrophysiological activation controls the onset of the mechanical contraction; therefore, important information about the electrophysiology could be deduced from the detailed observation of the resulting motion patterns. In this paper, we present the study of this inverse cardiac electrokinematic relationship. The objective is to predict the activation pattern knowing the cardiac motion from the analysis of cardiac image sequences. To achieve this, we propose to create a rich patient-specific database of synthetic time series of the cardiac images using simulations of a personalized cardiac electromechanical model, in order to study this complex relationship between electrical activity and kinematic patterns in the context of this specific patient. We use this database to train a machine-learning algorithm which estimates the depolarization times of each cardiac segment from global and regional kinematic descriptors based on displacements or strains and their derivatives. Finally, we use this learning to estimate the patient’s electrical activation times using the acquired clinical images. Experiments on the inverse electrokinematic learning are demonstrated on synthetic sequences and are evaluated on clinical data with promising results. The error calculated between our prediction and the invasive intracardiac mapping ground truth is relatively small (around 10 ms for ischemic patients and 20 ms for nonischemic patient). This approach suggests the possibility of noninvasive electrophysiological pattern estimation using cardiac motion imaging. PMID:24058008

Prakosa, Adityo; Sermesant, Maxime; Allain, Pascal; Villain, Nicolas; Rinaldi, C Aldo; Rhode, Kawal; Razavi, Reza; Delingette, Hervé; Ayache, Nicholas

2014-02-01

258

Combined Geometric/radiometric Point Cloud Matching for Shear Analysis  

NASA Astrophysics Data System (ADS)

In the recent past, dense image matching methods such as Semi-Global Matching (SGM) became popular for many applications. The SGM approach has been adapted to and implemented for Leica ADS line-scanner data by North West Geomatics (North West) in co-operation with Leica Geosystems; it is used in North West's production workflow. One of the advantages of ADS imagery is the calibrated color information (RGB and near infrared), extending SGM-derived point clouds to dense "image point clouds" or, more general, information clouds (info clouds). With the goal of automating the quality control of ADS data, info clouds are utilized for Shear Analysis: Three-dimensional offsets of adjacent ADS image strips are determined from a pattern of info cloud pairs in strip overlaps by point cloud matching. The presented approach integrates geometry (height) and radiometry (intensity) information; matching is based on local point-to-plane distances for all points in a given cloud. The offset is derived in a least squares adjustment by applying it to each individual distance computation equation. Using intensities in addition to heights greatly benefits the offset computation, because intensity gradients tend to occur more frequently than height gradients. They can provide or complement the required information for the derivation of planimetric offset components. The paper details the combined geometric/radiometric point cloud matching approach and verifies the results against manual measurements.

Gehrke, S.

2012-07-01

259

On Classifying Disease-Induced Patterns in the Brain Using Diffusion Tensor Images  

Microsoft Academic Search

\\u000a Diffusion tensor imaging (DTI) provides rich information about brain tissue structure especially in the white matter, which\\u000a is known to be affected in several diseases like schizophrenia. Identifying patterns of brain changes induced by pathology\\u000a is therefore crucial to clinical studies. However, the high dimensionality and complex structure of DTI make it difficult\\u000a to apply conventional linear statistical and pattern

Peng Wang; Ragini Verma

2008-01-01

260

A modified technique for fabricating a mirror image wax pattern for an auricular prosthesis.  

PubMed

This article describes a technique for fabricating a wax pattern for an auricular prosthesis by tracing the shape of a sliced cast of the contralateral ear at an interval of 1-mm and transferring the shape of each 1-mm slice to a similar dimension modeling wax sheet. In this way, slices of modeling wax are obtained, which can be reversed and placed over the previous slice to produce a mirror image wax pattern of the contralateral ear. PMID:25277032

Gajdhar, Shaiq; Gajdhar, Sajda Khan; Salakalakonda, Srikanth Reddy; Vasthare, Abubakkar

2015-01-01

261

Local spatial binary pattern: a new feature descriptor for content-based image retrieval  

NASA Astrophysics Data System (ADS)

In this paper, we propose a novel image retrieval algorithm using local spatial binary patterns (LSBP) for contentbased image retrieval. The traditional local binary pattern (LBP) encodes the relationship between the referenced pixel and its surrounding neighbors by calculating gray-level difference, but LBP lacks the spatial distribution information of texture direction. The proposed method encodes spatial relationship of the referenced pixel and its neighbors, based on the gray-level variation patterns of the horizontal, vertical and oblique directions. Additionally, variation between center pixel and its surrounding neighbors is calculated to reflect the magnitude information of the whole image. We compare our method with LBP, uniform LBP (ULBP), completed LBP (CLBP), local ternary pattern (LTP) and local tetra patterns (LTrP) based on three benchmark image databases including, Brodatz texture database(DB1), Corel database(DB2), and MIT VisTex database(DB3). Experiment analysis shows that the proposed method improves the retrieval results from 70.49%/41.30% to 73.26%/46.26% in terms of average precision/average recall on database DB2, from 79.02% to 85.92% and 82.14% to 90.88% in terms of average precision on databases DB1 and DB3, respectively, as compared with the traditional LBP.

Xia, Yu; Wan, Shouhong; Yue, Lihua

2014-01-01

262

Model-based classification methods of global patterns in dermoscopic images.  

PubMed

In this paper different model-based methods of classification of global patterns in dermoscopic images are proposed. Global patterns identification is included in the pattern analysis framework, the melanoma diagnosis method most used among dermatologists. The modeling is performed in two senses: first a dermoscopic image is modeled by a finite symmetric conditional Markov model applied to L?a?b? color space and the estimated parameters of this model are treated as features. In turn, the distribution of these features are supposed that follow different models along a lesion: a Gaussian model, a Gaussian mixture model, and a bag-of-features histogram model. For each case, the classification is carried out by an image retrieval approach with different distance metrics. The main objective is to classify a whole pigmented lesion into three possible patterns: globular, homogeneous, and reticular. An extensive evaluation of the performance of each method has been carried out on an image database extracted from a public Atlas of Dermoscopy. The best classification success rate is achieved by the Gaussian mixture model-based method with a 78.44% success rate in average. In a further evaluation the multicomponent pattern is analyzed obtaining a 72.91% success rate. PMID:24770918

Sáez, Aurora; Serrano, Carmen; Acha, Begoña

2014-05-01

263

Attempt of UAV oblique images and MLS point clouds for 4D modelling of roadside pole-like objects  

NASA Astrophysics Data System (ADS)

The state-of-the-art remote sensing technologies, namely Unmanned Aerial Vehicle (UAV) based oblique imaging and Mobile Laser Scanning (MLS) show great potential for spatial information acquisition. This study investigated the combination of the two data sources for 4D modelling of roadside pole-like objects. The data for the analysis were collected by the Microdrone md4-200 UAV imaging system and the Sensei MLS system developed by the Finnish Geodetic Institute. Pole extraction, 3D structural parameter derivation and texture segmentation were deployed on the oblique images and point clouds, and their results were fused to yield the 4D models for one example of pole-like objects, namely lighting poles. The combination techniques proved promising.

Lin, Yi; West, Geoff

2014-11-01

264

Searching for patterns in remote sensing image databases using neural networks  

NASA Technical Reports Server (NTRS)

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

265

Study of scattering patterns and subwavelength scale imaging based on finite-sized metamaterials  

NASA Astrophysics Data System (ADS)

A metamaterial slab, used as a superlens in a subwavelength imaging system, is frequently assumed homogeneous. It is the bulk properties of the metamaterial which are responsible for the resolution of the transferred information in the image domain, as a result of high transverse wave-vector coupling. However, how in a discretized metamaterial, individual meta-atoms (i.e., the meta-elements composing a negative index metamaterial slab) contribute to the imaging process is still actively studied. The main aim of this paper is to investigate the consequences of using only a few meta-atoms as a negative index slab-equivalent for subwavelength scale imaging. We make a specific choice for a meta-atom and investigate its resonant scattering patterns. We report on how knowledge of these 3D scattering patterns provides a means to understand the transfer of high spatial frequencies and assist with the design an improved negative index slab.

Zhang, Yuan; Chuang, Yi-Chen; Schenk, John O.; Fiddy, Michael A.

2012-04-01

266

Wind sets from SMS images - An assessment of quality for GATE. [Synchronous Meteorological Satellite cloud monitoring for GARP Atlantic Tropical Experiment  

NASA Technical Reports Server (NTRS)

The paper analyzes the accuracy, representativeness, and reproducibility of tracer winds in the 1974 GARP Atlantic Tropical Experiment whose data are used as ground truth. The tracer winds were generated by tracking clouds in SMS (Synchronous Meteorological Satellite) images. Data availability limits comparisons to satellite winds with ship winds at the surface and at 250 mb. Attention is focused on how accurately the cloud displacements can be measured and on the extent to which the cloud displacements represent the wind field. Operator errors in obtaining the cloud displacements are examined in a series of reproducibility tests and wind sets. Differences between proximate satellite and ship winds were all under 3 m/sec. Representativeness of cloud tracers for cumulus and cirrus level flow is found to be good within the accuracy of currently available ground truth data.

Suchman, D.; Martin, D. W.

1976-01-01

267

Investigation of mesoscale cloud features viewed by LANDSAT  

NASA Technical Reports Server (NTRS)

The author has identified the following significant results. Some 50 LANDSAT images displaying mesoscale cloud features were analyzed. This analysis was based on the Rayleigh-Kuettner model describing the formation of that type of mesoscale cloud feature. This model lends itself to computation of the average wind speed in northerly flow from the dimensions of the cloud band configurations measured from a LANDSAT image. In nearly every case, necessary conditions of a curved wind profile and orientation of the cloud streets within 20 degrees of the direction of the mean wind in the convective layer were met. Verification of the results by direct observation was hampered, however, by the incompatibility of the resolution of conventional rawinsonde observations with the scale of the banded cloud patterns measured from LANDSAT data. Comparison seems to be somewhat better in northerly flows than in southerly flows, with the largest discrepancies in wind speed being within 8m/sec, or a factor of two.

Sherr, P. E. (principal investigator); Feteris, P. J.; Lisa, A. S.; Bowley, C. J.; Fowler, M. G.; Barnes, J. C.

1976-01-01

268

Imaging pattern formation in surface reactions from ultra-high vacuum up to atmospheric pressures  

Microsoft Academic Search

Two new optical imaging methods with submonolayer surface sensitivity are applied together to investigate pattern formation of adsorbate concentrations on surfaces during heterogeneously catalyzed reactions. Ellipso-microscopy for surface imaging (EMSI) is based on an ellipsometric effect, reflection anisotropy microscopy (RAM) on the different reflectivity properties of non-isotropic surfaces.During the CO oxidation reaction on a Pt(110) surface, features such as front

Harm Hinrich Rotermund

1997-01-01

269

Model-Driven Integration for a Service Placement Optimizer in a Sustainable Cloud of Clouds  

E-print Network

International, Inc. San Mateo, CA 94402, U.S.A. Email: {higuchi, yyamano, oba}@ogis-international.com Abstract--"Cloud integration models using Enterprise Integration Patterns (EIPs) and Cloud Computing Patterns (CCPs) and (2, federated clouds, model-driven system integration and sustainable clouds I. INTRODUCTION Cloud computing

Suzuki, Jun

270

A Physical Retrieval of Cloud Liquid Water Over the Global Oceans Using Special Sensor Microwave\\/Imager (SSM\\/I) Observations  

Microsoft Academic Search

A method of remotely sensing integrated cloud liquid water over the oceans using spaceborne passive measurements from the special sensor microwave\\/imager (SSM\\/I) is described. The tech- nique is comprised of a simple physical model that uses the 19.35- and 37-GHz channels of the SSM\\/I. The most comprehensive validation to date of cloud liquid water estimated from satellites is presented. This

THOMAS J. GREENWALD; AEME L. STEPHENS; THOMAS H. VONDEII-IAAa

271

Comparing irradiance fields derived from Moderate Resolution Imaging Spectroradiometer airborne simulator cirrus cloud retrievals with solar spectral flux radiometer measurements  

NASA Astrophysics Data System (ADS)

During the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment, the Moderate Resolution Imaging Spectroradiometer (MODIS) airborne simulator (MAS) and the solar spectral flux radiometer (SSFR) operated on the same aircraft, the NASA ER-2. While MAS provided two-dimensional horizontal fields of cloud optical thickness and effective ice particle radius, the SSFR measured spectral irradiance in the visible to near-infrared wavelength range (0.3-1.7 ?m). The MAS retrievals, along with vertical profiles from a combined radar/lidar system on board the same aircraft were used to construct three-dimensional cloud fields, which were input into Monte Carlo radiative transfer models. The simulated field of spectral albedo (ratio of reflected upwelling to incident downwelling irradiance) was compared with the SSFR measurements. For two cases, the relative importance of spatial cloud heterogeneities, various approximations of the single scattering parameters, vertical structure, cirrus optical thickness, and ice crystal effective radius was studied.

Schmidt, K. Sebastian; Pilewskie, Peter; Platnick, Steven; Wind, Gala; Yang, Ping; Wendisch, Manfred

2007-12-01

272

Microphysical Analysis using Airborne 2-D Cloud and Precipitation Imaging Probe Data  

NASA Astrophysics Data System (ADS)

The NOAA P-3 instrumented aircraft provided in-situ cloud and precipitation microphysical observations during the DYNAMO (Dynamics of the Madden-Julian Oscillation) field experiment. The Particle Measuring System 2D cloud (2D-C) and precipitation (2D-P) probes collected data for particles between 12.5 ?m - 1.55 mm (25 ?m resolution) and 100 ?m - 6.2 mm (100 ?m resolution), respectively. Spectra from each instrument were combined to provide a broad distribution of precipitation particle sizes. The 'method of moments' technique was used to analyze drop size distribution (DSD) spectra, which were modeled by fitting a three-parameter (slope, shape, and intercept) gamma distribution to the spectra. The characteristic shape of the mean spectrum compares to previous maritime measurements. DSD variability will be presented with respect to the temporal evolution of cloud populations during a Madden-Julian Oscillation (MJO) event, as well as in-situ aircraft vertical wind velocity measurements. Using the third and sixth moments, rainfall rate (R) and equivalent radar reflectivity factor (Z), respectively, were computed for each DSD. Linear regression was applied to establish a Z-R relationship for the data for the estimation of precipitation. The study indicated unique characteristics of microphysical processes for this region. These results are important to continue to define the cloud population characteristics in the climatological MJO region. Improved representation of the cloud characteristics on the microphysical scale will serve as a check to model parameterizations, helping to improve numerical simulations.

Guy, N.; Jorgensen, D.; Witte, M.; Chuang, P. Y.; Black, R. A.

2013-12-01

273

Towards Efficient Automated Characterization of Irregular Histology Images via Transformation to Frieze-Like Patterns  

E-print Network

Towards Efficient Automated Characterization of Irregular Histology Images via Transformation to Frieze-Like Patterns ABSTRACT Histology is used in both clinical and research contexts as a highly equipment has enabled high-throughput digitization of high-resolution histology slides, the manual scoring

274

Patterned interrogation scheme for compressed sensing photoacoustic imaging using a Fabry Perot planar sensor  

NASA Astrophysics Data System (ADS)

Photoacoustic tomography (PAT) has become a powerful tool for biomedical imaging, particularly pre-clinical small animal imaging. Several different measurement systems have been demonstrated, in particular, optically addressed Fabry-Perot interferometer (FPI) sensors have been shown to provide exquisite images when a planar geometry is suitable. However, in its current incarnation the measurements must be made at each point sequentially, so these devices therefore suffer from slow data acquisition time. An alternative to this point-by-point interrogation scheme, is to interrogate the whole sensor with a series of independent patterns, so each measurement is the spatial integral of the product of the pattern and the acoustic field (as in the single-pixel Rice camera). Such an interrogation scheme allows compressed sensing to be used. This enables the number of measurements to be reduced significantly, leading to much faster data acquisition. An experimental implementation will be described, which employs a wide NIR tunable laser beam to interrogate the FPI sensor. The reflected beam is patterned by a digital micro-mirror device, and then focused to a single photodiode. To demonstrate the idea of patterned and compressed sensing for ultrasound detection, a scrambled Hadamard operator is used in the experiments. Photoacoustic imaging experiments of phantoms shows good reconstructed results with 20% compression.

Huynh, Nam; Zhang, Edward; Betcke, Marta; Arridge, Simon; Beard, Paul; Cox, Ben

2014-03-01

275

VITILIGO & NLRP1 Presented by Sarah Hamilton http://www.avrf.org/images/vitiligo-patterns.gif  

E-print Network

VITILIGO & NLRP1 Presented by Sarah Hamilton http://www.avrf.org/images/vitiligo-patterns.gif #12;Vitiligo Facts Autoimmune disease ­ loss of melanocytes Affects 2-4 million Americans; 65 million diseases http://www.bio.davidson.edu/Courses/Immunology/Students/Spring2003/Leese/Vitiligo.jpg #12;Vitiligo

Skop, Ahna

276

Strategies for the Segmentation of Subcutaneous Vascular Patterns in Thermographic Images  

NASA Astrophysics Data System (ADS)

Computer-assisted segmentation of vascular patterns in thermographic images provides the clinician with graphic outlines of thermally significant subcutaneous blood vessels. Segmentation strategies compared here consist of image smoothing protocols followed by thresholding and zero-crossing edge detectors. Median prefiltering followed by the Frei-Chen algorithm gave the most reproducible results, with an execution time of 143 seconds for 256 X 256 images. The Laplacian of Gaussian operator was not suitable due to streak artifacts in the thermographic imaging system. This computerized process may be adopted in a fast paced clinical environment to aid in the diagnosis and assessment of peripheral circulatory diseases, Raynaud's Disease3, phlebitis, varicose veins, as well as diseases of the autonomic nervous system. The same methodology may be applied to enhance the appearance of abnormal breast vascular patterns, and hence serve as an adjunct to mammography in the diagnosis of breast cancer. The automatically segmented vascular patterns, which have a hand drawn appearance, may also be used as a data reduction precursor to higher level pattern analysis and classification tasks.

Chan, Eric K. Y.; Pearce, John A.

1989-05-01

277

MATCHING CANVAS WEAVE PATTERNS FROM PROCESSING X-RAY IMAGES OF MASTER PAINTINGS  

E-print Network

MATCHING CANVAS WEAVE PATTERNS FROM PROCESSING X-RAY IMAGES OF MASTER PAINTINGS Don H. Johnson) of the canvas weave comprising a painting's support. Our spectral-based algorithm employs a variant of short frequencies. Paint- ings made on canvas sections cut from the same canvas roll have been hypothesized to have

278

A MULTI-MODAL PATTERN CLASSIFICATION FRAMEWORK FOR HYPERSPECTRAL IMAGE ANALYSIS  

E-print Network

A MULTI-MODAL PATTERN CLASSIFICATION FRAMEWORK FOR HYPERSPECTRAL IMAGE ANALYSIS Wei Li, Saurabh Analysis (LFDA) [6] to reduce the dimensionality of the data while preserving its multi- modal structure reduction is a crucial preprocessing step for effective analysis of high dimensional hyperspectral imagery

Fowler, James E.

279

Multichannel analysis of correlation length of SEVIRI images around ground-based cloud observatories to determine their representativeness  

NASA Astrophysics Data System (ADS)

Images of the geostationary Meteosat-9 SEVIRI instrument during the year 2012 are analyzed with respect to the representativeness of the observations of eight cloud observatories in Europe. Cloudy situations are selected to get a time series for every pixel in a 300 km × 300 km area centered around each ground station. Then the Pearson correlation coefficient of each time series to the one of the pixel nearest to the corresponding ground site is calculated. The area for which a station is representative is defined by the characteristic radius around each station for each SEVIRI channel, where the average correlation falls below 0.9. It is found that measurements in the visible and near infrared channels, which respond to cloud microphysics, are correlated in an area with a 1 to 4 km radius, while the thermal channels, that correspond to cloud top temperature, are correlated to a distance of about 20 km. The defined radius even increases for the water vapor and ozone channels. While all stations in Central Europe are quite alike, the correlations around the station in the mountains of southern Italy are much lower. Additionally correlations at different distances corresponding to the grid box sizes of forecast models were compared. The results show good comparability between regional forecast models (grid size ? 10 km) and ground-based measurements since the correlations in less than 10 km distance are in all cases higher than 0.8. For larger distances like they are typical for global models (grid size ? 20 km) the correlations decrease to 0.6, especially for shortwave measurements and corresponding cloud products. By comparing daily means, the characteristic radius of each station is increased to about 3 to 10 times the value of instantaneous measurements and also the comparability to models grows.

Slobodda, J.; Hünerbein, A.; Lindstrot, R.; Preusker, R.; Ebell, K.; Fischer, J.

2014-06-01

280

IMAGE-EUV Observation of Large Scale Standing Wave Pattern in the Nightside Plasmasphere  

NASA Technical Reports Server (NTRS)

We present analyses of a nightside plasmaspheric pattern of bifurcated, filamentary He(+) 30.4-nm emission enhancements observed by IMAGE EUV between approximately 19:40-22:13 UT on 28 June 2000 that indicate the presence of a large-scale, global ULF standing wave pattern. Analysis of coincident IMAGE magnetometer chain data reveals that these ULF waves extend across the magnetic latitude-longitude range of the chain and possess multiple spectral features between 0.6-5-mHz (3-30 minute period). Additionally, analysis of ACE SWE data reveals similarly structured spectral components in the solar wind. Collectively, these analyses lead to the conclusion that the observed large-scale ULF wave pattern is the result of solar wind pressure pulses 'ringing' the inner-magnetosphere.

Six, N. Frank (Technical Monitor); Gallagher, D. L.; Adrian, M. L.; Sandel, B. R.

2002-01-01

281

Hotspot detection using image pattern recognition based on higher-order local auto-correlation  

NASA Astrophysics Data System (ADS)

Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

2011-04-01

282

Characterising the dynamics of expirated bloodstain pattern formation using high-speed digital video imaging.  

PubMed

During forensic investigations, it is often important to be able to distinguish between impact spatter patterns (blood from gunshots, explosives, blunt force trauma and/or machinery accidents) and bloodstain patterns generated by expiration (blood from the mouth, nose or lungs). These patterns can be difficult to distinguish on the basis of the size of the bloodstains. In this study, high-speed digital video imaging has been used to investigate the formation of expirated bloodstain patterns generated by breathing, spitting and coughing mechanisms. Bloodstain patterns from all three expiration mechanisms were dominated by the presence of stains less than 0.5 mm in diameter. Video analysis showed that in the process of coughing blood, high-velocity, very small blood droplets were ejected first. These were followed by lower velocity, larger droplets, strands and plumes of liquid held together in part by saliva. The video images showed the formation of bubble rings and beaded stains, traditional markers for classifying expirated patterns. However, the expulsion mechanism, the distance travelled by the blood droplets, and the type of surface the blood was deposited on were all factors determining whether beaded stains were generated. PMID:20668870

Donaldson, Andrea E; Walker, Nicole K; Lamont, Iain L; Cordiner, Stephen J; Taylor, Michael C

2011-11-01

283

Exploiting adaptive total variation model for image reconstruction from speckle patterns  

NASA Astrophysics Data System (ADS)

Due to the multiple scattering of light in turbid media such as biological tissues, the image of target becomes highly deteriorated even disappears entirely. The adaptive total variation (ATV) image reconstruction algorithm, which is based on majorization-minimization approach together with Bayesian framework, is utilized to recover the object from its speckle pattern. Numerical simulation results indicates that, compared with Tikhonov regularization method, the ATV approach can effectively suppress the noise of the restored image and preserve more image details as well, consequently greatly boosts the SNR and the sharpness of the result image. Furthermore, the recovered results by ATV algorithm have overcome the diffraction-limit of the conventional optical system. Consequently, the combination of ATV algorithm with multiple scattering of turbid media will be beneficial to the observation of cells and protein molecules in biological tissues and other structures in micro/nano scale.

Gong, Changmei; Shao, Xiaopeng; Wu, Tengfei

2013-08-01

284

Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds  

NASA Astrophysics Data System (ADS)

We compared 1 year of Advanced Microwave Scanning Radiometer-EOS (AMSR-E) Wentz and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud liquid water path estimates in warm marine clouds. In broken scenes AMSR-E increasingly overestimated MODIS, and retrievals became uncorrelated as cloud fraction decreased, while in overcast scenes the techniques showed generally better agreement, but with a MODIS overestimation. We found microwave and visible near-infrared retrievals being most consistent in extensive marine Sc clouds with correlations up to 0.95 and typical RMS differences of 15 g m-2. The overall MODIS high bias in overcast domains could be removed, in a global mean sense, by adiabatic correction; however, large regional differences remained. Most notably, MODIS showed strong overestimations at high latitudes, which we traced to 3-D effects in plane-parallel visible-near-infrared retrievals over heterogeneous clouds at low Sun. In the tropics or subtropics, AMSR-E-MODIS differences also depended on cloud type, with MODIS overestimating in stratiform clouds and underestimating in cumuliform clouds, resulting in large-scale coherent bias patterns where marine Sc transitioned into trade wind Cu. We noted similar geographic variations in Wentz cloud temperature errors and MODIS 1.6-3.7 ?m droplet effective radius differences, suggesting that microwave retrieval errors due to cloud absorption uncertainties, and visible near-infrared retrieval errors due to cloud vertical stratification might have contributed to the observed liquid water path bias patterns. Finally, cloud-rain partitioning was found to introduce a systematic low bias in Wentz retrievals above 180 g m-2 as the microwave algorithm erroneously assigned an increasing portion of the liquid water content of thicker nonprecipitating clouds to rain.

Seethala, C.; HorváTh, ÁKos

2010-07-01

285

Observations and Modeling of 3-Dimensional Cloud and Aerosol Fields from the Multiangle SpectroPolarimetric Imager (MSPI)  

NASA Astrophysics Data System (ADS)

Knowledge of the detailed 3-dimensional structure of clouds and atmospheric aerosols is vital for correctly modeling their radiative effects and interpreting optical remote sensing measurements of scattered sunlight. We will describe a set of new observations made by the Multiangle SpectroPolarimetric Imager (MSPI) from the ground and from the NASA ER-2 aircraft. MSPI is being developed and tested at JPL as a payload for the preliminary Aerosol-Cloud-Ecosystems (PACE) satellite mission, which is expected to fly near the end of the decade. MSPI builds upon experience gained from the Multi-angle Imaging SpectroRadiometer (MISR) currently orbiting on NASA's Terra satellite. Ground-MSPI and Air-MSPI are two prototype cameras operating in the ultraviolet (UV) to the visible/near-infrared (VNIR) range mounted on gimbals that acquire imagery in a pushbroom fashion, including polarization in selected spectral bands with demonstrated high polarimetric accuracy (0.5% uncertainty in degree of linear polarization). The spatial resolution of Ground-MSPI is 1 m for objects at a distance of 3 km. From the operational altitude of the ER-2, Air-MSPI has a ground resolution of approximately 10 m at nadir. This resolution, coupled with good calibration and high polarimetric performance means that MSPI can be used to derive radiatively important parameters of aerosols and clouds using intensity and polarization information together. As part of the effort for developing retrieval algorithms for the instrument, we have employed an extremely flexible 3-dimensional vector radiative transfer code. We will show example imagery from both MSPI cameras and describe how these scenes are modeled using this code. We will also discuss some of the important unknowns and limitations of this observational approach.

Garay, M. J.; Diner, D. J.; Martonchik, J. V.; Davis, A. B.

2011-12-01

286

Integration of Image Data for Refining Building Boundaries Derived from Point Clouds  

NASA Astrophysics Data System (ADS)

Geometrically and topologically correct 3D building models are required to satisfy with new demands such as 3D cadastre, map updating, and decision making. More attention on building reconstruction has been paid using Airborne Laser Scanning (ALS) point cloud data. The planimetric accuracy of roof outlines, including step-edges is questionable in building models derived from only point clouds. This paper presents a new approach for the detection of accurate building boundaries by merging point clouds acquired by ALS and aerial photographs. It comprises two major parts: reconstruction of initial roof models from point clouds only, and refinement of their boundaries. A shortest closed circle (graph) analysis method is employed to generate building models in the first step. Having the advantages of high reliability, this method provides reconstruction without prior knowledge of primitive building types even when complex height jumps and various types of building roof are available. The accurate position of boundaries of the initial models is determined by the integration of the edges extracted from aerial photographs. In this process, scene constraints defined based on the initial roof models are introduced as the initial roof models are representing explicit unambiguous geometries about the scene. Experiments were conducted using the ISPRS benchmark test data. Based on test results, we show that the proposed approach can reconstruct 3D building models with higher geometrical (planimetry and vertical) and topological accuracy.

Perera, S. N.; Hetti Arachchige, N.; Schneider, D.

2014-08-01

287

Global ice cloud observations: radiative properties and statistics from moderate-resolution imaging spectroradiometer measurements  

E-print Network

parameter. This technique is based on a previous method developed by Meyer et al. (2004). The applicability of the algorithm is demonstrated with retrievals from level-2 and -3 MODIS data. The technique is also evaluated with the operational MODIS cloud...

Meyer, Kerry Glynne

2009-05-15

288

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures  

NASA Technical Reports Server (NTRS)

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.

1990-01-01

289

Lacunarity analysis of spatial pattern in CT images of vertebral trabecular bone for assessing osteoporosis.  

PubMed

The structural integrity of vertebral trabecular bone is determined by the continuity of its trabecular network and the size of the holes comprising its marrow space, both of which determine the apparent size of the marrow spaces in a transaxial CT image. A model-independent assessment of the trabeculation pattern was determined from the lacunarity of thresholded CT images. Using test images of lumbar vertebrae from human cadavers, acquired at different slice thicknesses, we determined that both median thresholding and local adaptive thresholding (using a 7 x 7 window) successfully segmented the grey-scale images. Lacunarity analysis indicated a multifractal nature to the images, and a range of marrow space sizes with significant structure around 14-18 mm(2). Preliminary studies of in vivo images from a clinical CT scanner indicate that lacunarity analysis can follow the pattern of bone loss in osteoporosis by monitoring the homogeneity of the marrow spaces, which is related to the connectivity of the trabecular bone network and the marrow space sizes. Although the patient sample was small, derived parameters such as the maximum deviation of the lacunarity from a neutral (fractal) model, and the maximum derivative of this deviation, seem to be sufficiently sensitive to distinguish a range of bone conditions. Our results suggest that these parameters, used with bone mineral density values, may have diagnostic value in characterizing osteoporosis and predicting fracture risk. PMID:11886832

Dougherty, Geoffrey; Henebry, Geoffrey M

2002-03-01

290

Cloud Arcs in the Western Pacific  

NASA Technical Reports Server (NTRS)

Small cumulus clouds in this natural-color view from the Multi-angle Imaging SpectroRadiometer have formed a distinctive series of quasi-circular arcs. Clues regarding the formation of these arcs can be found by noting that larger clouds exist in the interior of each arc.

The interior clouds are thicker and likely to be more convectively active than the other clouds, causing much of the air near the centers of the arcs to rise. This air spreads out horizontally in all directions as it rises and continues to spread out as it begins to sink back to the surface. This pushes any existing small cumulus clouds away from the central region of convection.

As the air sinks, it also warms, preventing other small clouds from forming, so that the regions just inside the arcs are kept clear. At the arcs, the horizontal flow of sinking air is now quite weak and on meeting the undisturbed air it can rise again slightly -- possibly assisting in the formation of new small cumulus clouds. Although examples of the continuity of air, in which every rising air motion must be compensated by a sinking motion elsewhere, are very common, the degree of organization exhibited here is relatively rare, as the wind field at different altitudes usually disrupts such patterns. The degree of self organization of this cloud image, whereby three or four such circular events form a quasi-periodic pattern, probably also requires a relatively uncommon combination of wind, temperature and humidity conditions for it to occur.

The image was acquired by MISR's nadir camera on March 11, 2002, and is centered west of the Marshall Islands. Enewetak Atoll is discernible through thin cloud as the turquoise band near the right-hand edge of the image.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and views almost the entire globe every 9 days. This image is a portion of the data acquired during Terra orbit 11863, and covers an area of about 380 kilometers x 345 kilometers. It utilizes data from blocks 80 to 82 within World Reference System-2 path 90.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

2002-01-01

291

Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites  

NASA Technical Reports Server (NTRS)

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics (ITCZ and the deep convective clouds over the western tropical Pacific and Indian sub-continent).

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.

2012-01-01

292

A local-sky star recognition algorithm based on rapid triangle pattern index for ICCD images  

NASA Astrophysics Data System (ADS)

Local-sky star recognition algorithm is a process of recognizing the extracted stars in image by making use of the prior rough attitude of star sensor in celestial sphere. In order to improve the detection and response performance of star sensor working in dynamic condition, ICCD is applied to imaging stars. However, image taken by ICCD has more non-Gaussian noise and the energy of imaging star is unstable. So a local-sky star recognition algorithm using spatial triangular relationship as matching features is supposed to deal with the difficulties. In the first place, an index array is designed according to Guide Triangles, which is applied to construct Guide Triangle Index List. In the second place, a general directing range of star sensor boresight is calculated according to FOV of star sensor and the output of inertial guidance system, and then, the candidate Guide Triangles set in above region is obtained rapidly. In the third place, construct image triangle patterns by applying position and energy of the extracted stars in the image, and then match the image triangle patterns with the above candidate Guide Triangles set for two stages, until N(N>=2) groups of successfully matched triangles pairs with smallest matching deviations sum are obtained. At the last, the recognized Guide Stars have to be matched posterior referring to the principle of simulated sky image, and the recognition results of image stars are all obtained. The proposed algorithm has compact Guide Database structure, rapid local-sky guide triangles obtaining, and good recognition correction percentage, even it has worse star location precision and more false stars. The simulation tests are performed to validate the relative efficiency and adaptation of the algorithm.

Zhang, Wei; Qi, Sheng-xiang; Zhang, Rui; Yang, Lili; Sun, Ji-fu; Song, Li-quan; Tian, Jin-wen

2013-09-01

293

Ammonia Clouds on Jupiter  

NASA Technical Reports Server (NTRS)

[figure removed for brevity, see original site] Click on the image for movie of Ammonia Ice Clouds on Jupiter

In this movie, put together from false-color images taken by the New Horizons Ralph instrument as the spacecraft flew past Jupiter in early 2007, show ammonia clouds (appearing as bright blue areas) as they form and disperse over five successive Jupiter 'days.' Scientists noted how the larger cloud travels along with a small, local deep hole.

2007-01-01

294

Imaging nanometer-thick patterned self-assembled monolayers via second-harmonic generation microscopy  

SciTech Connect

We have used the inherent surface sensitivity of second-harmonic generation to develop an instrument for nonlinear optical microscopy of surfaces and interfaces. This optical technique is ideal for imaging nanometer-thick, chromophoric self-assembled monolayers (SAMs), which have been patterned using photolithographic techniques. In this paper, we demonstrate the application of second-harmonic generation microscopy to patterned SAMs of the noncentrosymmetric molecule calixarene and discuss the resolution and sensitivity limits of the technique. {copyright} {ital 1997 American Institute of Physics.}

Smilowitz, L.; Jia, Q.X.; Yang, X.; Li, D.Q.; McBranch, D.; Buelow, S.J.; Robinson, J.M. [Chemical Sciences and Technology Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)] [Chemical Sciences and Technology Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)

1997-03-01

295

Imaging evaluation of lymphadenopathy and patterns of lymph node spread in head and neck cancer.  

PubMed

Accurate and consistent characterization of metastatic cervical adenopathy is essential for the initial staging, treatment planning and surveillance of head and neck cancer patients. While enlarged superficial nodes may be clinically palpated, imaging allows identification of deeper adenopathy as well as clinically unsuspected pathology and thus imaging has become an integral part of the evaluation of most head and neck cancers patients. This review will focus on the evaluation of cervical adenopathy, summarizing the currently used nomenclature and imaging approach for determining cervical lymph node metastases in head and neck malignancies. The imaging-based classification, which has also been adopted by the American Joint Committee on Cancer, will be presented, the morphologic characteristics used to identify metastatic nodes will be reviewed and the typical nodal spread patterns of the major mucosal cancers of the head and neck will be examined. PMID:25385488

Forghani, Reza; Yu, Eugene; Levental, Mark; Som, Peter M; Curtin, Hugh D

2015-02-01

296

Toward Image-Based Three-Dimensional Reconstruction from Cubesats: Impacts of Spatial Resolution and SNR on Point Cloud Quality  

NASA Astrophysics Data System (ADS)

The adoption of cube-satellites (cubesats) by the space community has drastically lowered the cost of access to space and reduced the development lifecycle from the hundreds of millions of dollars spent on traditional decade-long programs. Rapid deployment and low cost are attractive features of cubesat-based imaging that are conducive to applications such as disaster response and monitoring. One proposed application is 3D surface modeling through a high revisit rate constellation of cubesat imagers. This work begins with the characterization of an existing design for a cubesat imager based on ground sampled distance (GSD), signal-to-noise ratio (SNR), and smear. From this characterization, an existing 3D workflow is applied to datasets that have been degraded within the regime of spatial resolutions and signal-to-noise ratios anticipated for the cubesat imager. The fidelity of resulting point clouds are assessed locally for both an urban and a natural scene. The height of a building and normals to its surfaces are calculated from the urban scene, while quarry depth estimates and rough volume estimates of a pile of rocks are produced from the natural scene. Though the reconstructed scene geometry and completeness of the scene suffer noticeably from the degraded imagery, results indicate that useful information can still be extracted using some of these techniques up to a simulated GSD of 2 meters.

Stoddard, Jordyn

297

Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS)  

NASA Technical Reports Server (NTRS)

The authors describe the status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning spectrometer with 32 uniformly spaced channels between 0.410 and 0.875 micron. They review the various methods being developed for the remote sensing of atmospheric properties using MODIS, placing primary emphasis on the principal atmospheric applications of determining the optical, microphysical, and physical properties of clouds and aerosol particles from spectral reflection and thermal emission measurements. In addition to cloud and aerosol properties, MODIS-N will be used for determining the total precipitable water vapor and atmospheric stability. The physical principles behind the determination of each of these atmospheric products are described, together with an example of their application to aircraft and/or satellite measurements.

King, Michael D.; Kaufman, Yoram J.; Menzel, W. Paul; Tanre, Didier D.

1992-01-01

298

Effect of Clouds on Optical Imaging of the Space Shuttle During the Ascent Phase: A Statistical Analysis Based on a 3D Model  

NASA Technical Reports Server (NTRS)

Clouds are highly effective in obscuring optical images of the Space Shuttle taken during its ascent by ground-based and airborne tracking cameras. Because the imagery is used for quick-look and post-flight engineering analysis, the Columbia Accident Investigation Board (CAIB) recommended the return-to-flight effort include an upgrade of the imaging system to enable it to obtain at least three useful views of the Shuttle from lift-off to at least solid rocket booster (SRB) separation (NASA 2003). The lifetimes of individual cloud elements capable of obscuring optical views of the Shuttle are typically 20 minutes or less. Therefore, accurately observing and forecasting cloud obscuration over an extended network of cameras poses an unprecedented challenge for the current state of observational and modeling techniques. In addition, even the best numerical simulations based on real observations will never reach "truth." In order to quantify the risk that clouds would obscure optical imagery of the Shuttle, a 3D model to calculate probabilistic risk was developed. The model was used to estimate the ability of a network of optical imaging cameras to obtain at least N simultaneous views of the Shuttle from lift-off to SRB separation in the presence of an idealized, randomized cloud field.

Short, David A.; Lane, Robert E., Jr.; Winters, Katherine A.; Madura, John T.

2004-01-01

299

Cloud computing platform for GIS image processing in U-city  

Microsoft Academic Search

Ubiquitous city (U-city) is a city with ubiquitous information technology that enables citizens to access the converged information anywhere and anytime. A lot of compute power are required in U-city, because large amount of data should be processed in real-time. Cloud computing enables users to use the abstracted and virtualized computing resources and to process huge amount of information without

Jong Won Park; Chang Ho Yun; Shin-gyu Kim; Heon Y. Yeom; Yong Woo Lee

2011-01-01

300

Multi-line spectral imaging of dense cores in the Lupus molecular cloud  

E-print Network

The molecular clouds Lupus 1, 3 and 4 were mapped with the Mopra telescope at 3 and 12 mm. Emission lines from high density molecular tracers were detected, i.e. NH$_3$ (1,1), NH$_3$ (2,2), N$_2$H$^+$ (1-0), HC$_3$N (3-2), HC$_3$N (10-9), CS (2-1), CH$_3$OH (2$_0-1_0$)A$^+$ and CH$_3$OH (2$_{-1}-1_{-1}$)E. Velocity gradients of more than 1 km s$^{-1}$ are present in Lupus 1 and 3 and multiple gas components are present in these clouds along some lines of sight. Lupus 1 is the cloud richest in high density cores, 8 cores were detected in it, 5 cores were detected in Lupus 3 and only 2 in Lupus 4. The intensity of the three species HC$_3$N, NH$_3$ and N$_2$H$^+$ changes significantly in the various cores: cores that are brighter in HC$_3$N are fainter or undetected in NH$_3$ and N$_2$H$^+$ and vice versa. We found that the column density ratios HC$_3$N/N$_2$H$^+$ and HC$_3$N/NH$_3$ change by one order of magnitude between the cores, indicating that also the chemical abundance of these species is different. The ...

Benedettini, Milena; Burton, Micheal G; Viti, Serena; Molinari, Sergio; Caselli, Paola; Testi, Leonardo

2011-01-01

301

Variations in the referral patterns to stress nuclear imaging and stress echocardiography scans  

Microsoft Academic Search

Background  Stress myocardial perfusion imaging (MPI) and stress echocardiography (Echo) are commonly used for the noninvasive evaluation\\u000a of patients with suspected coronary artery disease (CAD). Very few studies have compared the referral patterns to these imaging\\u000a modalities in terms of the clinical profile of patients, reasons for referral, and type of referring physicians.\\u000a \\u000a \\u000a \\u000a \\u000a Methods and Results  This was a prospective study of

Salam Itani; Walid Gharzuddine; Samir Arnaout; Mukbil Hourani; Samir Alam; Habib A. Dakik

2009-01-01

302

An X-ray image of the Large Magellanic Cloud and a study of its hot interstellar medium  

SciTech Connect

A comprehensive re-analysis of the Einstein Observatory imaging survey of the Large Magellanic Cloud is presented. Techniques necessary for the study of diffuse x-rays are described in detail. A discrete source search of a {approximately}37 deg{sup 2} region in the vicinity of the LMC reveals 105 sources, 33 of which are reported here for the first time. Subtraction of all discrete emitters reveals extensive diffuse x-ray emission with a luminosity of {approximately}2 {times} 10{sup 38} erg s{sup {minus}1} associated with the Cloud. The spectrum of this emission, well fitted by an optically thin thermal plasma, reveals a temperature range from {approximately}10{sup 6}K in the western part of the galaxy to {approximately}10{sup 7}K in the vicinity of the active star formation complex near 30 Doradus. An anticorrelation of HI and diffuse x-rays on scales of {le}1 kpc is consistent with a picture in which superbubbles of hot gas are created in the neutral ISM by the combined action of stellar winds and supernovae in massive stellar associations. Combining the x-ray survey with the information derived from observations in other wavelength bands, the author assesses the physical condition of the hot gas in the Cloud. In particular, he shows that the detection of two dozen x-ray bright OB associations is consistent with a scenario in which recent supernovae enhance the x-ray emission of wind-driven ISM bubbles around these young associations.

Wang, Qingde.

1990-01-01

303

Efficient generation of diffraction-limited multi-sheet pattern for biological imaging.  

PubMed

We demonstrate a new technique to generate multiple light-sheets for fluorescence microscopy. This is possible by illuminating the cylindrical lens using multiple copies of Gaussian beams. A diffraction grating placed just before the cylindrical lens splits the incident Gaussian beam into multiple beams traveling at different angles. Subsequently, this gives rise to diffraction-limited light-sheets after the Gaussian beams pass through the combined cylindrical lens-objective sub-system. Direct measurement of field at and around the focus of objective lens shows multi-sheet pattern with an average thickness of 7.5 ?m and inter-sheet separation of 380 ?m. Employing an independent orthogonal detection sub-system, we successfully imaged fluorescently-coated yeast cells (?4???m) encaged in agarose gel-matrix. Such a diffraction-limited sheet-pattern equipped with dedicated detection system may find immediate applications in the field of optical microscopy and fluorescence imaging. PMID:25680162

Mondal, Partha Pratim; Dilipkumar, Shilpa; Mohan, Kavya

2015-02-15

304

Drainage patterns of the cholecystic vein evaluated by power doppler imaging  

Microsoft Academic Search

Power Doppler imaging (PDI) is a new technique that enhances detection of low-velocity blood flow. We used this modality to\\u000a assess gallbladder vasculature, especially drainage pattern and flow analysis of the cholecystic vein. The power Doppler equipment\\u000a used in this study was the Acuson Sequoia 512 system (Mountain View, California). Subjects were 27 patients with acute cholecystitis,\\u000a 9 with gallbladder

Keisuke Osakabe; Yuji Horiguchi; Hideo Imai; Hiroshi Sakamoto; Tomohiro Suzuki; Hiroshi Kubo; Masanao Uematsu; Fumiyasu Takeuchi; Yuko Nakamura; Takao Hayashi; Masahiro Asano; Toru Nishikawa; Yuko Kushi; Horoshi Nakano

2001-01-01

305

Voyager 1 imaging and IRIS observations of Jovian methane absorption and thermal emission: Implications for cloud structure  

NASA Technical Reports Server (NTRS)

Images from three filters of the Voyager 1 wide angle camera are used to measure the continuum reflectivity and spectral gradient near 6000 A and the 6190 A band methane/continuum ratio for a variety of cloud features in Jupiter's atmosphere. The dark barge features in the North Equatorial Belt have anomalously strong positive continuum spectral gradients suggesting unique composition. Methane absorption is shown at unprecedented spatial scales for the Great Red Spot and its immediate environment, for a dark barge feature in the North Equatorial Belt, and for two hot spot and plume regions in the North Equatorial Belt. Methane absorption and five micrometer emission are correlated in the vicinity of the Great Red Spot but are anticorrelated in one of the plume hot spot regions. Methane absorption and simultaneous maps of five micrometer brightness temperature is quantitatively compared to realistic cloud structure models which include multiple scattering at five micrometer as well as in the visible. Variability in H2 quadrupole lines are also investigated.

West, R. A.; Kupferman, P. N.; Hart, H.

1984-01-01

306

Waves on White: Ice or Clouds?  

NASA Technical Reports Server (NTRS)

As it passed over Antarctica on December 16, 2004, the Multi-angle Imaging SpectroRadiometer (MISR) on NASA's Terra satellite captured this image showing a wavy pattern in a field of white. At most other latitudes, such wavy patterns would likely indicate stratus or stratocumulus clouds. MISR, however, saw something different. By using information from several of its multiple cameras (each of which views the Earth's surface from a different angle), MISR was able to tell that what looked like a wavy cloud pattern was actually a wavy pattern on the ice surface. One of MISR's cloud classification products, the Angular Signature Cloud Mask (ASCM), correctly identified the rippled area as being at the surface.

In this image pair, the view from MISR's most oblique backward-viewing camera is on the left, and the color-coded image on the right shows the results of the ASCM. The colors represent the level of certainty in the classification. Areas that were classed as cloudy with high confidence are white, and areas where the confidence was lower are yellow; dark blue shows confidently clear areas, while light blue indicates clear with lower confidence. The ASCM works particularly well at detecting clouds over snow and ice, but also works well over ocean and land. The rippled area on the surface which could have been mistaken for clouds are actually sastrugi -- long wavelike ridges of snow formed by the wind and found on the polar plains. Usually sastrugi are only several centimeters high and several meters apart, but large portions of East Antarctica are covered by mega-sastrugi ice fields, with dune-like features as high as four meters separated by two to five kilometers. The mega-sastrugi fields are a result of unusual snow accumulation and redistribution processes influenced by the prevailing winds and climate conditions. MISR imagery indicates that these mega sastrugi were stationary features between 2002 and 2004.

Being able to distinguish clouds from snow or ice-covered surfaces is important in order to adequately characterize the radiation balance of the polar regions. However, detecting clouds using spaceborne detectors over snow and ice surfaces is notoriously difficult, because the surface may often be as bright and as cold as the overlying clouds, and because polar atmospheric temperature inversions sometimes mean that clouds are warmer than the underlying snow or ice surface. The Angular Signature Cloud Mask (ASCM) was developed based on the Band-Differenced Angular Signature (BDAS) approach, introduced by Di Girolamo and Davies (1994) and updated for MISR application by Di Girolamo and Wilson (2003). BDAS uses both spectral and angular changes in reflectivity to distinguish clouds from the background, and the ASCM calculates the difference between the 446 and 866 nanometer reflectances at MISR's two most oblique cameras that view forward-scattered light. New land thresholds for the ASCM are planned for delivery later this year.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. This image area covers about 277 kilometers by 421 kilometers in the interior of the East Antarctic ice sheet. These data products were generated from a portion of the imagery acquired during Terra orbit 26584 and utilize data from within blocks 159 to 161 within World Reference System-2 path 63.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

2005-01-01

307

Obtaining breathing patterns from any sequential thoracic x-ray image set  

NASA Astrophysics Data System (ADS)

A technique is presented to allow a breathing pattern to be obtained from any multi-slice CT, cone-beam or other series of sequential chest x-ray image sets. The technique requires no extra signals to be recorded and does not need specific external or internal oscillating structures to be visible in the field of view. The breathing pattern is instead acquired from analysing the variation in pixel values between projection images. For cone-beam image sets, slowly varying changes, due to an angular attenuation dependence, must be corrected before the breathing trace analysis can begin. All the results of the new technique were checked visually and were in good agreement. If the studied image set could be analysed using the existing 'Amsterdam shroud' technique, then the results it provided were also used for comparison. In cases that allowed comparison by both techniques, the results were in agreement. The new technique was also shown to provide a usable signal when applied to cardiac motion.

Kavanagh, Anthony; Evans, Philip M.; Hansen, Vibeke N.; Webb, Steve

2009-08-01

308

Wavelet-based decomposition and analysis of structural patterns in astronomical images  

NASA Astrophysics Data System (ADS)

Context. Images of spatially resolved astrophysical objects contain a wealth of morphological and dynamical information, and effectively extracting this information is of paramount importance for understanding the physics and evolution of these objects. The algorithms and methods currently employed for this purpose (such as Gaussian model fitting) often use simplified approaches to describe the structure of resolved objects. Aims: Automated (unsupervised) methods for structure decomposition and tracking of structural patterns are needed for this purpose to be able to treat the complexity of structure and large amounts of data involved. Methods: We developed a new wavelet-based image segmentation and evaluation (WISE) method for multiscale decomposition, segmentation, and tracking of structural patterns in astronomical images. Results: The method was tested against simulated images of relativistic jets and applied to data from long-term monitoring of parsec-scale radio jets in 3C 273 and 3C 120. Working at its coarsest resolution, WISE reproduces the previous results of a model-fitting evaluation of the structure and kinematics in these jets exceptionally well. Extending the WISE structure analysis to fine scales provides the first robust measurements of two-dimensional velocity fields in these jets and indicates that the velocity fields probably reflect the evolution of Kelvin-Helmholtz instabilities that develop in the flow.

Mertens, Florent; Lobanov, Andrei

2015-02-01

309

Ghost imaging using labyrinth-like phase modulation patterns for high-efficiency and high-security optical encryption  

NASA Astrophysics Data System (ADS)

Ghost imaging has attracted more and more current attention due to its marked physical characteristics, and many physical applications, such as sensing and optical security, have been explored. In this letter, we propose ghost imaging using labyrinth-like phase modulation patterns for optical encryption. Since only one phase-only mask should be pre-set and the labyrinth patterns occupy only few spaces, high-efficiency storage or transmission of system keys can be implemented. In addition, each labyrinth pattern (i.e., phase modulation pattern) possesses high randomness and flexibility, hence high security can be guaranteed for the proposed optical encryption.

Chen, Wen; Chen, Xudong

2015-01-01

310

Jupiter's High-Altitude Clouds  

NASA Technical Reports Server (NTRS)

The New Horizons Multispectral Visible Imaging Camera (MVIC) snapped this incredibly detailed picture of Jupiter's high-altitude clouds starting at 06:00 Universal Time on February 28, 2007, when the spacecraft was only 2.3 million kilometers (1.4 million miles) from the solar system's largest planet. Features as small as 50 kilometers (30 miles) are visible. The image was taken through a narrow filter centered on a methane absorption band near 890 nanometers, a considerably redder wavelength than what the eye can see. Images taken through this filter preferentially pick out clouds that are relatively high in the sky of this gas giant planet because sunlight at the wavelengths transmitted by the filter is completely absorbed by the methane gas that permeates Jupiter's atmosphere before it can reach the lower clouds.

The image reveals a range of diverse features. The south pole is capped with a haze of small particles probably created by the precipitation of charged particles into the polar regions during auroral activity. Just north of the cap is a well-formed anticyclonic vortex with rising white thunderheads at its core. Slightly north of the vortex are the tendrils of some rather disorganized storms and more pinpoint-like thunderheads. The dark 'measles' that appear a bit farther north are actually cloud-free regions where light is completely absorbed by the methane gas and essentially disappears from view. The wind action considerably picks up in the equatorial regions where giant plumes are stretched into a long wave pattern. Proceeding north of the equator, cirrus-like clouds are shredded by winds reaching speeds of up to 400 miles per hour, and more pinpoint-like thunderheads are visible. Although some of the famous belt and zone structure of Jupiter's atmosphere is washed out when viewed at this wavelength, the relatively thin North Temperate Belt shows up quite nicely, as does a series of waves just north of the belt. The north polar region of Jupiter in this image has a mottled appearance, and the scene is not as dynamic as the equatorial and south polar regions.

The intricate structures revealed in this image are exciting, but they are only part of the story. The New Horizons instruments have taken images of Jupiter at approximately 260 different wavelengths, providing essentially a three-dimensional view of Jupiter's atmosphere, since images at different wavelengths probe different altitudes. New Horizons is providing a wealth of data on this fascinating planet during this last close-up view of Jupiter until the middle of the next decade.

2007-01-01

311

Method for characterizing mask defects using image reconstruction from X-ray diffraction patterns  

DOEpatents

The invention applies techniques for image reconstruction from X-ray diffraction patterns on the three-dimensional imaging of defects in EUVL multilayer films. The reconstructed image gives information about the out-of-plane position and the diffraction strength of the defect. The positional information can be used to select the correct defect repair technique. This invention enables the fabrication of defect-free (since repaired) X-ray Mo--Si multilayer mirrors. Repairing Mo--Si multilayer-film defects on mask blanks is a key for the commercial success of EUVL. It is known that particles are added to the Mo--Si multilayer film during the fabrication process. There is a large effort to reduce this contamination, but results are not sufficient, and defects continue to be a major mask yield limiter. All suggested repair strategies need to know the out-of-plane position of the defects in the multilayer.

Hau-Riege, Stefan Peter (Fremont, CA)

2007-05-01

312

Pattern recognition system invariant to rotation and scale to identify color images  

NASA Astrophysics Data System (ADS)

This work presents a pattern recognition digital system based on nonlinear correlations. The correlation peak values given by the system were analyzed by the peak-to-correlation energy (PCE) metric to determine the optimal value of the non-linear coefficient kin the k-law. The system was tested with 18 different color images of butterflies; each image was rotated from 0° to 180° with increments of 1° and scaled ±25% with increments of 1% and to take advantage of the color property of the images the RGB model was employed. The boxplot statistical analysis of the mean with ±2*EE (standard errors) for the PCE values set that the system invariant to rotation and scale has a confidence level at least of 95.4%.

Coronel-Beltrán, Angel

2014-10-01

313

Robust non-parametric probabilistic image processing for face recognition and pattern recognition  

NASA Astrophysics Data System (ADS)

Face Recognition has been a pattern recognition application of great interest. Many mathematical models have been used for face recognition and among them probabilistic methods However, up to now probabilistic methods rely heavily on the number of training data and do not fully exploit the 2-dimensional information of the images, both the training and the testing sets. In this paper's method a new 2-D robust probabilistic method of transforming the principal components of the initial image data, allowing support vector machines to efficiently capture the inference between images. This new algorithm encodes every image with the help of Robust Kernel non Parametric Estimation and in the second stage uses Support Vector Machines to classify this encoded information. Results exhibit that Non Parametric Estimation of the Probability Function of the image highlights the unique characteristics of each person making it easier for classifiers to group those instances and efficiently perform the classification of the images and thus leading to better results compared to up to date methods for face recognition.

Pavlidou, Meropi; Zioutas, George

2014-04-01

314

Cloud tracking by scale space classification  

Microsoft Academic Search

The problem of cloud tracking within a sequence of geo-stationary satellite images has direct relevance to the analysis of cloud life cycles and to the detection of cloud motion vectors (CMVs). The proposed approach first identifies a homogeneous consistent cloud mass for tracking and then establishes motion correspondence within an image sequence. In contrast to the crosscorrelation based approach as

Dipti Prasad Mukherjee; Scott T. Acton

2002-01-01

315

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns  

NASA Technical Reports Server (NTRS)

A technique, associated system and program code, for retrieving depth information about at least one surface of an object, such as an anatomical feature. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the anatomical feature; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor); Guan, Chun (Inventor)

2010-01-01

316

System and technique for retrieving depth information about a surface by projecting a composite image of modulated light patterns  

NASA Technical Reports Server (NTRS)

A technique, associated system and program code, for retrieving depth information about at least one surface of an object. Core features include: projecting a composite image comprising a plurality of modulated structured light patterns, at the object; capturing an image reflected from the surface; and recovering pattern information from the reflected image, for each of the modulated structured light patterns. Pattern information is preferably recovered for each modulated structured light pattern used to create the composite, by performing a demodulation of the reflected image. Reconstruction of the surface can be accomplished by using depth information from the recovered patterns to produce a depth map/mapping thereof. Each signal waveform used for the modulation of a respective structured light pattern, is distinct from each of the other signal waveforms used for the modulation of other structured light patterns of a composite image; these signal waveforms may be selected from suitable types in any combination of distinct signal waveforms, provided the waveforms used are uncorrelated with respect to each other. The depth map/mapping to be utilized in a host of applications, for example: displaying a 3-D view of the object; virtual reality user-interaction interface with a computerized device; face--or other animal feature or inanimate object--recognition and comparison techniques for security or identification purposes; and 3-D video teleconferencing/telecollaboration.

Hassebrook, Laurence G. (Inventor); Lau, Daniel L. (Inventor); Guan, Chun (Inventor)

2008-01-01

317

Image enhancement tools for tracing fringe patterns in holographic interferograms acquired during laser fusion experiments  

SciTech Connect

Pulsed holographic interferometry is essentially the only direct method for determining electron density profiles in inertial fusion plasmas. Consequently, it is a very important diagnostic tool in laser fusion experimentation. The tracing of fringe patterns in the reconstructed holograms is required to determine their precise number and location for subsequent Abel inversion. This is a very labor-intensive task, for which computer assistance has long been sought. In the KMS Fusion multiframe optical probing system, a sequence of four time resolved image frames is produced at rates equivalent to over 5 billion/sec. The increased number of images thus generated has spurred the development of improved methods for handling data. A plan has evolved for providing scientists with interactive adaptive image enhancement tools to assist in locating the fringes. The feasibility of applying digital techniques to aid in the analysis of holographic interferograms has been demonstrated by others. However, only limited success has been achieved in tracing highly dense fringes in the presence of noise. Traditional noise reduction methods tend to fail in the case of high density fringes, where the spatial frequency of the noise is close to that of the pattern to be discerned. Other problems are introduced by uneven lighting conditions, competing fringe patterns (due to aberrations in optical components or other attenuators in the optical path), and bonafide discontinuities in the fringes. Newly developed digital enhancement tools apply tailorable neighborhood operators to individual pixels as directed by a cursor that may be manipulated via jobstick or keyboard control. Operations may be performed on a sectional blow-up while viewing both the full image and the enlarged section. In this manner, global information can be utilized to aid in the local enhancement operations, and vice versa.

Vavra, P.C.; Busch, G.E.; Shepard, C.L.

1983-01-01

318

Wave Clouds over the Arabian Sea  

NASA Technical Reports Server (NTRS)

Like a massive, ethereal bird gliding into the Persian Gulf, a large cluster of wave clouds spans the Arabian Sea from Oman to India. This cloud formation is likely an undular bore, which is created in the interaction between the cool, dry air in a low-pressure system with a stable layer of warm, moist air. In this case, a low-pressure system probably sits over the Arabian Peninsula, the Gulf of Oman, and Iran and Pakistan. The strong winds generated by the low-pressure system are kicking up clouds of dust from Iran and Pakistan, and, to a lesser degree, Oman. The low-pressure system is also pushing air south-southeast, and this south-moving wave of displaced air pushes ahead of the low-pressure system like a mound of water moving ahead of a boat in calm water. The wave of cool, dry air pushes forward until it meets the wall of warm, moist air that blankets the Arabian Sea. When the two air masses clash, the cool air pushes the warm air up. The warm air rises, cools at the peak of the wave, falls again, and then rises to a slightly lower peak, and so forth, until the wave dissipates. Clouds form at the high-altitude peaks of the waves, with the most defined cloud at the front of the group, where the initial wave formed, followed by increasingly less-defined lines of cloud. The air that moves in front of the low-pressure system does not push forward in a uniform wall; instead it pushes forward in a ragged band, with one part racing ahead of another, like a line of crew racers on a river. Because the air is not uniform, there are small, interacting arcs of waves within the larger band of clouds. Undular bores are rare and hard to predict. This particular undular bore formed over the Arabian Sea on May 8, 2007, when the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Aqua satellite captured this photo-like image. Typical undular bore patterns might display one or two rows of clouds. With more than thirty waves of clouds, this cloud pattern is unusually large. Some secondary air mass--a jet of warm tropical air, perhaps--cuts across the center of the wave pattern, creating the long vertical cloud that makes the formation resemble a bird. The undulating air also appears to have roughened the surface of the ocean. Bands of light and dark water mimic the wave pattern near the shore of Oman. Rough water disperses light, creating the dark bands, while calm water is brighter. This wave pattern is probably happening across the Arabian Sea, but it is only visible on the left side of the image because of the angle of the light reflecting from the water. In this area, sunlight reflecting off the water directly to the MODIS sensor turns the water's surface into a silvery mirror. It is only in these areas of sunglint that the surface roughness created by the undular bore is visible. The large image provided above is at MODIS' maximum resolution of 250 meters per pixel. The image is available in additional resolutions from the MODIS Rapid Response System. For a different view of an undular bore, see LIDAR Profile of a Passing Cold Front on the Earth Science Picture of the Day, a service of the Universities Space Research Association sponsored by NASA Goddard Space Flight Center.

2007-01-01

319

An imaging system that autonomously monitors lighting patterns with application to airport lighting  

NASA Astrophysics Data System (ADS)

This paper presents a novel measurement system that assesses the uniformity of a complete airport lighting installation. The system improves safety with regard to aircraft landing procedures by ensuring airport lighting is properly maintained and conforms to current standards and recommendations laid down by the International Civil Aviation Organisation. The measuring device consists of a CMOS vision sensor with associated lens system fitted to the interior of an aircraft. The vision system is capable of capturing sequences of airport lighting images during a normal approach to an aerodrome. These images are then post processed to determine the uniformity of the complete pattern. Airport lighting consists of elevated approach and inset runway luminaires. Each luminaire emits an intensity which is dependant on the angular displacement from the luminaire. For example, during a normal approach a given luminaire will emit its maximum intensity down to its minimum intensity as the aircraft approaches and finally passes over the luminaire. As such, it is possible to predict the intensity that each luminaire within the airport lighting pattern emits, at a given time, during a normal approach. Any luminaires emitting the same intensity can then be banded together for the uniformity analysis. Having derived the theoretical groups of similar luminaires within a standard approach, this information was applied to a sequence of airport lighting images that were recorded during an approach to Belfast International Airport. Since we are looking to determine the uniformity of the pattern, only the total pixel grey level representing each luminaire within each banded group needs to be extracted and tracked through the entire image sequence. Any luminaires which fail to meet the requirements (i.e. a threshold value depending on the performance of the other luminaires in that band) are monitored and reported to the assessor for attention. The extraction and tracking algorithms have been optimised for minimal human intervention. Techniques such as component analysis as well as centre of mass algorithms are used to detect and locate the luminaires. A search algorithm is used to obtain the brightness (total grey level) of each luminaire. For the sample test at Belfast International Airport several luminaires were found that do not output sufficient intensity. As a final conclusion however, the Belfast International lighting pattern is legal and conforms to standards as no two consecutive luminaires fail in the pattern. The techniques used in this paper are novel. No known research exists that couples uniformity of airport lighting with photometrics. A solid basis has been established for future work on monitoring the individual characteristics of the luminaires. This includes colour and intensity measurements.

Niblock, J. H.; McMenemy, K.; Irwin, G. W.

2006-02-01

320

Automatic reconstruction of 3D urban landscape by computing connected regions and assigning them an average altitude from LiDAR point cloud image  

NASA Astrophysics Data System (ADS)

The demand of 3D city modeling has been increasing in many applications such as urban planing, computer gaming with realistic city environment, car navigation system with showing 3D city map, virtual city tourism inviting future visitors to a virtual city walkthrough and others. We proposed a simple method for reconstructing a 3D urban landscape from airborne LiDAR point cloud data. The automatic reconstruction method of a 3D urban landscape was implemented by the integration of all connected regions, which were extracted and extruded from the altitude mask images. These mask images were generated from the gray scale LiDAR image by the altitude threshold ranges. In this study we demonstrated successfully in the case of Kanazawa city center scene by applying the proposed method to the airborne LiDAR point cloud data.

Kawata, Yoshiyuki; Koizumi, Kohei

2014-10-01

321

Parameter Estimation of Fossil Oysters from High Resolution 3D Point Cloud and Image Data  

NASA Astrophysics Data System (ADS)

A unique fossil oyster reef was excavated at Stetten in Lower Austria, which is also the highlight of the geo-edutainment park 'Fossilienwelt Weinviertel'. It provides the rare opportunity to study the Early Miocene flora and fauna of the Central Paratethys Sea. The site presents the world's largest fossil oyster biostrome formed about 16.5 million years ago in a tropical estuary of the Korneuburg Basin. About 15,000 up to 80-cm-long shells of Crassostrea gryphoides cover a 400 m2 large area. Our project 'Smart-Geology for the World's largest fossil oyster reef' combines methods of photogrammetry, geology and paleontology to document, evaluate and quantify the shell bed. This interdisciplinary approach will be applied to test hypotheses on the genesis of the taphocenosis (e.g.: tsunami versus major storm) and to reconstruct pre- and post-event processes. Hence, we are focusing on using visualization technologies from photogrammetry in geology and paleontology in order to develop new methods for automatic and objective evaluation of 3D point clouds. These will be studied on the basis of a very dense surface reconstruction of the oyster reef. 'Smart Geology', as extension of the classic discipline, exploits massive data, automatic interpretation, and visualization. Photogrammetry provides the tools for surface acquisition and objective, automated interpretation. We also want to stress the economic aspect of using automatic shape detection in paleontology, which saves manpower and increases efficiency during the monitoring and evaluation process. Currently, there are many well known algorithms for 3D shape detection of certain objects. We are using dense 3D laser scanning data from an instrument utilizing the phase shift measuring principle, which provides accurate geometrical basis < 3 mm. However, the situation is difficult in this multiple object scenario where more than 15,000 complete or fragmentary parts of an object with random orientation are found. The goal is to investigate if the application of state-of-the-art 3D digitizing, data processing, and visualization technologies support the interpretation of this paleontological site. The obtained 3D data (approx. 1 billion points at the respective area) is analyzed with respect to their 3D structure in order to derive geometrical information. The aim of this contribution is to segment the 3D point cloud of laser scanning data into meaningful regions representing particular objects. Geometric parameters (curvature, tangent plane orientation, local minimum and maximum, etc.) are derived for every 3D point of the point cloud. A set of features is computed in each point using different kernel sizes to define neighborhoods of different size. This provides information on convexity (outer surface), concavity (inner surface) and locally flat areas, which shall be further utilized in fitting model of Crassostrea-shells. In addition, digitizing is performed manually in order to obtain a representative set of reference data for the evaluation of the obtained results. For evaluating these results the reference data (length and orientation of specimen) is then compared to the automatically derived segments of the point cloud. The study is supported by the Austrian Science Fund (FWF P 25883-N29).

Djuricic, Ana; Harzhauser, Mathias; Dorninger, Peter; Nothegger, Clemens; Mandic, Oleg; Székely, Balázs; Molnár, Gábor; Pfeifer, Norbert

2014-05-01

322

IMPROVING KNOWLEDGE DISCOVERY FROM SYNTHETIC APERTURE RADAR IMAGES USING THE LINKED OPEN DATA CLOUD AND SEXTANT  

E-print Network

AND SEXTANT C. Nikolaou, K. Kyzirakos, K. Bereta, K. Dogani, S. Giannakopoulou, P. Smeros, G. Garbis, MSAR-X images can be improved using linked open data and Sextant, a tool for browsing and exploration of linked

Koubarakis, Manolis

323

Many Local Pattern Texture Features: Which Is Better for Image-Based Multilabel Human Protein Subcellular Localization Classification?  

PubMed Central

Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilabel subcellular image samples. We prepared a large multilabel immunohistochemistry (IHC) image benchmark from the Human Protein Atlas database and tested the performance of different local texture features, including completed local binary pattern, local tetra pattern, and the standard local binary pattern feature. According to our experimental results from binary relevance multilabel machine learning models, the completed local binary pattern, and local tetra pattern are more discriminative for describing IHC images when compared to the traditional local binary pattern descriptor. The combination of these two novel local pattern features and the conventional global texture features is also studied. The enhanced performance of final binary relevance classification model trained on the combined feature space demonstrates that different features are complementary to each other and thus capable of improving the accuracy of classification. PMID:25050396

Xu, Ying-Ying; Shen, Hong-Bin

2014-01-01

324

Improving pit-pattern classification of endoscopy images by a combination of experts.  

PubMed

The diagnosis of colorectal cancer is usually supported by a staging system, such as the Duke or TNM system. In this work we discuss computer-aided pit-pattern classification of surface structures observed during high-magnification colonoscopy in order to support dignity assessment of colonic polyps. This is considered a quite promising approach because it allows in vivo staging of colorectal lesions. Since recent research work has shown that the characteristic surface structures of the colon mucosa exhibit texture characteristics, we employ a set of texture image features in the wavelet-domain and propose a novel classifier combination approach which is similar to a combination of experts. The experimental results of our work show superior classification performance compared to previous approaches on both a two-class (non-neoplastic vs. neoplastic) and a more complicated six-class (pit-pattern) classification problem. PMID:20425994

Häfner, Michael; Gangl, Alfred; Kwitt, Roland; Uhl, Andreas; Vécsei, Andreas; Wrba, Friedrich

2009-01-01

325

Valles Marineris cloud trails  

NASA Astrophysics Data System (ADS)

Distinctive cloud trails are identified in Mars Reconnaissance Orbiter Mars Color Imager (MARCI) images over specific locations associated with Valles Marineris and Noctis Labyrinthus and at perihelion solar longitudes (LS = 230°-260°). High-contrast surface shadows are well defined, as cast from their eastern margins, supporting altitude and optical depth determinations. These relatively high altitude clouds (40-50 km) exhibit narrow latitudinal widths (25-75 km) in comparison to extended longitudinal dimensions (400-1000 km). MARCI multispectral imaging of cloud surface shadows in five wavelength channels (260, 320, 437, 546, and 653 nm) yields the wavelength dependence of cloud extinction optical depth, revealing a range of small cloud particle sizes (reff = 0.2-0.5 ?m) and moderate cloud optical depths (0.03-0.10 visible and 0.1-0.2 ultraviolet). Local time and temporal sampling characteristics of MARCI cloud images indicate that these clouds develop very rapidly in afternoon hours (1300-1500 LT), reach their full longitudinal extents within <2 h time scales, and often reoccur on successive afternoons. Mars Global Surveyor Mars Orbital Camera imaging in previous Mars years indicates these clouds are annually repeating. These observed characteristics suggest a cloud formation mechanism that is specific to ˜50 km horizontal and vertical scales, transports water vapor and dust upward from lower levels, exists during the afternoon, and is likely associated with the mesoscale atmospheric circulations induced by the near-equatorial canyons of Mars. Cloud particles formed in such updrafts would then be rapidly transported westward in the strong retrograde zonal circulation of the subsolar middle atmosphere in this season.

Clancy, R. Todd; Wolff, Michael J.; Cantor, Bruce A.; Malin, Michael C.; Michaels, Timothy I.

2009-11-01

326

A sparse representation-based algorithm for pattern localization in brain imaging data analysis.  

PubMed

Considering the two-class classification problem in brain imaging data analysis, we propose a sparse representation-based multi-variate pattern analysis (MVPA) algorithm to localize brain activation patterns corresponding to different stimulus classes/brain states respectively. Feature selection can be modeled as a sparse representation (or sparse regression) problem. Such technique has been successfully applied to voxel selection in fMRI data analysis. However, single selection based on sparse representation or other methods is prone to obtain a subset of the most informative features rather than all. Herein, our proposed algorithm recursively eliminates informative features selected by a sparse regression method until the decoding accuracy based on the remaining features drops to a threshold close to chance level. In this way, the resultant feature set including all the identified features is expected to involve all the informative features for discrimination. According to the signs of the sparse regression weights, these selected features are separated into two sets corresponding to two stimulus classes/brain states. Next, in order to remove irrelevant/noisy features in the two selected feature sets, we perform a nonparametric permutation test at the individual subject level or the group level. In data analysis, we verified our algorithm with a toy data set and an intrinsic signal optical imaging data set. The results show that our algorithm has accurately localized two class-related patterns. As an application example, we used our algorithm on a functional magnetic resonance imaging (fMRI) data set. Two sets of informative voxels, corresponding to two semantic categories (i.e., "old people" and "young people"), respectively, are obtained in the human brain. PMID:23227167

Li, Yuanqing; Long, Jinyi; He, Lin; Lu, Haidong; Gu, Zhenghui; Sun, Pei

2012-01-01

327

A Sparse Representation-Based Algorithm for Pattern Localization in Brain Imaging Data Analysis  

PubMed Central

Considering the two-class classification problem in brain imaging data analysis, we propose a sparse representation-based multi-variate pattern analysis (MVPA) algorithm to localize brain activation patterns corresponding to different stimulus classes/brain states respectively. Feature selection can be modeled as a sparse representation (or sparse regression) problem. Such technique has been successfully applied to voxel selection in fMRI data analysis. However, single selection based on sparse representation or other methods is prone to obtain a subset of the most informative features rather than all. Herein, our proposed algorithm recursively eliminates informative features selected by a sparse regression method until the decoding accuracy based on the remaining features drops to a threshold close to chance level. In this way, the resultant feature set including all the identified features is expected to involve all the informative features for discrimination. According to the signs of the sparse regression weights, these selected features are separated into two sets corresponding to two stimulus classes/brain states. Next, in order to remove irrelevant/noisy features in the two selected feature sets, we perform a nonparametric permutation test at the individual subject level or the group level. In data analysis, we verified our algorithm with a toy data set and an intrinsic signal optical imaging data set. The results show that our algorithm has accurately localized two class-related patterns. As an application example, we used our algorithm on a functional magnetic resonance imaging (fMRI) data set. Two sets of informative voxels, corresponding to two semantic categories (i.e., “old people” and “young people”), respectively, are obtained in the human brain. PMID:23227167

He, Lin; Lu, Haidong; Gu, Zhenghui; Sun, Pei

2012-01-01

328

New nonuniform sampling image representation method and its application in knowledge-based active pattern recognition  

NASA Astrophysics Data System (ADS)

The research of image representation method based on nonuniform sampling and the development of the foveated sensors are active research fields in recent years. We propose in this paper a nonuniform sampling image representation method based on an improved log-polar transform and apply it into the knowledge-based active pattern recognition. The novelty of our method lies in three aspects. First, compared with other nonuniform representation methods, our method provides a flexible structure between the pure nonuniform sampling and the classical uniform sampling representation and imitates the focus characteristic of human vision. The size of the areas of interest which is uniformly sampled with the highest resolution can be adjusted arbitrarily according to the knowledge of vision task and objects. Second, we proposed a knowledge-based method to decide `where to look next' based on the fovea-periphery structure. By introducing the concept of knowledge grain, knowledge of objects is organized hierarchically, from coarse to fine. We use fine grain knowledge to do the accurate pattern recognition in fovea area and use coarse grain knowledge to locate the fixation point candidates in periphery. Third, we give a general paradigm for knowledge-based active pattern recognition. Nonuniform sampling transform is imposed on the input image to obtain the fovea-periphery structure first. Then different grain of knowledge is used to solve the problems of `what it is' and `where it is` in fovea and periphery. The above procedure is repeated until no more fixation points can be found or the goal of vision task has already been reached. Experimental result in this paper demonstrates our idea to be a valid one.

Long, Fuhui; Zheng, Nanning; Jiang, Jiande

1998-07-01

329

IR Thermal Imaging Device using Photo-Patternable Temperature Sensitive Paint  

NASA Astrophysics Data System (ADS)

This paper reports an infrared-to-visible transducer array made of temperature sensitive paint (TSP) for low-cost thermal imaging application. A novel fabrication process using a photo-patternable temperature sensitive paint (PTSP) combined with an SU-8 transfer method was developed. The developped process is simpler than before, and prevents the TSP structure from plasma-induced damage and sticking across a sacrificially-etched gap. The selfsuspended structure as small as 100 pm was successfully fabricated with a large gap of 40 ?m from the substrate. The heated object of 300°C was detected with a resolution of about 0.4 mm.

Tsukamoto, T.; Wang, M.; Tanaka, S.

2014-11-01

330

Differentiation of bacterial colonies and temporal growth patterns using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Detection and identification of bacteria are important for health and safety. Hyperspectral imaging offers the potential to capture unique spectral patterns and spatial information from bacteria which can then be used to detect and differentiate bacterial species. Here, hyperspectral imaging has been used to characterize different bacterial colonies and investigate their growth over time. Six bacterial species (Pseudomonas fluorescens, Escherichia coli, Serratia marcescens, Salmonella enterica, Staphylococcus aureus, Enterobacter aerogenes) were grown on tryptic soy agar plates. Hyperspectral data were acquired immediately after, 24 hours after, and 96 hours after incubation. Spectral signatures from bacterial colonies demonstrated repeatable measurements for five out of six species. Spatial variations as well as changes in spectral signatures were observed across temporal measurements within and among species at multiple wavelengths due to strengthening or weakening reflectance signals from growing bacterial colonies based on their pigmentation. Between-class differences and within-class similarities were the most prominent in hyperspectral data collected 96 hours after incubation.

Mehrübeoglu, Mehrube; Buck, Gregory W.; Livingston, Daniel W.

2014-09-01

331

A physical retrieval of cloud liquid water over the global oceans using special sensor microwave/imager (SSM/I) observations  

NASA Astrophysics Data System (ADS)

A method of remotely sensing integrated cloud liquid water over the oceans using spaceborne passive measurements from the special sensor microwave/imager (SSM/I) is described. The technique is comprised of a simple physical model that uses the 19.35- and 37-GHz channels of the SSM/I. The most comprehensive validation to date of cloud liquid water estimated from satellites is presented. This is accomplished through a comparison to independent ground-based microwave radiometer measurements of liquid water on San Nicolas Island, over the North Sea, and on Kwajalein and Saipan Islands in the western Pacific. In areas of marine stratocumulus clouds off the coast of California a further comparison is made to liquid water inferred from advanced very high resolution radiometer (AVHRR) visible reflectance measurements. The results are also compared qualitatively with near-coincident satellite imagery and with other existing microwave methods in selected regions. These comparisons indicate that the liquid water amounts derived from the simple scheme are consistent with the ground-based measurements for nonprecipitating cloud systems in the subtropics and middle to high latitudes. The comparison in the tropics, however, was less conclusive. Nevertheless, the retrieval method appears to have general applicability over most areas of the global oceans. An observational measure of the minimum uncertainty in the retrievals is determined in a limited number of known cloud-free areas, where the liquid water amounts are found to have a low variability of 0.016 kg m-2. A simple sensitivity and error analysis suggests that the liquid water estimates have a theoretical relative error typically ranging from about 25% to near 40% depending on the atmospheric/surface conditions and on the amount of liquid water present in the cloud. For the global oceans as a whole the average cloud liquid water is determined to be about 0.08 kg m-2. The major conclusion of this paper is that reasonably accurate amounts of cloud liquid water can be retrieved from SSM/I observations for nonprecipitating cloud systems, particularly in areas of persistent stratocumulus clouds, with less accurate retrievals in tropical regions.

Greenwald, Thomas J.; Stephens, Graeme L.; Vonder Haar, Thomas H.; Jackson, Darren L.

1993-10-01

332

Fundamental remote sensing science research program. Part 1: Status report of the mathematical pattern recognition and image analysis project  

NASA Technical Reports Server (NTRS)

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of the Earth from remotely sensed measurement of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inference about the Earth.

Heydorn, R. D.

1984-01-01

333

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns  

NASA Astrophysics Data System (ADS)

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Oliveira, D. L. L.; Nascimento, M. Z.; Neves, L. A.; Batista, V. R.; Godoy, M. F.; Jacomini, R. S.; Duarte, Y. A. S.; Arruda, P. F. F.; Neto, D. S.

2014-03-01

334

Hohlraum Target Alignment from X-ray Detector Images using Starburst Design Patterns  

SciTech Connect

National Ignition Facility (NIF) is a high-energy laser facility comprised of 192 laser beams focused with enough power and precision on a hydrogen-filled spherical, cryogenic target to initiate a fusion reaction. The target container, or hohlraum, must be accurately aligned to an x-ray imaging system to allow careful monitoring of the frozen fuel layer in the target. To achieve alignment, x-ray images are acquired through starburst-shaped windows cut into opposite sides of the hohlraum. When the hohlraum is in alignment, the starburst pattern pairs match nearly exactly and allow a clear view of the ice layer formation on the edge of the target capsule. During the alignment process, x-ray image analysis is applied to determine the direction and magnitude of adjustment required. X-ray detector and source are moved in concert during the alignment process. The automated pointing alignment system described here is both accurate and efficient. In this paper, we describe the control and associated image processing that enables automation of the starburst pointing alignment.

Leach, R R; Conder, A; Edwards, O; Kroll, J; Kozioziemski, B; Mapoles, E; McGuigan, D; Wilhelmsen, K

2010-12-14

335

How bees discriminate a pattern of two colours from its mirror image.  

PubMed

A century ago, in his study of colour vision in the honeybee (Apis mellifera), Karl von Frisch showed that bees distinguish between a disc that is half yellow, half blue, and a mirror image of the same. Although his inference of colour vision in this example has been accepted, some discrepancies have prompted a new investigation of the detection of polarity in coloured patterns. In new experiments, bees restricted to their blue and green receptors by exclusion of ultraviolet could learn patterns of this type if they displayed a difference in green contrast between the two colours. Patterns with no green contrast required an additional vertical black line as a landmark. Tests of the trained bees revealed that they had learned two inputs; a measure and the retinotopic position of blue with large field tonic detectors, and the measure and position of a vertical edge or line with small-field phasic green detectors. The angle between these two was measured. This simple combination was detected wherever it occurred in many patterns, fitting the definition of an algorithm, which is defined as a method of processing data. As long as they excited blue receptors, colours could be any colour to human eyes, even white. The blue area cue could be separated from the green receptor modulation by as much as 50°. When some blue content was not available, the bees learned two measures of the modulation of the green receptors at widely separated vertical edges, and the angle between them. There was no evidence that the bees reconstructed the lay-out of the pattern or detected a tonic input to the green receptors. PMID:25617892

Horridge, Adrian

2015-01-01

336

How Bees Discriminate a Pattern of Two Colours from Its Mirror Image  

PubMed Central

A century ago, in his study of colour vision in the honeybee (Apis mellifera), Karl von Frisch showed that bees distinguish between a disc that is half yellow, half blue, and a mirror image of the same. Although his inference of colour vision in this example has been accepted, some discrepancies have prompted a new investigation of the detection of polarity in coloured patterns. In new experiments, bees restricted to their blue and green receptors by exclusion of ultraviolet could learn patterns of this type if they displayed a difference in green contrast between the two colours. Patterns with no green contrast required an additional vertical black line as a landmark. Tests of the trained bees revealed that they had learned two inputs; a measure and the retinotopic position of blue with large field tonic detectors, and the measure and position of a vertical edge or line with small-field phasic green detectors. The angle between these two was measured. This simple combination was detected wherever it occurred in many patterns, fitting the definition of an algorithm, which is defined as a method of processing data. As long as they excited blue receptors, colours could be any colour to human eyes, even white. The blue area cue could be separated from the green receptor modulation by as much as 50°. When some blue content was not available, the bees learned two measures of the modulation of the green receptors at widely separated vertical edges, and the angle between them. There was no evidence that the bees reconstructed the lay-out of the pattern or detected a tonic input to the green receptors. PMID:25617892

Horridge, Adrian

2015-01-01

337

Quantifying radiographic image quality improvement (POD) by reducing grain diffraction patterns  

SciTech Connect

Grain diffraction patterns in radiographs of castings have been observed for at least several decades. The 1959 NDT Handbook says this, Mottling (diffraction patterns) due to x-ray diffraction is occasionally encountered. (...in thin sections with large grain structure). Today, with increased radiography of thin sections and more importantly larger grain structure alloys, diffraction (mottling) is seen more frequently and is complicating radiographic interpretation. Therefore, mottling has increased proportionally in importance. Since radiographic NDT uses polychromatic x-ray, it is this ``very complicated`` pattern the authors are trying to reduce in this paper. To reduce the pattern, the equation give {lambda} (wavelength) and d (distance between planes) as the only control variables. Since d is given, {lambda} must be used to avoid (reduce) diffraction patterns. ``Mottling due to diffraction can be reduced and in some cases eliminated by raising kV (shortening {lambda})``. ...filtering the beam may be necessary to reduce wavelength enough. By reducing wavelength, the radiographic contrast is reduced. Required radiographic sensitivity may be lost. They propose as a solution using ultrafine grain film with very high contrast at density 3+ (if needed). System contrast is a function of the exposing x-ray wavelength and to instantaneous gradient of the film at the density of radiograph. A good approximation is given by: Contrast (System) = Contrast (Part) {times} Contrast (Film). Additionally, as shown in a previous talk, a sharper image (hi-res film) allows lower contrast for equal EPS perception. This lead to the choice, NDT 30. While very slow, they are using high kV. High kV increases tube output (mr/sec.) as well as the well known penetrability. The exposure using NDT 30 is thus actually shorter.

Aman, J.K.; Trapp, L.F. [DuPont NDT Systems, Chadds Ford, PA (United States)

1993-12-31

338

Analysis of dual polarization images of precipitating clouds collected by the COSMO SkyMed constellation  

NASA Astrophysics Data System (ADS)

Currently, several satellite missions are employing X-band synthetic aperture radars (SAR) with polarimetric capabilities. In images collected over land by X-band SAR, precipitation results mainly in evident attenuation of the surface returns. Effects of precipitation in polarimetric SAR images and how to exploit them for precipitation studies are emerging topics of interest. This paper investigates polarimetric signatures of precipitation in images collected by the X-band SARs of the Italian Space Agency COSMO SkyMed constellation using the HH-VV alternate polarimetric mode. Analyzed images were collected in 2010 when the constellation was composed of three satellites and operated in the “tandem like” interferometric configuration, which allowed acquisition of the same scene with the same viewing geometry and a minimum decorrelation time of one day. Observations collected in Piedmont (Italy) and Tampa Bay (Florida, US) have been analyzed along with coincident observations collected by operational weather radars, used to reconstruct the component of SAR returns due to precipitation at horizontal and vertical polarization states. Different techniques are used depending on the different characteristics of terrestrial radars. SAR observations reconstructed from terrestrial measurements are in fairly good agreement with actual SAR observations. Results confirm that the attenuation signature in SAR images collected over land is particularly pronounced in the presence of precipitation cells and can be related to the radar reflectivity integrated along the same path. The difference between copolar HH and VV power measurements reveals a differential attenuation due to anisotropy of precipitation, whose range is limited when the SAR incidence angle is low. A specific feature observed in the CosmoSkyMed alternate polarization implementation is the presence of the scalloping effect, a periodic effect along the azimuth direction that cannot always be removed by standard de-scalloping techniques. Amplitude of scalloping between the two polarizations can reach a couple of decibels, close to the maximum range of differential path integrated attenuation.

Baldini, Luca; Roberto, Nicoletta; Gorgucci, Eugenio; Fritz, Jason; Chandrasekar, V.

2014-07-01

339

Feature reduction for improved recognition of subcellular location patterns in fluorescence microscope images  

NASA Astrophysics Data System (ADS)

The central goal of proteomics is to clarify the mechanism by which each protein in a given cell type carries out its function. Automated protein subcellular location determination by fluorescence microscopy can play an important role in fulfilling this goal. The subcellular location of a protein is critical to understanding its function because each subcellular compartment has a unique biochemical environment. We have previously shown that neural network classifiers using sets of numerical features computed from fluorescence microscope images were able to recognize all major subcellular location patterns with reasonable accuracy. Current classifiers are limited by under-determined classification boundaries due to the limited number of available images compared to the number of features. In this paper, we compare various feature reduction methods that can address this problem. Specifically, principal component analysis, kernel principal component analysis, nonlinear principal component analysis, independent component analysis, classification trees, fractal dimensionality reduction, stepwise discriminant analysis, and genetic algorithms are used to select feature subsets that are evaluated using support vector machine classifiers. The best results were obtained using stepwise discriminant analysis and we found that as few as eight features can provide good classification accuracy for all major subcellular patterns in HeLa cells.

Huang, Kai; Velliste, Meel; Murphy, Robert F.

2003-06-01

340

Voltage-Sensitive Dyes And Imaging Techniques Reveal New Patterns Of Electrical Activity In Heart Cortex  

NASA Astrophysics Data System (ADS)

Voltage-sensitive dyes bind to the plasms membrane of excitable cells (ie., muscle or nerve cells) and exhibit fluorescence and/or absorption changes that vary linearly with changes in transmembrane electrical potential. These potentiometric optical probes can be used to measure local changes in transmembrane potential by monitoring optical signals from dye molecules bound to the surface membrane. Consequently, when excitable cells are stained with such a dye and are stimulated to fire an electrical impulse (ie., an action potential (AP)), the changes in dye fluorescence have the characteristic shape and time course of APs recorded with an intracellular micro-electrode. Potentiometric dyes in conjuction with imaging techniques can now be used to visualize complex patterns and propagation of electrical activity. With photodiode arrays on video imaging techniques, patterns of biological electrical activity can be obtained with high temporal and spatial resolution which could not be obtained by conventional micro-electrodes. These methods reveal new details and offer powerful approaches to study fundamental problem in cardiac electrophysiology, communication in nerve networks, and the organization of cortical neurons.

Salama, Guy

1988-04-01

341

WSRT HI imaging of ultra-compact high velocity clouds: gas-bearing dark matter minihalos?  

NASA Astrophysics Data System (ADS)

A long standing problem in cosmology is the mismatch between the number of low mass dark matter halos predicted by simulations and the number of low mass galaxies observed in the Local Volume. We recently presented a set of isolated ultra-compact high velocity clouds (UCHVCs) identified within the dataset of the Arecibo Legacy Fast ALFA (ALFALFA) HI line survey that are consistent with representing low-mass gas-bearing dark matter halos within the Local Volume (Adams+ 2013). At distances of ~1 Mpc, the UCHVCs have HI masses of ~10^5 Msun and indicative dynamical masses of 10^7-10^8 Msun. The HI diameters of the UCHVCs range from 4' to 20', or 1 to 6 kpc at a distance of 1 Mpc.We have selected the most compact and isolated UCHVCs with the highest average column densities as representing the best galaxy candidates. These systems have been observed with the Westerbork Synthesis Radio Telescope (WSRT) to enable higher spatial resolution (~60") studies of the HI distribution. The HI morphology revealed by the WSRT data offers clues to the environment and origin of the UCHVCs, the kinematics of the HI allow the underlying mass distribution to be constrained, and the combination of spatial and spectral resolution allow the detection of a cold neutral medium component to the HI. The WSRT HI observations discriminate among the selected galaxy candidates for those objects that are most likely gas-bearing dark matter halos.One UCHVC, AGC198606, is of particular interest as it is located 16 km/s and 1.2 degrees from Leo T and has similar HI properties within the ALFALFA dataset. The WSRT HI observations reveal a smooth HI morphology and a velocity gradient along the HI major axis of the system consistent with rotation. These properties are consistent with the hypothesis that this object is a gas-bearing low-mass dark matter halo.

Adams, Elizabeth A.; Oosterloo, Tom; Giovanelli, Riccardo; Haynes, Martha P.; Cannon, John M.; Faerman, Yakov; Janesh, William; Janowiecki, Steven; Munoz, Ricardo; Rhode, Katherine L.; Salzer, John Joseph; Sternberg, Amiel

2015-01-01

342

A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus  

NASA Technical Reports Server (NTRS)

The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary constraints for this particular problem are that the method must be reasonably robust and fast. Unlike most geological features, the small volcanoes of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include (1) a circular planimetric outline, (2) known diameter frequency distribution from preliminary studies, (3) a limited number of basic morphological shapes, and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Burl, M. C.; Fayyad, U. M.; Smyth, P.; Aubele, J. C.; Crumpler, L. S.

1993-01-01

343

Stratus cloud structure from MM-radar transects and satellite images: scaling properties and artifact detection with semi-discrete wavelet analysis  

SciTech Connect

Spatial and/or temporal variabilities of clouds is of paramount importance for at least two in tensely researched sub-problems in global and regional climate modeling: (1) cloud-radiation interaction where correlations can trigger 3D radiative transfer effects; and (2) dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets as a simple yet powerful way of quantifying cloud variability. More precisely, we use 'semi-discrete' wavelet transforms which, at least in the present statistical applications, have advantages over both its continuous and discrete counterparts found in the bulk of the wavelet literature. With the particular choice of normalization we adopt, the scale-dependence of the variance of the wavelet coefficients (i.e,, the wavelet energy spectrum) is always a better discriminator of transition from 'stationary' to 'nonstationary' behavior than conventional methods based on auto-correlation analysis, second-order structure function (a.k.a. the semi-variogram), or Fourier analysis. Indeed, the classic statistics go at best from monotonically scale- or wavenumber-dependent to flat at such a transition; by contrast, the wavelet spectrum changes the sign of its derivative with respect to scale. We apply 1D and 2D semi-discrete wavelet transforms to remote sensing data on cloud structure from two sources: (1) an upward-looking milli-meter cloud radar (MMCR) at DOE's climate observation site in Oklahoma deployed as part of the Atmospheric Radiation Measurement (ARM) Progrm; and (2) DOE's Multispectral Thermal Imager (MTI), a high-resolution space-borne instrument in sunsynchronous orbit that is described in sufficient detail for our present purposes by Weber et al. (1999). For each type of data, we have at least one theoretical prediction - with empirical validation already in existence - for a power-law relation for wavelet statistics with respect to scale. This is what is expected in physical (i.e., finite scaling range) fractal phenomena. In particular, we find long-range correlations in cloud structure coming from the important nonstationary regime. More surprisingly, we also uncover artifacts the data that are traceable either to instrumental noise (in the satellite data) or to smoothing assumptions (in the MMCR data processing). Finally, we discuss the potentially damaging ramifications the smoothing artifact can have on both cloud-radiation and cloud-modeling studies using MMCR data.

Davis, A. B. (Anthony B.); Petrov, N. P. (Nikola P.); Clothiaux, E. E. (Eugene E.); Marshak, A. (Alexander)

2002-01-01

344

Quantitative imaging of protein adsorption on patterned organic thin-film arrays using secondary electron emission.  

PubMed

Secondary electron emission is developed as a means to quantify and image protein binding to Au surfaces modified with patterned organic thin-film arrays. Alkane thiols were patterned via microcontact printing on gold, and their effects on the secondary electron (SE) yield of the surface, systematically quantified. We show that a self-assembled monolayer (SAM) of hexadecane thiol significantly increases the SE yield over the native gold surface, a yield that increases as a function of alkane chain length (C8-C16). This effect is linearly correlated with the surface potentials and wetting properties of these SAMs. Surface layers comprised of poly(ethylene glycol) (PEG) grafted polyacrylamide polymers behave differently, affecting the SE yield by attenuation according to the polymer thickness. These results demonstrate the relative contributions of factors related to the adsorbate molecular structures that serve to strongly mediate the SE yield, providing a foundation for exploiting them as a quantitative electron imaging probe. The latter capability is demonstrated using a model microfluidic assay in which a series of proteins was spatially addressed to a SAM-based pixel array. The gray scale contrasts seen with protein adsorption are directly correlated with both protein molecular weight and mass coverage. These methods are used in two model protein assay experiments: (1) the measurement of the concentration dependent adsorption isotherm for a model protein (fibrinogen); and (2) the selective recognition of a biotinylated protein layer by avidin. These results demonstrate a unique approach to imaging protein binding processes on surfaces with both high analytical and spatial sensitivity. PMID:16771500

Mack, Nathan H; Dong, Rui; Nuzzo, Ralph G

2006-06-21

345

Surface reflectivity from the Ozone Monitoring Instrument using the Moderate Resolution Imaging Spectroradiometer to eliminate clouds: Effects of snow on ultraviolet and visible trace gas retrievals  

Microsoft Academic Search

Satellite retrievals of tropospheric composition from measurements of solar backscatter require accurate information about surface reflectivity. We use clear-sky data from the Ozone Monitoring Instrument (OMI) to determine global surface reflectivity under both snow-covered and snow-free conditions at 354 nm. Clear-sky scenes are determined using cloud and aerosol data from the Moderate Resolution Imaging Spectroradiometer\\/Aqua satellite instrument that flies 12

G. O'Byrne; R. V. Martin; A. van Donkelaar; J. Joiner; E. A. Celarier

2010-01-01

346

Image workstation in a medical intensive care unit changes viewing patterns and timing of image-based clinical actions in routine portable chest radiographs  

NASA Astrophysics Data System (ADS)

In order to determine the effect of an image workstation, viewing patterns and related clinical actions were evaluated in a randomized prospective study. During 16 weeks of Computed Radiography data collection, an image workstation was conveniently available to the Medical Intensive Care Unit clinicians. The workstation was not available for clinical use during 16 weeks of Analog Film data collection. Viewing patterns were evaluated by comparing viewing times. Patient care was evaluated by comparing the time of performing image based clinical actions. The percentage of routine exams viewed before AM Radiology Conference increased from 0% during the Analog Periods to 27% during the CR PACS Periods. Clinicians selected images taken during the first few days of the patient's admission for viewing before conference. Images taken later in admission were viewed during or after conference. On days when radiology conference was not held, images were viewed significantly earlier when the workstation was available. Clinical actions based on images viewed on the workstation were performed significantly earlier. When an image workstation was available routine images were viewed sooner and image based actions occurred earlier.

Redfern, Regina O.; Kundel, Harold L.; Polansky, Marcia; Langlotz, Curtis P.; Lanken, Paul N.; Brikman, Inna; Horii, Steven C.; Bozzo, Mary T.; Feingold, Eric R.; Nodine, Calvin F.

1996-05-01

347

Integrating Remote Sensing Data, Hybrid-Cloud Computing, and Event Notifications for Advanced Rapid Imaging & Analysis (Invited)  

NASA Astrophysics Data System (ADS)

Space-based geodetic measurement techniques such as Interferometric Synthetic Aperture Radar (InSAR) and Continuous Global Positioning System (CGPS) are now important elements in our toolset for monitoring earthquake-generating faults, volcanic eruptions, hurricane damage, landslides, reservoir subsidence, and other natural and man-made hazards. Geodetic imaging's unique ability to capture surface deformation with high spatial and temporal resolution has revolutionized both earthquake science and volcanology. Continuous monitoring of surface deformation and surface change before, during, and after natural hazards improves decision-making from better forecasts, increased situational awareness, and more informed recovery. However, analyses of InSAR and GPS data sets are currently handcrafted following events and are not generated rapidly and reliably enough for use in operational response to natural disasters. Additionally, the sheer data volumes needed to handle a continuous stream of InSAR data sets also presents a bottleneck. It has been estimated that continuous processing of InSAR coverage of California alone over 3-years would reach PB-scale data volumes. Our Advanced Rapid Imaging and Analysis for Monitoring Hazards (ARIA-MH) science data system enables both science and decision-making communities to monitor areas of interest with derived geodetic data products via seamless data preparation, processing, discovery, and access. We will present our findings on the use of hybrid-cloud computing to improve the timely processing and delivery of geodetic data products, integrating event notifications from USGS to improve the timely processing for response, as well as providing browse results for quick looks with other tools for integrative analysis.

Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Fielding, E. J.; Agram, P.; Manipon, G.; Stough, T. M.; Simons, M.; Rosen, P. A.; Wilson, B. D.; Poland, M. P.; Cervelli, P. F.; Cruz, J.

2013-12-01

348

The detection of weak signal patterns in radar ocean intensity images  

SciTech Connect

Detection of weak patterns in radar ocean RCS images is complicated by the fact that signals and noise are interactive rather than additive and the ambient noise background is non Gaussian or even strongly non Gaussian at low grazing angles. This paper addresses this difficult problem with the aid of two simplifying assumptions: (1) the signal modulation is weak, and (2) departure from Gaussianity is small. In situations where this departure is large, an approach is suggested for reducing this non Gaussianity. The relevant weak signal detection theory, based on the Likelihood ratio, is reviewed and adapted for use in the analysis. The approach to this problem, similar to that previously used for complex images, is facilitated by approximating the multivariate probability distributions as a composite integral involving underlying processes which are assumed to be Gaussian. This formulation, subject to the approximations in the analysis, permits derivation of an ideal detection statistic (which determines the form of optimum receiver) and a signal/noise ratio which characterizes detection performance in the weak signal limit. Implications for image processing are discussed and directions for future analysis are suggested.

Manasse, R.

1996-06-15

349

Martian Clouds Pass By on a Winter Afternoon  

NASA Technical Reports Server (NTRS)

NASA's Mars Exploration Rover Opportunity captured a view of wispy afternoon clouds, not unlike fair weather clouds on Earth, passing overhead on the rover's 956th sol, or Martian day (Oct. 2, 2006). With Opportunity facing northeast, the clouds appear to drift gently toward the west in this movie taken with the rover's navigation camera.

The 10 frames, taken 32 seconds apart, show the formation and evolution of what are likely mid-level, convective water clouds. Such clouds are common near Mars' equator at this time of the Martian year. They have been observed by both of NASA's Mars Exploration Rovers, by satellites orbiting Mars, and by the Hubble Space Telescope. In this case, the clouds appear to develop at a fixed location, in the center of the frame about 25 degrees above the horizon. This style of origin suggests that a thermal plume is rising over a surface feature. In spite of apparent winds aloft, the thermal plume appears to remain stationary for the 5-minute duration of the movie.

Though scientists have determined from the images that the wind bearing is east-northeast, approximately 80 degrees, it is not possible on the basis of the movie to unambiguously determine the height and speed of the clouds. Scientists estimate, based on models of atmospheric wind profiles and the apparent displacement of the clouds, that all of the clouds in the movie are at about the same height somewhere between 5 kilometers and 25 kilometers (3 to 20 miles) above the surface. The clouds are estimated to be moving at 2.5 meters per second, if they are low, to 12.5 meters per second, if they are high (8 feet per second to 41 feet per second).

Like clouds on Earth, these Martian clouds are probably composed of ice crystals and possibly supercooled water droplets. They are similar in appearance to terrestrial cirrocumulus or high altocumulus clouds. On Earth, such clouds are relatively transient and consist of small, individual cloudlets arranged in rippled patterns. They usually form 6 kilometers to 12 kilometers (4 to 7 miles) above Earth's surface by a process known as convection, during which warm air rises and cools, with clouds condensing from the moist air once it has cooled sufficiently.

These Martian clouds appear to be associated with a broader layer of ice-crystal clouds fanning out toward the upper right of the frames at the end of the movie. This is similar to the occurrence of terrestrial cirrocumulus and altocumulus clouds within layers of cirrus or cirrostratus clouds on Earth. Also apparent in this movie are prominent waves in the clouds, a result of the effect of gravity waves on cloud thickness, as on Earth.

Though both rovers now have the ability to autonomously detect clouds, these images were taken prior to the first use of the new abilities. The images shown here were stored on Opportunity and were transmitted to Earth on sol 1056 (Jan. 12, 2007) during a routine communications pass.

2007-01-01

350

Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States  

USGS Publications Warehouse

A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image). These detected cloud and shadow areas are further refined using an integration process and a false shadow removal process according to the geometric relationship between cloud and shadow. Cloud and shadow filling is based on the concept of the Spectral Similarity Group (SSG), which uses the reference image to find similar alternative pixels in the target image to serve as replacement values for restored areas. Pixels are considered to belong to one SSG if the pixel values from Landsat bands 3, 4, and 5 in the reference image are within the same spectral ranges. This new approach was applied to five Landsat path/rows across different landscapes and seasons with various types of cloud patterns. Results show that almost all of the clouds were captured with minimal commission errors, and shadows were detected reasonably well. Among five test scenes, the lowest producer's accuracy of cloud detection was 93.9% and the lowest user's accuracy was 89%. The overall cloud and shadow detection accuracy ranged from 83.6% to 99.3%. The pixel-filling approach resulted in a new cloud-free image that appears seamless and spatially continuous despite differences in phenology between the target and reference images. Our methods offer a straightforward and robust approach for preparing images for the new 2011 National Land Cover Database production.

Jin, Suming; Homer, Collin; Yang, Limin; Xian, George; Fry, Joyce; Danielson, Patrick; Townsend, Philip A.

2013-01-01

351

Neptune's cloud structure in 1989 - Photometric variations and correlation with ground-based images  

NASA Astrophysics Data System (ADS)

Ground-based photoelectric photometry in b, y, and the 6190 and 7250 A methane-bands, as well as spectrum scans of the methane 6190 A band and CCD images at 6190 and 8900 A, were obtained for Neptune during Voyager 2's approach of that planet on August 24, 1989. Photometric variations are presently correlated with the disk transit of bright planetary features, and the changes in feature distribution and brightness noted in the results are evaluated for implications bearing on long-term variability. It is suggested that the long-term secular variation is related to a slow change in a size of location of both the bright companion and the Great Dark Spot.

Lockwood, G. W.; Thompson, D. T.; Hammel, H. B.; Birch, P.; Candy, M.

1991-04-01

352

AUTOMATIC FEATURE MATCHING BETWEEN DIGITAL IMAGES AND 2D REPRESENTATIONS OF A 3D LASER SCANNER POINT CLOUD  

E-print Network

the computation of the relative orientation of a photo to a dense 3D point cloud from point correspondences using POINT CLOUD N. Meierhold a, *, M. Spehrb , A. Schilling a , S. Gumholdb , H.-G. Maasa a Technische, SMT, Department for Computer Sciences ­ (Marcel.Spehr, Stefan.Gumhold)@tu-dresden.de Commission V, WG

Gumhold, Stefan

353

Parkinson's disease-related perfusion and glucose metabolic brain patterns identified with PCASL-MRI and FDG-PET imaging  

PubMed Central

Introduction Under normal conditions, the spatial distribution of resting cerebral blood flow and cerebral metabolic rate of glucose are closely related. A relatively new magnetic resonance (MR) technique, pseudo-continuous arterial spin labeling (PCASL), can be used to measure regional brain perfusion. We identified a Parkinson's disease (PD)-related perfusion and metabolic covariance pattern in the same patients using PCASL and FDG-PET imaging and assessed (dis)similarities in the disease-related pattern between perfusion and metabolism in PD patients. Methods Nineteen PD patients and seventeen healthy controls underwent [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) imaging. Of 14 PD patients and all healthy controls PCASL-MRI could be obtained. Data were analyzed using scaled subprofile model/principal component analysis (SSM/PCA). Results Unique Parkinson's disease-related perfusion and metabolic covariance patterns were identified using PCASL and FDG-PET in the same patients. The PD-related metabolic covariance brain pattern is in high accordance with previously reports. Also our disease-related perfusion pattern is comparable to the earlier described perfusion pattern. The most marked difference between our perfusion and metabolic patterns is the larger perfusion decrease in cortical regions including the insula. Conclusion We identified PD-related perfusion and metabolic brain patterns using PCASL and FDG-PET in the same patients which were comparable with results of existing research. In this respect, PCASL appears to be a promising addition in the early diagnosis of individual parkinsonian patients. PMID:25068113

Teune, Laura K.; Renken, Remco J.; de Jong, Bauke M.; Willemsen, Antoon T.; van Osch, Matthias J.; Roerdink, Jos B.T.M.; Dierckx, Rudi A.; Leenders, Klaus L.

2014-01-01

354

Frequency-based image analysis of random patterns: an alternative way to classical stereocorrelation  

E-print Network

The paper presents an alternative way to classical stereocorrelation. First, 2D image processing of random patterns is described. Sub-pixel displacements are determined using phase analysis. Then distortion evaluation is presented. The distortion is identified without any assumption on the lens model because of the use of a grid technique approach. Last, shape measurement and shape variation is caught by fringe projection. Analysis is based on two pin-hole assumptions for the video-projector and the camera. Then, fringe projection is coupled to in-plane displacement to give rise to 3D measurement set-up. Metrological characterization shows a resolution comparable to classical (stereo) correlation technique (1/100th pixel). Spatial resolution seems to be an advantage of the method, because of the use of temporal phase stepping (shape measurement, 1 pixel) and windowed Fourier transform (in plane displacements measurement, 9 pixels). Two examples are given. First one is the study of skin properties; second one ...

Molimard, Jérôme; Zahouani, Hassan

2013-01-01

355

Water Ice Clouds over the Northern Plains  

NASA Technical Reports Server (NTRS)

(Released 14 May 2002) The Science This image, centered near 48.5 N and 240.5 W, displays splotchy water ice clouds that obscure the northern lowland plains in the region where the Viking 2 spacecraft landed. This image is far enough north to catch the edge of the north polar hood that develops during the northern winter. This is a cap of water and carbon dioxide ice clouds that form over the Martian north pole. As Mars progresses into northern spring, the persistent north polar hood ice clouds will dissipate and the surface viewing conditions will improve greatly. As the season develops, an equatorial belt of water ice clouds will form. This belt of water ice clouds is as characteristic of the Martian climate as the southern hemisphere summer dust storm season. Seasons on Mars have a dramatic effect on the state of the dynamic Martian atmosphere. The Story Muted in an almost air-brushed manner, this image doesn't have the crispness that most THEMIS images have. That's because clouds were rising over the surface of the red planet on the day this picture was taken. Finding clouds on Mars might remind us of conditions here on Earth, but these Martian clouds are made of frozen water and frozen carbon dioxide -- in other words, clouds of ice and 'dry ice.' Strange as that may sound, the clouds seen here form on a pretty regular basis at the north Martian pole during its winter season. As springtime comes to the northern hemisphere of Mars (and fall comes to the southern), these clouds will slowly disappear, and a nice belt of water ice clouds will form around the equator. So, if you were a THEMIS camera aimer, that might tell you when your best viewing conditions for different areas on Mars would be. As interesting as clear pictures of Martian landforms are, however, you wouldn't want to bypass the weather altogether. Pictures showing seasonal shifts are great for scientists to study, because they reveal a lot about the patterns of the Martian climate and the circulation of the atmosphere. There are a lot of interesting global climate relationships to study. For example, when it's winter in the north of Mars and clouds like the ones in this image form, dust storms rage in the south of Mars, where it's summer. So why does Mars have these wild seasons? Like the Earth, Mars is tilted on its axis. As it travels in its orbit around the sun, the angle between the Earth's axis and the Earth-Sun line changes. That's true for Mars as well. As each point on Mars spins on the rotating red planet each day, the part of the cycle spent in sunlight (day) and shadow (night) just aren't equal because of these angles. When day is longer than night (summer) in the north, night is longer than day (winter) in the south. Half a year later, when Mars has traveled in its orbit to the other side of the sun, the situation is exactly reversed. All this sounds familiar to Earthlings, but there's yet one more difference. Mars is farther away from the sun than the Earth. That means it takes longer for Mars to make a trip around the sun in its orbit than the Earth does -- about twice as long, in fact. That means that the seasons on Mars also last twice as long!

2002-01-01

356

Patterns of response to visual scenes are linked to the low-level properties of the image.  

PubMed

Scene-selective regions in the brain play an important role in the way that we navigate through our visual environment. However, the principles that govern the organization of these regions are not fully understood. For example, it is not clear whether patterns of response in scene-selective regions are linked to high-level semantic category or to low-level spatial structure in scenes. To address this issue, we used multivariate pattern analysis with fMRI to compare patterns of response to different categories of scenes. Although we found distinct patterns of neural response to each category of scene, the magnitude of the within-category similarity varied across different scenes. To determine whether this variation in the categorical response to scenes could reflect variation in the low-level image properties, we measured the similarity of images from each category of scene. Although we found that the low-level properties of images from each category were more similar to each other than to other categories of scenes, we also found that the magnitude of the within-category similarity varied across different scenes. Finally, we compared variation in the neural response to different categories of scenes with corresponding variation in the low-level image properties. We found a strong positive correlation between the similarity in the patterns of neural response to different scenes and the similarity in the image properties. Together, these results suggest that categorical patterns of response to scenes are linked to the low-level properties of the images. PMID:24862072

Watson, David M; Hartley, Tom; Andrews, Timothy J

2014-10-01

357

Cloud Fun  

NSDL National Science Digital Library

Learners complete a series of hands-on and investigative activities to explore cumulus clouds. Learners observe cumulus clouds outside, read a book about how cumulus clouds differ from other clouds, and create a list of words that describe cumulus clouds. Then, learners create their own cumulus cloud out of white paper and complete the Cloud Fun Student Activity sheet that includes a description of the cloud and what the weather was like on the day the cloud was observed. Learners will use their five senses to describe their clouds. Clouds can be displayed in the classroom or assembled into a class book. This lesson guide includes brief background information about cumulus clouds, adaptations for younger and older learners, and extension ideas.

Program, The G.

2006-01-01

358

Filter-Based Classification of Training Image Patterns for Spatial Simulation  

Microsoft Academic Search

Multiple-point simulation, as opposed to simulation one point at a time, operates at the pattern level using a priori structural information. To reduce the dimensionality of the space of patterns we propose a multi-point filtersim algorithm that classifies structural patterns using selected filter statistics. The pattern filter statistics are specific linear combinations of pattern pixel values that represent directional mean,

Tuanfeng Zhang; Paul Switzer; Andre Journel

2006-01-01

359

A Mid-Infrared Imaging Survey of Embedded Young Stellar Objects in the (rho) Ophiuchi Cloud Core  

NASA Technical Reports Server (NTRS)

Results of a comprehensive, new, ground-based mid-infrared imaging survey of the young stellar population of the (rho) Ophiuchi cloud are presented. Data were acquired at the Palomar 5m and at the Keck 10m telescopes with the MIRLIN and LWS instruments, at 0'.5 and 0'.25 resolutions, respectively. Of 172 survey objects, 85 were detected. Among the 22 multiple systems observed, 15 were resolved and their individual component fluxes determined. A plot of the frequency distribution of the detected objects with SED spectral slope shows that YSOs spend approx.4 x 10(exp 5) yr in the flat-spectrum phase, clearing out their remnant infall envelopes. Mid-infrared variability is found among a significant fraction of the surveyed objects and is found to occur for all SED classes with optically thick disks. Large-amplitude near-infrared variability, also found for all SED classes with optically thick disks, seems to occur with somewhat higher frequency at the earlier evolutionary stages. Although a general trend of mid-infrared excess and near-infrared veiling exists progressing through SED classes, with Class I objects generally exhibiting r(sub K) >= 1, flat-spectrum objects with r(sub K) >= 0.58, and Class III objects with r(sub K) =0, Class II objects exhibit the widest range of r(sub K) values, ranging from 0 <= r(sub K) <= 4.5. However, the highly variable value of veiling that a single source can exhibit in any of the SED classes in which active disk accretion can take place is striking and is direct observational evidence for highly time-variable accretion activity in disks. Finally, by comparing mid-infrared versus near-infrared excesses in a subsample with well-determined effective temperatures and extinction values, disk-clearing mechanisms are explored. The results are consistent with disk clearing proceeding from the inside out.

Barsony, Mary; Ressler, Michael E.; Marsh, Kenneth A.

2005-01-01

360

Image Analysis And Pattern Recognition For Porosity Estimation From Thin Sections  

NASA Astrophysics Data System (ADS)

Estimating porosity from thin sections is one of the key steps in many different rock physics and petrologic analyses. The estimated porosity is a critical input for computing transport properties of rocks from thin sections. The porosity estimate and its uncertainty depend, amongst other things, on the image analyses techniques used. In this poster, we present the results of exploring different image analysis algorithms for estimating porosity from thin section. The general methodology for calculating porosity from thin section involves conversion of a colored image to a binary image. The average of the binary image gives us the porosity. As most thin sections use blue epoxy impregnation, the conversion to binary image requires computationally identifying pixels that are blue. One of the challenges is to capture the variability of the color value, all of which are nominally blue. We compared two different color spaces, RGB and HSV color space, which can be used to specify the blue color. Two different approaches were tried for converting the colored image in different color spaces to a binary image. The first approach involved using thresholds for conversion. A single dimension threshold based on the intensity histogram as well as a multiple dimension threshold based on (RGB) and (HSV) pixel values were explored. In general, multiple dimension thresholding in HSV space gave better results but the choice of threshold is subjective. The second approach involved statistical pattern recognition and classifying of grains and pores. We tested both discriminant analysis and neural network classification. A training data was defined using different groups of pixels from selected pore and grain regions of the thin section. The trivariate training data consists of the range of HSV values for each group (grain or pore). A misclassification error was calculated for the different classification algorithms as the fraction of the observations in the training data that are misclassified. The quadratic discriminant method seems to give the best results and least error. The misclassification error was about 12.6%. The neural network classification depends upon the residual error to be achieved. Different instantiations of the neural network give slightly different porosities for a specified residual. The variance of the estimated porosities decreases with decrease in residual error, but the trade-off is an increased bias in the estimate. This is the expected bias-variance trade-off behavior. In general, the HSV color space gave better results in specifying the blue color than the RGB color space. The multiple dimensional threshold works better than the single threshold. It also proved to be a simpler, though subjective, method than statistical discriminant analysis. Though discriminant analysis gave good results, it involved preparation of training data from the thin section, which adds to processing time. Nevertheless, it can be useful for identifying different types of grains and hence may be useful for computational methods that require not only classification of pore space but also different grain types.

Richa, R.; Mukerji, T.; Keehm, Y.; Mavko, G.

2005-12-01

361

On the fractal structure of molecular clouds  

Microsoft Academic Search

We present a new method to analyze the structure of observed molecular cloud images which is the generalization of the Allan-variance method traditionally used in the stability and drift analysis of instrumentation and electronic devices. Applied to integrated intensity maps of two molecular cloud data sets, the method shows, together with an analysis of the phases of the cloud images,

J. Stutzki; F. Bensch; A. Heithausen; V. Ossenkopf; M. Zielinsky

1998-01-01

362

A gravity wave case study for an observation over Antarctica using the cloud imaging and particle size experiment  

NASA Astrophysics Data System (ADS)

This work presents a case study using a new data set for space based observations of Gravity Waves (GW) near the stratopause. The data set uses the Cloud Imaging and Particle Size instrument (CIPS) on the Aeronomy of Ice in the Mesosphere (AIM) satellite. The CIPS instrument is a camera array with a wide field of view centered in the nadir. The instrument observes with a band pass centered at the UV wavelength of 265 nm. The GWs are observed via perturbations in the Rayleigh scattered sunlight near the stratopause. Gravity waves are the dominant driver of mesospheric dynamics and they are insufficiently constrained in global climate models. CIPS observes the GWs over much of a hemisphere at a higher altitude than similar imaging observations such as those from the Atmospheric Infrared Sounder instrument (AIRS). The sensitivity to the shorter horizontal wavelengths (~20km) compliments the GW data sets constructed from limb viewing instruments which observe near the stratopause but tend to see the GWs with longer horizontal wavelengths. A GW observed on two consecutive orbits on October 10th 2010 to the east of McMurdo station in Antarctica is presented. The dominant horizontal wavelength of this GW was approximately 150km. From the apparent phase progression between the two orbits, a ground based phase speed of 20 m/s is estimated. The GW was propagating in the upwind direction according to winds from MERRA re-analysis data. From this wind data, the intrinsic frequency of the GW is estimated, and from the dispersion relation, the vertical wavelength (~18km) is derived. Using the three dimensional wave vector, the radiative transfer of the Rayleigh scattered albedo observation is simulated and used to determine the GW amplitude. The resulting momentum flux is estimated to be approximately 10 mPa. Momentum flux is the critical measurement needed to understand the forcing by GWs on the mean flow. This momentum flux is sufficient for a local deceleration of the mean flow of approximately 200 m/s/day.

Carstens, J. N.; Bailey, S. M.; Alexander, M.; Randall, C. E.

2013-12-01

363

The effects of charge cloud size and digitisation on the SPAN anode  

Microsoft Academic Search

Microchannel plate (MCP) detectors are often used with charge division anode readouts, such as the spiral-anode (SPAN) anode, to provide high position resolution. This paper discusses the effect on image quality, of digitization (causing fixed patterning), electronic noise, pulse height distribution (PHD) and charge cloud size. The discussion is supported by experimental data obtained from a 1D SPAN anode. Results

A. A. Breeveld; M. L. Edgar; J. S. Lapington; Alan Smith

1992-01-01

364

MY NASA DATA Lesson Plan: Storm Clouds-Fly over a Late Winter Storm onboard a NASA Earth Observing Satellite  

NSDL National Science Digital Library

: This lesson plan uses Clouds and Earth's Radiant Energy System (CERES) cloud data and a weather map to explore cloud coverage during a winter storm. When atmospheric scientists, including meteorologists, study weather patterns, they may use several different sources of information. For example, in studying storm patterns, they may use a combination of Earth Observing Satellite data, such as from CERES, or NOAA weather satellite imagery, and geographical tools to determine locations and paths of storms. As one part of the training to analyze this data and imagery, scientists look at 'case studies' such as the late winter storm shown in the weather satellite imagery included with the lesson. An infrared satellite image looks at the temperature. Cold things (like high clouds) are very bright. Warm things (like Mexico and Florida) are dark. The imagery can be compared to data collected by other satellites, so that improved models of storm patterns can be developed.

2006-01-01

365

Multi-layer Clouds Over the South Indian Ocean  

NASA Technical Reports Server (NTRS)

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17794. The panels cover an area of 335 kilometers x 605 kilometers, and utilize data from blocks 142 to 145 within World Reference System-2 path 155.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

2003-01-01

366

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. XX, NO. Y, MONTH 2003 1 Image Enhancement and Denoising by  

E-print Network

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. XX, NO. Y, MONTH 2003 1 Image. Gilboa and Y.Y. Zeevi are with the Department of Electrical Engineering, Technion - Israel Institute of Technology, Tech- nion city, Haifa 32000, Israel. e-mail: gilboa@tx.technion.ac.il, zeevi@ee.technion.ac.il N

Sochen, Nir

367

Clouds of high contrast on Uranus.  

PubMed

Near-infrared images of Uranus taken with the Hubble Space Telescope in July and October 1997 revealed discrete clouds with contrasts exceeding 10 times the highest contrast observed before with other techniques. At visible wavelengths, these 10 clouds had lower contrasts than clouds seen by Voyager 2 in 1986. Uranus' rotational rates for southern latitudes were identical in 1986 and 1997. Clouds in northern latitudes rotate slightly more slowly than clouds in opposite southern latitudes. PMID:9554844

Karkoschka, E

1998-04-24

368

Mesoscale wake clouds in Skylab pictures.  

NASA Technical Reports Server (NTRS)

The recognition of cloud patterns formed in the wake of orographic obstacles was investigated using pictures from Skylab, for the purpose of estimating atmospheric motions. The existence of ship-wake-type wave clouds in contrast to vortex sheets were revealed during examination of the pictures, and an attempt was made to characterize the pattern of waves as well as the transition between waves and vortices. Examples of mesoscale cloud patterns which were analyzed photogrammetrically and meteorologically are presented.

Fujita, T. T.; Tecson, J. J.

1974-01-01

369

Mathematical Investigation of Gamma Ray and Neutron Absorption Grid Patterns for Homeland Defense Related Fourier Imaging Systems  

NASA Technical Reports Server (NTRS)

Terrorist suitcase nuclear devices typically using converted Soviet tactical nuclear warheads contain several kilograms of plutonium. This quantity of plutonium emits a significant number of gamma rays and neutrons as it undergoes radioactive decay. These gamma rays and neutrons normally penetrate ordinary matter to a significant distance. Unfortunately this penetrating quality of the radiation makes imaging with classical optics impractical. However, this radiation signature emitted by the nuclear source may be sufficient to be imaged from low-flying aerial platforms carrying Fourier imaging systems. The Fourier imaging system uses a pair of co-aligned absorption grids to measure a selected range of spatial frequencies from an object. These grids typically measure the spatial frequency in only one direction at a time. A grid pair that looks in all directions simultaneously would be an improvement over existing technology. A number of grid pairs governed by various parameters were investigated to solve this problem. By examining numerous configurations, it became apparent that an appropriate spiral pattern could be made to work. A set of equations was found to describe a grid pattern that produces straight fringes. Straight fringes represent a Fourier transform of a point source at infinity. An inverse Fourier transform of this fringe pattern would provide an accurate image (location and intensity) of a point source.

Boccio, Dona

2003-01-01

370

Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns  

PubMed Central

Background Differential gene expression patterns in cells of the mammalian brain result in the morphological, connectional, and functional diversity of cells. A wide variety of studies have shown that certain genes are expressed only in specific cell-types. Analysis of cell-type-specific gene expression patterns can provide insights into the relationship between genes, connectivity, brain regions, and cell-types. However, automated methods for identifying cell-type-specific genes are lacking to date. Results Here, we describe a set of computational methods for identifying cell-type-specific genes in the mouse brain by automated image computing of in situ hybridization (ISH) expression patterns. We applied invariant image feature descriptors to capture local gene expression information from cellular-resolution ISH images. We then built image-level representations by applying vector quantization on the image descriptors. We employed regularized learning methods for classifying genes specifically expressed in different brain cell-types. These methods can also rank image features based on their discriminative power. We used a data set of 2,872 genes from the Allen Brain Atlas in the experiments. Results showed that our methods are predictive of cell-type-specificity of genes. Our classifiers achieved AUC values of approximately 87% when the enrichment level is set to 20. In addition, we showed that the highly-ranked image features captured the relationship between cell-types. Conclusions Overall, our results showed that automated image computing methods could potentially be used to identify cell-type-specific genes in the mouse brain. PMID:24947138

2014-01-01

371

Imaging Spatial and Temporal Patterns of Landslide Movement with Ground-Based Radar Interferometry  

NASA Astrophysics Data System (ADS)

Ground-based interferometric radar (GBIR) provides a means of addressing questions about landslides that involve monitoring changes across large areas (<10 km2) with high spatial (<1 mm) and temporal precision (<1 hr). Recent studies have shown that landslide displacement rates may exhibit sensitivity to unlikely sources, such as atmospheric tides. This study applies GBIR to measure temporal and spatial patterns of movement in a slow-velocity slide on the west side of the Colorado Front Range. Multiple deployments of the GBIR permit assessing long-term (seasonal) variations in slide kinematics, which compared favorably with ground-truth measurements using more conventional surveying techniques. Each GBIR deployment involves long observation sessions (5 - 36 hours) with images acquired every 7.5 - 15 minutes. The data redundancy permits rigorous time-series analysis that results in 0.3 - 0.4 mm positional uncertainties. The time series is further constrained by imposing a 'no back-slip' condition that is justified by the nearly horizontal viewing geometry facing in the slide's direction of transport. The slide demonstrates significant seasonal variations that correspond with variations in groundwater measured by piezometric wells in the study area. These are primarily driven by variations in spring snow melt and precipitation. Additionally, short-span time series for individual observation sessions suggest short term variations in displacement rate over periods of several hours. One possible model for this quasi stick-slip behavior may involve release of excess fluid pressure during slide movement that increases frictional coupling at the base of the slide. As a tool for geodetic imaging, offers a significant improvement in temporal and spatial resolution compared with satellite and airborne radar interferometry. The sensitivity and temporal sampling of GBIR complement well the spatial resolution and 3-dimensional displacements measured with other methods, such as terrestrial laser scanners.

Gomez, F.; Held, B. M.; Lowry, B. W.; Mooney, M.; Zhou, W.; Grasmick, J.

2012-12-01

372

Application of the mean intensity of the second derivative in evaluating the speckle patterns in digital image correlation  

NASA Astrophysics Data System (ADS)

In this work, the mean intensity of the second derivative of speckle pattern was used to quantify the quality of the speckle patterns for digital image correlation. Numerical experimental studies were performed to justify the correctness and effectiveness of this new global parameter. The results indicate that the measured displacement error was related to the mean intensity of the second derivative of the speckle patterns when they had equal mean intensity gradients. The results also indicate that the measurement accuracy was affected by both the mean intensity gradient and the mean intensity of the second derivative. Therefore, high quality speckle patterns should have a large mean intensity gradient and a small mean intensity of the second derivative.

Yu, Hai; Guo, Rongxin; Xia, Haiting; Yan, Feng; Zhang, Yubo; He, Tianchun

2014-09-01

373

Cloud based emergency health care information service in India.  

PubMed

A hospital is a health care organization providing patient treatment by expert physicians, surgeons and equipments. A report from a health care accreditation group says that miscommunication between patients and health care providers is the reason for the gap in providing emergency medical care to people in need. In developing countries, illiteracy is the major key root for deaths resulting from uncertain diseases constituting a serious public health problem. Mentally affected, differently abled and unconscious patients can't communicate about their medical history to the medical practitioners. Also, Medical practitioners can't edit or view DICOM images instantly. Our aim is to provide palm vein pattern recognition based medical record retrieval system, using cloud computing for the above mentioned people. Distributed computing technology is coming in the new forms as Grid computing and Cloud computing. These new forms are assured to bring Information Technology (IT) as a service. In this paper, we have described how these new forms of distributed computing will be helpful for modern health care industries. Cloud Computing is germinating its benefit to industrial sectors especially in medical scenarios. In Cloud Computing, IT-related capabilities and resources are provided as services, via the distributed computing on-demand. This paper is concerned with sprouting software as a service (SaaS) by means of Cloud computing with an aim to bring emergency health care sector in an umbrella with physical secured patient records. In framing the emergency healthcare treatment, the crucial thing considered necessary to decide about patients is their previous health conduct records. Thus a ubiquitous access to appropriate records is essential. Palm vein pattern recognition promises a secured patient record access. Likewise our paper reveals an efficient means to view, edit or transfer the DICOM images instantly which was a challenging task for medical practitioners in the past years. We have developed two services for health care. 1. Cloud based Palm vein recognition system 2. Distributed Medical image processing tools for medical practitioners. PMID:22865161

Karthikeyan, N; Sukanesh, R

2012-12-01

374

Microphysical implications of cloud-precipitation covariance derived from satellite remote sensing  

NASA Astrophysics Data System (ADS)

Covariance between cloud and precipitation water in shallow marine boundary layer clouds is assessed using collocated satellite observations from CloudSat and the moderate resolution imaging spectroradiometer (MODIS) at spatial scales typical of global models. An analytic construct is presented, which suggests that global models that do not take subgrid scale cloud-precipitation covariance into account in their microphysical parameterizations may significantly underestimate grid mean microphysical process rates in warm clouds. The proposed framework indicates a mean bias in autoconversion rates of 129% when subgrid scale cloud water variability is neglected and bias in accretion rates of 60% when subgrid cloud-precipitation covariability is neglected at a model grid resolution of 141 km. The bias in accretion rate is dependent on the significant correlation (?) found between cloud and precipitation, which in the global mean is found to be ? = 0.44. The regional distribution of the process rate biases is largely governed by the spatial pattern of cloud water variance. Specific areas of low cloud water variance are found in the subtropical eastern ocean basins and the high latitudes, whereas much of the tropics display relatively larger cloud water variance. These regional distinctions in cloud water variance are associated with commensurate regionality in the process rate biases. The magnitude of the bias has a scale dependence that is governed by the spatial scaling behavior of the cloud and precipitation variances, which follow a power law scaling with exponent of 2/3 at scales below about 10 km and decreasing exponent above this length scale. While the parametric framework reduces biases in the accretion rate estimated from the grid-mean values of cloud and precipitation water, it is shown that it still undercorrects the accretion rate because it neglects the fact that the precipitation fractional area is less than the cloud fractional area and is preferentially colocated with the highest cloud water concentrations. These results imply that (1) predicting the appropriate balance of autoconversion to accretion in global models requires not only the subgrid scale cloud water variability but also the subgrid scale covariability of cloud and precipitation water and (2) the ability of a global model to calculate the correct regional variation in process rates depends crucially on the fidelity of that model to predict or diagnose the spatial distribution of the variance in cloud water.

Lebsock, Matthew; Morrison, Hugh; Gettelman, Andrew

2013-06-01

375

Cloud shadow speed sensor  

NASA Astrophysics Data System (ADS)

Changing cloud cover is a major source of solar radiation variability and poses challenges for the integration of solar energy. A compact and economical system is presented that measures cloud shadow motion vectors to estimate power plant ramp rates and provide short-term solar irradiance forecasts. The cloud shadow speed sensor (CSS) is constructed using an array of luminance sensors and a high-speed data acquisition system to resolve the progression of cloud passages across the sensor footprint. An embedded microcontroller acquires the sensor data and uses a cross-correlation algorithm to determine cloud shadow motion vectors. The CSS was validated against an artificial shading test apparatus, an alternative method of cloud motion detection from ground-measured irradiance (linear cloud edge, LCE), and a UC San Diego sky imager (USI). The CSS detected artificial shadow directions and speeds to within 15° and 6% accuracy, respectively. The CSS detected (real) cloud shadow directions and speeds with average weighted root-mean-square difference of 22° and 1.9 m s-1 when compared to USI and 33° and 1.5 m s-1 when compared to LCE results.

Fung, V.; Bosch, J. L.; Roberts, S. W.; Kleissl, J.

2014-06-01

376

Remote Measurements of Snowfalls in Wakasa Bay, Japan with Airborne Millimeter- wave Imaging Radiometer and Cloud Radar  

NASA Technical Reports Server (NTRS)

In this paper we explore the application of combined millimeter-wave radar and radiometry to remotely measure snowfall. During January-February of 2003, a field campaign was conducted with the NASA P-3 aircraft in Wakasa Bay, Japan for the validation of the AMSRE microwave radiometer on board the Aqua satellite. Among the suite of instruments-on board the P-3 aircraft were the Millimeter-wave Imaging Radiometer (MIR) from the NASA Goddard Space Flight Center and the 94 GHz Airborne Cloud Radar (ACR) which is co-owned and operated by NASA Jet Propulsion Laboratory/University of Massachusetts. MIR is a total power, across-track scanning radiometer that measures radiation at the frequencies of 89, 150, 183.3 +/- 1, 183.3 +/- 3, 183.3 +/-7, 220, and 340 GHz. The MIR has flown many successful missions since its completion in May 1992. ACR is a newer instrument and flew only a few times prior to the Wakasa Bay deployment. These two instruments which are particularly well suited for the detection of snowfall functioned normally during flights over snowfall and excellent data sets were acquired. On January 14, 28, and 29 flights were conducted over snowfall events. The MIR and ACR detected strong signals during periods of snowfall over ocean and land. Results from the analysis of these concurrent data sets show that (1) the scattering of millimeter-wave radiation as detected by the MIR is strongly correlated with ACR radar reflectivity profiles, and (2) the scattering is highly frequency-dependent, the higher the frequency the stronger the scattering. Additionally, the more transparent channels of the MIR (e.g., 89, 150, and 220 GHz) are found to display ambiguous signatures of snowfall because of their exposure to surface features. Thus, the snowfall detection and retrievals of snowfall parameters, such as the ice water path (IWP) and median mass diameter (D(me)) are best conducted at the more opaque channels near 183.3 GHz and 340 GHz. Retrievals of IWP and D(me) using the MIR measurements at 183.3 and 340 GHZ are currently in progress, and the results will be compared with those derived from the ACR reflectivity profiles. Implication from this comparison will be discussed.

Wang, J. R.; Austin, R.; Liu, G. S.; Racette, P. E.

2004-01-01

377

Immobilized Antibody Orientation Analysis using Secondary Ion Mass Spectrometry and Fluorescence Imaging of Affinity-generated Patterns  

PubMed Central

This study assesses the capability of high-resolution surface analytical tools to distinguish immobilized antibody orientations on patterned surfaces designed for antibody affinity capture. High-fidelity, side-by-side co-patterning of protein A (antibody Fc domain affinity reagent) and fluorescein (antibody Fab domain hapten) was achieved photo-lithographically on commercial amine-reactive hydrogel polymer surfaces. This was verified from fluorescence imaging using fluorescently labeled protein A and intrinsic fluorescence from fluorescein. Subsequently, dye-labeled murine anti-fluorescein antibody (4-4-20), and antibody Fab and Fc fragments were immobilized from solution onto respective protein A- and fluorescein- co-patterned or control surfaces using antibody-ligand affinity interactions. Fluorescence assays support specific immobilization to fluorescein hapten- and protein A-patterned regions through antigen-antibody recognition and natural protein A-Fc domain interactions, respectively. Affinity-based antibody immobilization on the two different co-patterned surfaces generated side-by-side full antibody “heads-up” and “tails-up” oriented surface patterns. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis, sensitive to chemical information from the top 2-3 nm of the surface, provided ion-specific images of these antibody patterned regions, imaging and distinguishing characteristic ions from amino acids enriched in Fab domains for antibodies oriented in “heads-up” regions, and ions from amino acids enriched in Fc domains for antibodies oriented in “tails-up” regions. Principal component analysis (PCA) improved the distinct ToF-SIMS amino acid compositional and ion-specific surface mapping sensitivity for each “heads-up” versus “tails-up” patterned region. Characteristic Fab and Fc fragment immobilized patterns served as controls. This provides first demonstration of pattern-specific, antibody orientation-dependent surface maps based on antibody domain- and structure- specific compositional differences by ToF-SIMS analysis. Since antibody immobilization and orientation are critical to many technologies, orientation characterization using ToF-SIMS could be very useful and convenient for immobilization quality control and understanding methods for improving the performance of antibody-based surface capture assays. PMID:20230047

Liu, Fang; Dubey, Manish; Takahashi, Hironobu; Castner, David G.; Grainger, David W.

2010-01-01

378

Participation in the Mars Data Analysis Program: Analysis of cloud forms in Viking and Mariner 9 images  

NASA Technical Reports Server (NTRS)

The first systematic account of the climate of Mars, based upon observations was produced. Cloud data were used to determine spatially and temporally varying near-surface wind direction, relative wind speed, static stability, and humidity conditions on a global scale. Existing models of meteorological processes were critically reexamined in light of the data, and more stringent constraints were set on global processes. Several discoveries were made, including the large extent and seasonal variability of the Mars equatorial Hadley cell, the failure of high latitude winds to reverse direction in early northern spring, the change in meridional wind component in southern midautum, and the almost constant cloud cover in the northern hemisphere, during spring and summer primarily by condensate clouds and in fall and winter by condensates and dust. The implications of these observations are discussed.

Gierasch, P.; Kahn, R. A.

1985-01-01

379

An effective procedure to create a speckle pattern on biological soft tissue for digital image correlation measurements.  

PubMed

Creating a speckle pattern on biological soft tissue, which would be suitable for digital image correlation measurements, is challenging. Speckle patterns should neither cause or require sample dehydration, nor alter the mechanical response, but they should adhere to the tissue surface and withstand large deformations. A two-step procedure has been implemented to create a highly-contrasted pattern. It requires staining of the tissue with methylene blue solution to obtain a dark background and airbrushing the surface with paint to create white speckles. This study evaluated the effectiveness of the proposed procedure and whether the pattern creation had any effect on the elastic response of soft tissue. Forty porcine collateral ligaments underwent three series of cyclic tensile tests to a nominal elongation of 10% for 30 cycles. The specimen stiffness was calculated from the load-elongation curve collected during the last 10 cycles. One side of 20 ligaments was blue stained between the first and second test series, and white patterned between the second and third test series. During the last series, ligament surface images were also acquired and elaborated using the digital image correlation technique. The other 20 ligaments were untreated. The data show a small non-significant upward trend in stiffness in treated as well as in untreated ligaments (maximum increase of 1.7%). The 'successfully-correlated area' of the stereo-visible ligament surface was on average 96%, i.e. small parts of the 'stereo-visible area' were lost during computation. The described procedure is an effective method to create a pattern on biological soft tissues. PMID:25064161

Lionello, Giacomo; Sirieix, Camille; Baleani, Massimiliano

2014-11-01

380

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees  

NASA Technical Reports Server (NTRS)

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Shiffman, Smadar

2004-01-01

381

DEEP NEAR-INFRARED IMAGING OF THE {rho} Oph CLOUD CORE: CLUES TO THE ORIGIN OF THE LOWEST-MASS BROWN DWARFS  

SciTech Connect

A search for young substellar objects in the {rho} Oph cloud core region has been made with the aid of multiband profile-fitting point-source photometry of the deep-integration Combined Calibration Scan images of the 2MASS extended mission in the J, H, and K{sub s} bands, and Spitzer IRAC images at 3.6, 4.5, 5.8, and 8.0 {mu}m. The field of view of the combined observations was 1{sup 0} x 9.'3, and the 5{sigma} limiting magnitude at J was 20.5. Comparison of the observed spectral energy distributions with the predictions of the COND and DUSTY models, for an assumed age of 1 Myr, supports the identification of many of the sources with brown dwarfs and enables the estimation of effective temperature, T {sub eff}. The cluster members are then readily distinguishable from background stars by their locations on a plot of flux density versus T {sub eff}. The range of estimated T {sub eff} values extends down to {approx}750 K which, based on the COND model, would suggest the presence of objects of sub-Jupiter mass. The results also suggest that the mass function for the {rho} Oph cloud resembles that of the {sigma} Orionis cluster based on a recent study, with both rising steadily toward lower masses. The other main result from our study is the apparent presence of a progressive blueward skew in the distribution of J - H and H - K{sub s} colors, such that the blue end of the range becomes increasingly bluer with increasing magnitude. We suggest that this behavior might be understood in terms of the 'ejected stellar embryo' hypothesis, whereby some of the lowest-mass brown dwarfs could escape to locations close to the front edge of the cloud, and thereby be seen with less extinction.

Marsh, Kenneth A.; Plavchan, Peter; Kirkpatrick, J. Davy; Lowrance, Patrick J.; Cutri, Roc M. [Infrared Processing and Analysis Center, California Institute of Technology 100-22, Pasadena, CA 91125 (United States); Velusamy, Thangasamy, E-mail: kam@ipac.caltech.ed, E-mail: plavchan@ipac.caltech.ed, E-mail: davy@ipac.caltech.ed, E-mail: lowrance@ipac.caltech.ed, E-mail: roc@ipac.caltech.ed, E-mail: Thangasamy.Velusamy@jpl.nasa.go [Jet Propulsion Laboratory, MS 169-506, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States)

2010-08-10

382

Artist's Rendering of Multiple Whirlpools in a Sodium Gas Cloud  

NASA Technical Reports Server (NTRS)

This image depicts the formation of multiple whirlpools in a sodium gas cloud. Scientists who cooled the cloud and made it spin created the whirlpools in a Massachusetts Institute of Technology laboratory, as part of NASA-funded research. This process is similar to a phenomenon called starquakes that appear as glitches in the rotation of pulsars in space. MIT's Wolgang Ketterle and his colleagues, who conducted the research under a grant from the Biological and Physical Research Program through NASA's Jet Propulsion Laboratory, Pasadena, Calif., cooled the sodium gas to less than one millionth of a degree above absolute zero (-273 Celsius or -460 Fahrenheit). At such extreme cold, the gas cloud converts to a peculiar form of matter called Bose-Einstein condensate, as predicted by Albert Einstein and Satyendra Bose of India in 1927. No physical container can hold such ultra-cold matter, so Ketterle's team used magnets to keep the cloud in place. They then used a laser beam to make the gas cloud spin, a process Ketterle compares to stroking a ping-pong ball with a feather until it starts spirning. The spinning sodium gas cloud, whose volume was one- millionth of a cubic centimeter, much smaller than a raindrop, developed a regular pattern of more than 100 whirlpools.

2003-01-01

383

Optimum exposure conditions for computed radiography depending on fixed pattern noise and efficiency of imaging plate-scanner systems  

SciTech Connect

The presently active standards on Computed Radiography (CR) need a major revision. It was observed by many users that the image quality for class B of EN 14784-2 is not achievable under the same exposure conditions as used for film exposure. A mathematical model was developed and tested, which allows the calculation of the image quality, proven by image quality indicators (IQI), depending on the fixed pattern noise and the efficiency of the used imaging