Science.gov

Sample records for image cloud patterns

  1. Active Imaging through Cirrus Clouds.

    PubMed

    Landesman, B; Kindilien, P; Pierson, R; Matson, C; Mosley, D

    1997-11-24

    The presence of clouds of ice particles in the uplink and downlink path of an illumination beam can severely impede the performance of an active imaging system. Depending on the optical depth of the cloud, i.e., its density and depth, the beam can be completely scattered and extinguished, or the beam can pass through the cloud with some fraction attenuated, scattered, and depolarized. In particular, subvisual cirrus clouds, i.e., high, thin cirrus clouds that cannot be observed from the ground, can affect the properties and alignment of both uplink and downlink beams. This paper discusses the potential for active imaging in the presence of cirrus clouds. We document field data results from an active imaging experiment conducted several years ago, which the authors believe to show the effects of cirrus clouds on an active imaging system. To verify these conclusions, we include the results of a simulation of the interaction of a coherent illumination scheme with a cirrus cloud.

  2. Detailed Cloud Patterns in Martian Northern Hemisphere

    NASA Technical Reports Server (NTRS)

    1998-01-01

    Cold and cloudy mornings; cool, hazy afternoons. High winds aloft and weather fronts moving slowly to the east. It is winter in the Martian northern hemisphere. One of the many reasons to study Mars is that, at times, its weather is very 'Earth-like.' At this time of the Martian year, clouds are abundant, especially in the morning and especially in the high northern latitudes. Clouds and fogs are also observed in low-lying areas farther to the south, in some lowlands they are as far south as the equator.

    The above color composite images, obtained by Mars Global Surveyor's camera on June 4, 1998, illustrate this Martian 'weather report.' Most of the thick, white clouds seen here occur north of latitude 35oN (roughly equivalent to Albuquerque NM, Memphis TN, and Charlotte, NC). Fog (seen as bright orange because it is lighter than the ground but some of the ground is still visible) occupies the lowest portions of the Kasei Valles outflow channel around 30oN and at 25oN.

    Several different types of cloud features are seen. The repetitious, wash-board pattern of parallel lines are 'gravity wave clouds'. These commonly form, in the lee--downwind side-- of topographic features such as mountain ranges (on Earth) or crater rims (on Mars), under very specific atmospheric conditions (low temperatures, high humidity, and high wind speeds). In this area, the wave clouds are lower in the atmosphere than some of the other clouds. These other clouds show attributes reflecting more the regional weather pattern, occasionally showing the characteristic 'slash' shape (southwest to northeast) of a weather front. These clouds probably contain mostly crystals of water ice but, depending on the temperature at high altitude (and more likely closer to the pole), some could also contain frozen carbon dioxide ('dry ice').

    MOC images 34501 (the red wide angle image) and 34502 (the blue wide angle image) were obtained on Mars Global Surveyor's 345th orbit about the planet

  3. Waves, advection, and cloud patterns on Venus

    NASA Technical Reports Server (NTRS)

    Schinder, Paul J.; Gierasch, Peter J.; Leroy, Stephen S.; Smith, Michael D.

    1990-01-01

    The stable layers adjacent to the nearly neutral layer within the Venus clouds are found to be capable of supporting vertically trapped, horizontally propagating waves with horizontal wavelengths of about 10 km and speeds of a few meters per second relative to the mean wind in the neutral layer. These waves may possibly be excited by turbulence within the neutral layer. Here, the properties of the waves, and the patterns which they might produce within the visible clouds if excited near the subsolar point are examined. The patterns can be in agreement with many features in images. The waves are capable of transferring momentum latitudinally to help maintain the general atmospheric spin, but at present we are not able to evaluate wave amplitudes. We also examine an alternative possibility that the cloud patterns are produced by advection and shearing by the mean zonal and meridional flow of blobs formed near the equator. It is concluded that advection and shearing by the mean flow is the most likely explanation for the general pattern of small scale striations.

  4. Determine precipitation rates from visible and infrared satellite images of clouds by pattern recognition technique. Progress Report, 1 Jul. 1985 - 31 Mar. 1987 Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Weinman, James A.; Garan, Louis

    1987-01-01

    A more advanced cloud pattern analysis algorithm was subsequently developed to take the shape and brightness of the various clouds into account in a manner that is more consistent with the human analyst's perception of GOES cloud imagery. The results of that classification scheme were compared with precipitation probabilities observed from ships of opportunity off the U.S. east coast to derive empirical regressions between cloud types and precipitation probability. The cloud morphology was then quantitatively and objectively used to map precipitation probabilities during two winter months during which severe cold air outbreaks were observed over the northwest Atlantic. Precipitation probabilities associated with various cloud types are summarized. Maps of precipitation probability derived from the cloud morphology analysis program for two months and the precipitation probability derived from thirty years of ship observation were observed.

  5. Cloud computing in medical imaging.

    PubMed

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

    2013-07-01

    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.

  6. Venus Cloud Patterns (colorized and filtered)

    NASA Technical Reports Server (NTRS)

    1990-01-01

    This picture of Venus was taken by the Galileo spacecrafts Solid State Imaging System on February 14, 1990, at a range of almost 1.7 million miles from the planet. A highpass spatial filter has been applied in order to emphasize the smaller scale cloud features, and the rendition has been colorized to a bluish hue in order to emphasize the subtle contrasts in the cloud markings and to indicate that it was taken through a violet filter. The sulfuric acid clouds indicate considerable convective activity, in the equatorial regions of the planet to the left and downwind of the subsolar point (afternoon on Venus). They are analogous to 'fair weather clouds' on Earth. The filamentary dark features visible in the colorized image are here revealed to be composed of several dark nodules, like beads on a string, each about 60 miles across. The Galileo Project is managed for NASA's Office of Space Science and Applications by the Jet Propulsion Laboratory; its mission is to study Jupiter and its satellites and magnetosphere after multiple gravity assist flybys at Venus and Earth. These images of the Venus clouds were taken by Galileo's Solid State Imaging System February 13, 1990, at a range of about 1 million miles. The smallest detail visible is about 20 miles. The two right images show Venus in violet light, the top one at a time six hours later than the bottom one. They show the state of the clouds near the top of Venus's cloud deck. A right to left motion of the cloud features is evident and is consistent with westward winds of about 230 mph. The two left images show Venus in near infrared light, at the same times as the two right images. Sunlight penetrates through the clouds more deeply at the near infrared wavelengths, allowing a view near the bottom of the cloud deck. The westward motion of the clouds is slower (about 150 mph) at the lower altitude. The clouds are composed of sulfuric acid droplets and occupy a range of altitudes from 30 to 45 miles. The images have

  7. Interpretation of MODIS Cloud Images by CloudSat/CALIPSO Cloud Vertical Profiles

    NASA Astrophysics Data System (ADS)

    Wang, T.; Fetzer, E. J.; Wong, S.; Yue, Q.

    2015-12-01

    Clouds observed by passive remote-sensing imager (Aqua-MODIS) are collocated to cloud vertical profiles observed by active profiling sensors (CloudSat radar and CALIPSO lidar) at the pixel-scale. By comparing different layers of cloud types classified in the 2B-CLDCLASS-LIDAR product from CloudSat+CALIPSO to those cloud properties observed by MODIS, we evaluate the occurrence frequencies of cloud types and cloud-overlap in CloudSat+CALIPSO for each MODIS cloud regime defined by cloud optical depth (τ) and cloud-top pressure (P) histograms. We find that about 70% of MODIS clear sky agrees with the clear category in CloudSat+CALIPSO; whereas the remainder is either single layer (~25%) cirrus (Ci), low-level cumulus (Cu), stratocumulus (Sc), or multi-layer (<5%) clouds in CloudSat+CALIPSO. Under MODIS cloudy conditions, 60%, 28%, and 8% of the occurrences show single-, double-, and triple-layer clouds, respectively in CloudSat+CALIPSO. When MODIS identifies single-layer clouds, 50-60% of the MODIS low-level clouds are categorized as stratus (Sc) in CloudSat+CALIPSO. Over the tropics, ~70% of MODIS high and optically thin clouds (considered as cirrus in the histogram) is also identified as Ci in CloudSat+CALIPSO, and ~40% of MODIS high and optically thick clouds (considered as convective in the histogram) agrees with CloudSat+CALIPSO deep convections (DC). Over mid-latitudes these numbers drop to 45% and 10%, respectively. The best agreement occurs in tropical single-layer cloud regimes, where 90% of MODIS high-thin clouds are identified as Ci by CloudSat+CALIPSO and 60% of MODIS high-thick clouds are identified as DC. Worst agreement is found for multi-layer clouds, where cirrus on top of low- and mid-level clouds in MODIS are frequently categorized as high-thick clouds by passive imaging - among these only 5-12% are DC in CloudSat+CALIPSO. It is encouraging that both MODIS low-level clouds (regardless of optical thickness) and high-level thin clouds are consistently

  8. Comparison of IR and Visible Cloud Imagers

    NASA Astrophysics Data System (ADS)

    Mandeville, W.; McLaughlin, T.; Bygren, S.; Randell, C.

    This paper presents a comparison between the Infrared Cloud Imager (IRCI) used at Ground-based Electro-Optical Deep Space Surveillance (GEODSS) sites and the Visible Cloud Imager (VCI) developed using a COTS all-sky camera. The cloud imagers are used to create exclusion maps for GEODSS observations based on detected cloud locations. Excluding observation attempts in obscured areas of the sky is done to improve the allocation of sensor resources. Estimates are made for atmospheric extinction across the entire sky by comparing known star brightness to measured brightness. Data for the comparison were collected at the GEODSS test site located in Yoder, Colorado for a variety of cloud conditions.

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

    NASA Astrophysics Data System (ADS)

    Morales-Juberías, Raúl; Dowling, Timothy E.

    2013-07-01

    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 Δy/Ld ≲ 0.15, where Δy ≲ 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

  10. Pattern recognition of satellite cloud imagery for improved weather prediction

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

    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.

  11. CEDIMS: cloud ethical DICOM image Mojette storage

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

    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.

  12. Patterns of Diurnal Marine Stratocumulus Cloud Fraction Variability

    SciTech Connect

    Burleyson, Casey D.; Yuter, S. E.

    2015-04-01

    The spatial patterns of subtropical marine stratocumulus cloud fraction variability on diurnal time scales are examined using high temporal resolution cloud masks based on 30-min 4 km x 4 km geosynchronous IR data for the period 2003-2010. This data set permits comparison of low cloud fraction variability characteristics among the three marine stratocumulus regions in the southeast Pacific, southeast Atlantic and northeast Pacific. In all three regions, the largest diurnal cycles and earliest time of cloud break up occur on the edges of the cloud field where cloud fractions are in general lower. During the peak season of cloudiness in the southeast Pacific and southeast Atlantic the amplitude of the diurnal cycle on the edges of the cloud deck was greater than 40%, more than double the value found in the center of each cloud deck. The rate at which the cloud breaks up during the day is closely tied to starting cloud fraction at dawn and the shortwave radiative flux. The maximum rate of cloud breakup occurs near 1200 LT. Cloud fraction begins to increase at 1600 LT (before the sun sets) and reaches its maximum value just before dawn. The diurnal cycle characteristics of the southeast Pacific and southeast Atlantic marine stratocumulus cloud decks are more similar to each other than to those in the northeast Pacific. The northeast Pacific cloud deck has weaker diurnal variation, slower rates of cloud breakup during the day for a given cloud fraction at dawn, and higher probabilities for cloud break up overnight.

  13. Global patterns of cloud optical thickness variation with temperature

    SciTech Connect

    Tselioudis, G.; Rossow, W.B.; Rind, D. )

    1992-12-01

    The International Satellite Cloud Climatology Project (ISCCP) 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. The analysis is done separately for clouds over land and ocean. 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. The behavior of the optical thickness-temperature relation is usually, though not always, the same whether the temperature variations are driven by seasonal, latitudinal, or day-to-day changes. Important exceptions are noted. Some explanations for the observed behavior are proposed. 43 refs., 8 figs.

  14. Cloud Optimized Image Format and Compression

    NASA Astrophysics Data System (ADS)

    Becker, P.; Plesea, L.; Maurer, T.

    2015-04-01

    Cloud based image storage and processing requires revaluation of formats and processing methods. For the true value of the massive volumes of earth observation data to be realized, the image data needs to be accessible from the cloud. Traditional file formats such as TIF and NITF were developed in the hay day of the desktop and assumed fast low latency file access. Other formats such as JPEG2000 provide for streaming protocols for pixel data, but still require a server to have file access. These concepts no longer truly hold in cloud based elastic storage and computation environments. This paper will provide details of a newly evolving image storage format (MRF) and compression that is optimized for cloud environments. Although the cost of storage continues to fall for large data volumes, there is still significant value in compression. For imagery data to be used in analysis and exploit the extended dynamic range of the new sensors, lossless or controlled lossy compression is of high value. Compression decreases the data volumes stored and reduces the data transferred, but the reduced data size must be balanced with the CPU required to decompress. The paper also outlines a new compression algorithm (LERC) for imagery and elevation data that optimizes this balance. Advantages of the compression include its simple to implement algorithm that enables it to be efficiently accessed using JavaScript. Combing this new cloud based image storage format and compression will help resolve some of the challenges of big image data on the internet.

  15. Arctic Clouds Infrared Imaging Field Campaign Report

    SciTech Connect

    Shaw, J. A.

    2016-03-01

    The Infrared Cloud Imager (ICI), a passive thermal imaging system, was deployed at the North Slope of Alaska site in Barrow, Alaska, from July 2012 to July 2014 for measuring spatial-temporal cloud statistics. Thermal imaging of the sky from the ground provides high radiometric contrast during night and polar winter when visible sensors and downward-viewing thermal sensors experience low contrast. In addition to demonstrating successful operation in the Arctic for an extended period and providing data for Arctic cloud studies, a primary objective of this deployment was to validate novel instrument calibration algorithms that will allow more compact ICI instruments to be deployed without the added expense, weight, size, and operational difficulty of a large-aperture onboard blackbody calibration source. This objective was successfully completed with a comparison of the two-year data set calibrated with and without the onboard blackbody. The two different calibration methods produced daily-average cloud amount data sets with correlation coefficient = 0.99, mean difference = 0.0029 (i.e., 0.29% cloudiness), and a difference standard deviation = 0.054. Finally, the ICI instrument generally detected more thin clouds than reported by other ARM cloud products available as of late 2015.

  16. Global patterns of cloud optical thickness variation with temperature

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

    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.

  17. Global patterns of cloud optical thickness variation with temperature

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

    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.

  18. Optimized absorption imaging of mesoscopic atomic clouds

    NASA Astrophysics Data System (ADS)

    Muessel, Wolfgang; Strobel, Helmut; Joos, Maxime; Nicklas, Eike; Stroescu, Ion; Tomkovič, Jiří; Hume, David B.; Oberthaler, Markus K.

    2013-10-01

    We report on the optimization of high-intensity absorption imaging for small Bose-Einstein condensates. The imaging calibration exploits the linear scaling of the quantum projection noise with the mean number of atoms for a coherent spin state. After optimization for atomic clouds containing up to 300 atoms, we find an atom number resolution of atoms, mainly limited by photon shot noise and radiation pressure.

  19. Spatial and Temporal Patterns of Aerosol-Cloud Interactions

    NASA Astrophysics Data System (ADS)

    Fuchs, Julia; Cermak, Jan

    2014-05-01

    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.

  20. Imaging Sensor Constellation for Tomographic Chemical Cloud Mapping

    DTIC Science & Technology

    2009-01-30

    a chemical cloud parallels the approach used in X-ray based medical imaging and can be an important tool in understanding chemical cloud dynamics...SR-1345 PSI-1505 Imaging Sensor Constellation for Tomographic Chemical Cloud Mapping Bogdan R. Cosofret,1,* Daisei Konno,1 Aram Faghfouri...00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Imaging Sensor Constellation for Tomographic Chemical Cloud Mapping 5a. CONTRACT NUMBER 5b

  1. Recognition methods on cloud amount, movement of clouds, and rain clouds for rainfall prediction using whole sky images

    NASA Astrophysics Data System (ADS)

    Fujinuma, Kazuma; Arai, Masayuki

    2014-04-01

    The final target of our research is to develop a system for forecasting local concentrated heavy rain, such as guerrilla rainstorms, by using whole sky images taken on the ground. To construct this system, this paper proposes the following recognition methods: cloud amount, movement of clouds, and rain clouds. The experimental results show that red/blue (R/B) values are efficient for measuring the cloud amount. However, using the gravity of images and the difference among time-sequenced images is insufficient to recognize the movement of clouds and does not correlate well with the R/B values and rain.

  2. An efficient framework for modeling clouds from Landsat8 images

    NASA Astrophysics Data System (ADS)

    Yuan, Chunqiang; Guo, Jing

    2015-03-01

    Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.

  3. CloudSat Image of Tropical Thunderstorms Over Africa

    NASA Technical Reports Server (NTRS)

    2006-01-01

    [figure removed for brevity, see original site] Figure 1

    CloudSat image of a horizontal cross-section of tropical clouds and thunderstorms over east Africa. The red colors are indicative of highly reflective particles such as water (rain) or ice crystals, which the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudS at Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The brown line below the image indicates the relative elevation of the land surface. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) visible image taken at nearly the same time.

  4. 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 ...

  5. Pattern recognition analysis of polar clouds during summer and winter

    NASA Technical Reports Server (NTRS)

    Ebert, Elizabeth E.

    1992-01-01

    A pattern recognition algorithm is demonstrated which classifies eighteen surface and cloud types in high-latitude AVHRR imagery based on several spectral and textural features, then estimates the cloud properties (fractional coverage, albedo, and brightness temperature) using a hybrid histogram and spatial coherence technique. The summertime version of the algorithm uses both visible and infrared data (AVHRR channels 1-4), while the wintertime version uses only infrared data (AVHRR channels 3-5). Three days of low-resolution AVHRR imagery from the Arctic and Antarctic during January and July 1984 were analyzed for cloud type and fractional coverage. The analysis showed significant amounts of high cloudiness in the Arctic during one day in winter. The Antarctic summer scene was characterized by heavy cloud cover in the southern ocean and relatively clear conditions in the continental interior. A large region of extremely low brightness temperatures in East Antarctica during winter suggests the presence of polar stratospheric cloud.

  6. A cloud-based medical image repository

    NASA Astrophysics Data System (ADS)

    Maeder, Anthony J.; Planitz, Birgit M.; El Rifai, Diaa

    2012-02-01

    Many widely used digital medical image collections have been established but these are generally used as raw data sources without related image analysis toolsets. Providing associated functionality to allow specific types of operations to be performed on these images has proved beneficial in some cases (e.g. brain image registration and atlases). However, toolset development to provide generic image analysis functions on medical images has tended to be ad hoc, with Open Source options proliferating (e.g. ITK). Our Automated Medical Image Collection Annotation (AMICA) system is both an image repository, to which the research community can contribute image datasets, and a search/retrieval system that uses automated image annotation. AMICA was designed for the Windows Azure platform to leverage the flexibility and scalability of the cloud. It is intended that AMICA will expand beyond its initial pilot implementation (for brain CT, MR images) to accommodate a wide range of modalities and anatomical regions. This initiative aims to contribute to advances in clinical research by permitting a broader use and reuse of medical image data than is currently attainable. For example, cohort studies for cases with particular physiological or phenotypical profiles will be able to source and include enough cases to provide high statistical power, allowing more individualised risk factors to be assessed and thus allowing screening and staging processes to be optimised. Also, education, training and credentialing of clinicians in image interpretation, will be more effective because it will be possible to select instances of images with specific visual aspects, or correspond to types of cases where reading performance improvement is desirable.

  7. Cloud Imagers Offer New Details on Earth's Health

    NASA Technical Reports Server (NTRS)

    2009-01-01

    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

  8. Cloud classification using whole-sky imager data

    SciTech Connect

    Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R.

    1996-04-01

    Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes based on measured data from real cloud scenes. These renderings will provide the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

  9. Capturing and analyzing wheelchair maneuvering patterns with mobile cloud computing.

    PubMed

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

    2013-01-01

    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.

  10. Interferometric laser imaging for in-flight cloud droplet sizing

    NASA Astrophysics Data System (ADS)

    Dunker, Christina; Roloff, Christoph; Grassmann, Arne

    2016-12-01

    A non-intrusive particle sizing method with a high spatial distribution is used to estimate cloud droplet spectra during flight test campaigns. The interferometric laser imaging for droplet sizing (ILIDS) method derives particle diameters of transparent spheres by evaluating the out-of-focus image patterns. This sizing approach requires a polarized monochromatic light source, a camera including an objective lens with a slit aperture, a synchronization unit and a processing tool for data evaluation. These components are adapted to a flight test environment to enable the microphysical investigation of different cloud genera. The present work addresses the design and specifications of ILIDS system, flight test preparation and selected results obtained in the lower and middle troposphere. The research platform was a Dornier Do228-101 commuter aircraft at the DLR Flight Operation Center in Braunschweig. It was equipped with the required instrumentation including a high-energy laser as the light source. A comprehensive data set of around 71 800 ILIDS images was acquired over the course of five flights. The data evaluation of the characteristic ILIDS fringe patterns relies, among other things, on a relationship between the fringe spacing and the diameter of the particle. The simplest way to extract this information from a pattern is by fringe counting, which is not viable for such an extensive number of data. A brief contrasting comparison of evaluation methods based on frequency analysis by means of fast Fourier transform and on correlation methods such as minimum quadratic difference is used to encompass the limits and accuracy of the ILIDS method for such applications.

  11. Radiometric cloud imaging with an uncooled microbolometer thermal infrared camera.

    PubMed

    Shaw, Joseph; Nugent, Paul; Pust, Nathan; Thurairajah, Brentha; Mizutani, Kohei

    2005-07-25

    An uncooled microbolometer-array thermal infrared camera has been incorporated into a remote sensing system for radiometric sky imaging. The radiometric calibration is validated and improved through direct comparison with spectrally integrated data from the Atmospheric Emitted Radiance Interferometer (AERI). With the improved calibration, the Infrared Cloud Imager (ICI) system routinely obtains sky images with radiometric uncertainty less than 0.5 W/(m(2 )sr) for extended deployments in challenging field environments. We demonstrate the infrared cloud imaging technique with still and time-lapse imagery of clear and cloudy skies, including stratus, cirrus, and wave clouds.

  12. Data and image fusion for geometrical cloud characterization

    SciTech Connect

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

    1997-04-01

    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.

  13. Cloud morphology and motions from Pioneer Venus images

    NASA Technical Reports Server (NTRS)

    Rossow, W. B.; Del Genio, A. D.; Limaye, S. S.; Travis, L. D.; Stone, P. H.

    1980-01-01

    The horizontal and vertical cloud structures, atmospheric waves, and wind velocities at the cloud top level were determined by the Pioneer Venus photopolarimeter images in the UV from January through March 1979. The images indicate long-term evolution of cloud characteristics, the atmospheric dynamics, and rapid small changes in cloud morphology. The clouds show a globally coordinated oscillation relative to latitude circles; retrograde zonal winds of 100 m/s near the equator are determined from the tracking of small-scale cloud properties, but two hemispheres show important variations. The zonal wind velocity in the southern hemisphere is reduced toward the poles at a rate similar to solid body rotation; the midlatitude jet stream noted by Mariner 10 is not observed.

  14. Analysis of Gravity Waves Structures Visible in Noctilucent Cloud Images

    DTIC Science & Technology

    2010-01-01

    author. Tel.: +1 4357978128. E-mail address: dominiquepautet@gmail.com Keywords: Noctilucent clouds ( NLC ); Mesosphere lower thermosphere (MLT...clouds ( NLC ) are high-altitude bright cloud formations visible under certain conditions from high-latitude places during the summer months. Even if the...visible in the NLC images taken every summer night since 2004 from Stockholm, Sweden (59.4ºN). The parameters of 30 short-period gravity wave events

  15. Cloud Detection of Optical Satellite Images Using Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Lee, Kuan-Yi; Lin, Chao-Hung

    2016-06-01

    Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

  16. Cloud Detection Method Based on Feature Extraction in Remote Sensing Images

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

    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

  17. Gridless, pattern-driven point cloud completion and extension

    NASA Astrophysics Data System (ADS)

    Gravey, Mathieu; Mariethoz, Gregoire

    2016-04-01

    While satellites offer Earth observation with a wide coverage, other remote sensing techniques such as terrestrial LiDAR can acquire very high-resolution data on an area that is limited in extension and often discontinuous due to shadow effects. Here we propose a numerical approach to merge these two types of information, thereby reconstructing high-resolution data on a continuous large area. It is based on a pattern matching process that completes the areas where only low-resolution data is available, using bootstrapped high-resolution patterns. Currently, the most common approach to pattern matching is to interpolate the point data on a grid. While this approach is computationally efficient, it presents major drawbacks for point clouds processing because a significant part of the information is lost in the point-to-grid resampling, and that a prohibitive amount of memory is needed to store large grids. To address these issues, we propose a gridless method that compares point clouds subsets without the need to use a grid. On-the-fly interpolation involves a heavy computational load, which is met by using a GPU high-optimized implementation and a hierarchical pattern searching strategy. The method is illustrated using data from the Val d'Arolla, Swiss Alps, where high-resolution terrestrial LiDAR data are fused with lower-resolution Landsat and WorldView-3 acquisitions, such that the density of points is homogeneized (data completion) and that it is extend to a larger area (data extension).

  18. Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy

    SciTech Connect

    Thompson, David R.; McCubbin, Ian; Gao, Bo Cai; Green, Robert O.; Matthews, Alyssa A.; Mei, Fan; Meyer, Kerry G.; Platnick, Steven; Schmid, Beat; Tomlinson, Jason; Wilcox, Eric

    2016-08-12

    Shortwave Infrared imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4 to 1.8 μm. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation and then apply it to airborne data acquired in the Calwater-2/ACAPEX campaign of Winter 2015. Here NASA’s “Classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the U.S. Department of Energy ARM Aerial Facility G-1 aircraft measured cloud integral and microphysical properties in situ. Finally, the coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.

  19. Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy

    NASA Astrophysics Data System (ADS)

    Thompson, David R.; McCubbin, Ian; Gao, Bo Cai; Green, Robert O.; Matthews, Alyssa A.; Mei, Fan; Meyer, Kerry G.; Platnick, Steven; Schmid, Beat; Tomlinson, Jason; Wilcox, Eric

    2016-08-01

    Shortwave Infrared imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4 to 1.8 μm. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation and then apply it to airborne data acquired in the Calwater-2/ACAPEX campaign of Winter 2015. Here NASA's "Classic" Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the U.S. Department of Energy ARM Aerial Facility G-1 aircraft measured cloud integral and microphysical properties in situ. The coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.

  20. Atmospheric circulation of brown dwarfs and directly imaged extrasolar giant planets with active clouds

    NASA Astrophysics Data System (ADS)

    Tan, Xianyu; Showman, Adam

    2016-10-01

    Observational evidence have suggested active meteorology in the atmospheres of brown dwarfs (BDs) and directly imaged extrasolar giant planets (EGPs). In particular, a number of surveys for brown dwarfs showed that near-IR brightness variability is common for L and T dwarfs. Directly imaged EGPs share similar observations, and can be viewed as low-gravity versions of BDs. Clouds are believed to play the major role in shaping the thermal structure, dynamics and near-IR flux of these atmospheres. So far, only a few studies have been devoted to atmospheric circulation and the implications for observations of BDs and directly EGPs, and yet no global model includes a self-consistent active cloud formation. Here we present preliminary results from the first global circulation model applied to BDs and directly imaged EGPs that can properly treat absorption and scattering of radiation by cloud particles. Our results suggest that horizontal temperature differences on isobars can reach up to a few hundred Kelvins, with typical horizontal length scale of the temperature and cloud patterns much smaller than the radius of the object. The combination of temperature anomaly and cloud pattern can result in moderate disk-integrated near-IR flux variability. Wind speeds can reach several hundred meters per second in cloud forming layers. Unlike Jupiter and Saturn, we do not observe stable zonal jet/banded patterns in our simulations. Instead, our simulated atmospheres are typically turbulent and dominated by transient vortices. The circulation is sensitive to the parameterized cloud microphysics. Under some parameter combinations, global-scale atmospheric waves can be triggered and maintained. These waves induce global-scale temperature anomalies and cloud patterns, causing large (up to several percent) disk-integrated near-IR flux variability. Our results demonstrate that the commonly observed near-IR brightness variability for BDs and directly imaged EGPs can be explained by the

  1. Image transfer through cirrus clouds. II. Wave-front segmentation and imaging.

    PubMed

    Landesman, Barbara T; Matson, Charles L

    2002-12-20

    A hybrid technique to simulate the imaging of space-based objects through cirrus clouds is presented. The method makes use of standard Huygens-Fresnel propagation beyond the cloud boundary and a novel vector trace approach within the cloud. At the top of the cloud, the wave front is divided into an array of input gradient vectors, which are in turn transmitted through the cloud model by use of the Coherent Illumination Ray Trace and Imaging Software for Cirrus. At the bottom of the cloud, the output vector distribution is used to reconstruct a wave front that continues propagating to the ground receiver. Images of the object as seen through cirrus clouds with different optical depths are compared with a diffraction-limited image. Turbulence effects from the atmospheric propagation are not included.

  2. Automatic cloud coverage assessment of Formosat-2 image

    NASA Astrophysics Data System (ADS)

    Hsu, Kuo-Hsien

    2011-11-01

    Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

  3. Automated cloud-drift winds from GOES images

    NASA Astrophysics Data System (ADS)

    Kambhamettu, Chandra; Palaniappan, Kannappan; Hasler, A. Frederick

    1996-10-01

    Estimation of the atmospheric wind field based on cloud tracking using a time sequence of satellite imagery is an extremely challenging problem due to the complex dynamics of the imaging instruments and the underlying non-linear phenomena of cloud formation and weather. Cloud motion may involve both partial fluid motion and partial solid motion, which we model as semi-fluid motion. Motion algorithm with subpixel accuracy using differential geometry invariants of surfaces was developed to track clouds. The motion model is general enough to include both physical and geometrical constraints. Typically, a polynomial displacement function is used to model the local deformation behavior of a surface patch undergoing semi-fluid motion. The cloud tracking algorithm recovers local cloud surface deformations using a sequence of dense depth maps and corresponding intensity imagery, that captures the time evolution of cloud-top heights. Either intensity or depth information can be used by the semi-fluid motion analysis algorithm. A dense disparity or depth map that can be related to cloud-top heights is provided by the Goddard Automatic Stereo Analysis module for input to the motion analysis module. The results of the automatic cloud tracking algorithm are extremely promising with errors comparable to manually tracked winds. Experiments were performed on GOES images of Hurricanes Frederic, Gilbert and Luis, and a temporally dense 1.5 minute time interval thunderstorm sequence covering Florida region. Future work involves using multispectral information, incorporating robustness, cloud motion segmentation and adaptive searching for improving operational cloud-tracking performance.

  4. An enhanced neighborhood similar pixel interpolator approach for removing thick clouds in landsat images

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thick cloud contaminations in Landsat images limit their regular usage for land applications. A few methods have been developed to remove thick clouds using additional cloud-free images. Unfortunately, the cloud-free composition image produced by existing methods commonly lacks from the desired spat...

  5. Space Shuttle Video Images: An Example of Warm Cloud Lightning

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

    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.

  6. Observation of the inception and evolution of a cavitation cloud in tissue with ultrafast ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Prieur, Fabrice; Zorgani, Ali; Catheline, Stefan

    2017-03-01

    The local application of ultrasound is known to improve drug intake by tumors. Cavitating bubbles are one of the contributing effects. A setup where two ultrasound transducers are placed confocally is used to generate cavitation in ex vivo tissue. As the transducers emit a series of short bursts, the creation and evolution of the cavitation activity is monitored using an ultrafast ultrasound imaging system. This system capable of frame rates up to 10000 frames per second provides several tens of images between consecutive bursts. A cross-correlation between consecutive images used for speckle tracking shows a decorrelation of the imaging signal due to changes induced by the cavitation cloud. This post-processed sequence of images reveals that once bubbles have been created in the tissue, they remain for a short time even when no ultrasound is applied. The evolution of the size and place of the cavitation cloud between bursts show a repeatable pattern through a burst sequence.

  7. Jupiter's Cloud Distribution Between the Voyager 1 and 2 Encounters: Results from 5-Micrometer Imaging.

    PubMed

    Terrile, R J; Capps, R W; Becklin, E E; Cruikshank, D P

    1979-11-23

    As part of a continuing effort of ground-based support for Voyager target selection, infrared images in the 5-micrometer wavelength region were acquired in preparation for the Voyager 2 flyby of Jupiter. Observations were made during May 1979 from the Palomar 5-meter telescope and the new 3-meter NASA Infrared Telescope Facility at Mauna Kea and are compared to previous observations. Variations seen in the 5-micrometer flux distribution suggest global patterns of clouding over of some Jovian belts and clearing ofothers. These data were used to predict the Jovian cloud distribution at the time of the Voyager 2 encounter in order to target the imaging and infrared experiments to areas free of high obscuring clouds.

  8. The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

    2007-01-01

    The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

  9. Images from Galileo of the Venus cloud deck

    USGS Publications Warehouse

    Belton, M.J.S.; Gierasch, P.J.; Smith, M.D.; Helfenstein, P.; Schinder, P.J.; Pollack, James B.; Rages, K.A.; Ingersoll, A.P.; Klaasen, K.P.; Veverka, J.; Anger, C.D.; Carr, M.H.; Chapman, C.R.; Davies, M.E.; Fanale, F.P.; Greeley, R.; Greenberg, R.; Head, J. W.; Morrison, D.; Neukum, G.; Pilcher, C.B.

    1991-01-01

    Images of Venus taken at 418 (violet) and 986 [near-infrared (NIR)] nanometers show that the morphology and motions of large-scale features change with depth in the cloud deck. Poleward meridional velocities, seen in both spectral regions, are much reduced in the NIR. In the south polar region the markings in the two wavelength bands are strongly anticorrelated. The images follow the changing state of the upper cloud layer downwind of the subsolar point, and the zonal flow field shows a longitudinal periodicity that may be coupled to the formation of large-scale planetary waves. No optical lightning was detected.

  10. Secure public cloud platform for medical images sharing.

    PubMed

    Pan, Wei; Coatrieux, Gouenou; Bouslimi, Dalel; Prigent, Nicolas

    2015-01-01

    Cloud computing promises medical imaging services offering large storage and computing capabilities for limited costs. In this data outsourcing framework, one of the greatest issues to deal with is data security. To do so, we propose to secure a public cloud platform devoted to medical image sharing by defining and deploying a security policy so as to control various security mechanisms. This policy stands on a risk assessment we conducted so as to identify security objectives with a special interest for digital content protection. These objectives are addressed by means of different security mechanisms like access and usage control policy, partial-encryption and watermarking.

  11. Multistatic Imaging and Optical Modelling of Nacreous Clouds

    NASA Astrophysics Data System (ADS)

    Enell, C.-F.; Gustavsson, B.; Steen, A.; Brändström, U.; Rydesäter, P.

    The presence of polar stratospheric clouds (PSC) has important implications for stratospheric chemistry. Thus it is important to understand the development of such clouds. In this report the feasibility of using multi-static imaging for studies of PSC physics is discussed. In particular, a method to solve for particle sizes using bistatic multi-wavelength observations is described. It has not yet been possible to apply the proposed method to PSC images. However, a numerical simulation for the ideal case of single scattering by spherical particles works with reasonable accuracy, even when random noise is added.

  12. Images from Galileo of the Venus cloud deck

    NASA Technical Reports Server (NTRS)

    Belton, Michael J. S.; Gierasch, Peter J.; Smith, Michael D.; Helfenstein, Paul; Schinder, Paul J.; Pollack, James B.; Rages, Kathy A.; Morrison, David; Klaasen, Kenneth P.; Pilcher, Carl B.

    1991-01-01

    Images of Venus taken at 418 and 986 nm show that the morphology and motions of large-scale features change with depth in the cloud deck. Poleward meridional velocities, seen in both spectral regions, are much reduced in the NIR. In the south polar region the markings in the two wavelength bands are strongly anticorrelated. The images follow the changing state of the upper cloud layer downwind of the subsolar point, and the zonal flowfield shows a longitudinal periodicity that may be coupled to the formation of large-scale planetary waves. No optical lightning was detected.

  13. Auotomatic Classification of Point Clouds Extracted from Ultracam Stereo Images

    NASA Astrophysics Data System (ADS)

    Modiri, M.; Masumi, M.; Eftekhari, A.

    2015-12-01

    Automatic extraction of building roofs, street and vegetation are a prerequisite for many GIS (Geographic Information System) applications, such as urban planning and 3D building reconstruction. Nowadays with advances in image processing and image matching technique by using feature base and template base image matching technique together dense point clouds are available. Point clouds classification is an important step in automatic features extraction. Therefore, in this study, the classification of point clouds based on features color and shape are implemented. We use two images by proper overlap getting by Ultracam-x camera in this study. The images are from Yasouj in IRAN. It is semi-urban area by building with different height. Our goal is classification buildings and vegetation in these points. In this article, an algorithm is developed based on the color characteristics of the point's cloud, using an appropriate DEM (Digital Elevation Model) and points clustering method. So that, firstly, trees and high vegetation are classified by using the point's color characteristics and vegetation index. Then, bare earth DEM is used to separate ground and non-ground points. Non-ground points are then divided into clusters based on height and local neighborhood. One or more clusters are initialized based on the maximum height of the points and then each cluster is extended by applying height and neighborhood constraints. Finally, planar roof segments are extracted from each cluster of points following a region-growing technique.

  14. Determination of Cloud Base Height, Wind Velocity, and Short-Range Cloud Structure Using Multiple Sky Imagers Field Campaign Report

    SciTech Connect

    Huang, Dong; Schwartz, Stephen E.; Yu, Dantong

    2016-07-01

    Clouds are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of clouds by investing in scanning cloud radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's cloud observational capabilities. For example, cloud radars often fail to detect small shallow cumulus and thin cirrus clouds that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a cloud radar to complete a 3D volume scan and clouds can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM cloud observation capabilities. It enables the estimation of cloud coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus cloud or a thin cirrus cloud that cannot be detected by a cloud radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for cloud tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based cloud stereo-imaging technique, the cloud stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1, the cloud

  15. Integration of Images and LIDAR Point Clouds for Building FAÇADE Texturing

    NASA Astrophysics Data System (ADS)

    Chen, L. C.; Chan, L. L.; Chang, W. C.

    2016-06-01

    This paper proposes a model-based method for texture mapping using close-range images and Lidar point clouds. Lidar point clouds are used to aid occlusion detection. For occluded areas, we compensate the occlusion by different view-angle images. Considering the authenticity of façade with repeated patterns under different illumination conditions, a selection of optimum pattern is suggested. In the selection, both geometric shape and texture are analyzed. The grey level co-occurrence matrix analysis is applied for the selection of the optimal façades texture to generate of photorealistic building models. Experimental results show that the proposed method provides high fidelity textures in the generation of photorealistic building models. It is demonstrated that the proposed method is also practical in the selection of the optimal texture.

  16. Extraction of cloud statistics from whole sky imaging cameras

    SciTech Connect

    Kegelmeyer, W.P. Jr.

    1994-03-01

    Computer codes have been developed to extract basic cloud statistics from whole sky imaging (WSI) cameras. This report documents, on an algorithmic level, the steps and processes underlying these codes. Appendices comment on code details and on how to adapt to future changes in either the source camera or the host computer.

  17. Cloud Detection with the Earth Polychromatic Imaging Camera (EPIC)

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    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.

  18. Atmospheric Polarization Imaging with Variable Aerosols and Clouds

    DTIC Science & Technology

    2010-12-10

    to a cloud;  Measurements made at the Mauna Loa Observatory (a mountaintop observatory in Hawaii) confirmed previous studies by Coulson and...on work supported by this grant: 1. Mr. Andrew Dahlberg – All-sky polarization imager deployment at Mauna Loa Observatory , Hawaii – M.S. Thesis...the Mauna Loa Observatory on the island of Hawaii (Dahlberg et al. 2009). The Atmospheric Polarization Imager (API) System The API instrument

  19. Operational Cloud-Motion Winds from Meteosat Infrared Images.

    NASA Astrophysics Data System (ADS)

    Schmetz, Johannes; Holmlund, Kenneth; Hoffman, Joel; Strauss, Bernard; Mason, Brian; Gaertner, Volker; Koch, Arno; van de Berg, Leo

    1993-07-01

    The displacement of clouds in successive satellite images reflects the atmospheric circulation at various scales. The main application of the satellite-derived cloud-motion vectors is their use as winds in the data analysis for numerical weather prediction. At low latitudes in particular they constitute an indispensible data source for numerical weather prediction.This paper describes the operational method of deriving cloud-motion winds (CMW) from the IR image (10.5 12.5 µm) of the European geostationary Meteostat satellites. The method is automatic, that is, the cloud tracking uses cross correlation and the height assignment is based on satellite observed brightness temperature and a forecast temperature profile. Semitransparent clouds undergo a height correction based on radiative forward calculations and simultaneous radiance observations in both the IR and water vapor (5.7 7.1 µm) channel. Cloud-motion winds are subject to various quality checks that include manual quality control as the last step. Typically about 3000 wind vectors are produced per day over four production cycles.This paper documents algorithm changes and improvements made to the operational CMWs over the last five years. The improvements are shown by long-term comparisons with both collocated radiosondes and the first guess of the forecast model of the European Centre for Medium-Range Weather Forecasts. In particular, the height assignment of a wind vector and radiance filtering techniques preceding the cloud tracking have ameliorated the errors in Meteostat winds. The slow speed bias of high-level CMWs (<400 hPa) in comparison to radiosonde winds have been reduced from about 4 to 1.3 m s1 for a mean wind speed of 24 m s1. Correspondingly, the rms vectors error of Meteosat high-level CMWs decreased from about 7.8 to 5 m s1. Medium- and low-level CMWs were also significantly improved.

  20. Cloud Image Data Center for Healthcare Network in Taiwan.

    PubMed

    Weng, Shao-Jen; Lai, Lai-Shiun; Gotcher, Donald; Wu, Hsin-Hung; Xu, Yeong-Yuh; Yang, Ching-Wen

    2016-04-01

    This paper investigates how a healthcare network in Taiwan uses a practical cloud image data center (CIDC) to communicate with its constituent hospital branches. A case study approach was used. The study was carried out in the central region of Taiwan, with four hospitals belonging to the Veterans Hospital healthcare network. The CIDC provides synchronous and asynchronous consultation among these branches. It provides storage, platforms, and services on demand to the hospitals. Any branch-client can pull up the patient's medical images from any hospital off this cloud. Patients can be examined at the branches, and the images and reports can be further evaluated by physicians in the main Taichung Veterans General Hospital (TVGH) to enhance the usage and efficiency of equipment in the various branches, thereby shortening the waiting time of patients. The performance of the CIDC over 5 years shows: (1) the total number of cross-hospital images accessed with CDC in the branches was 132,712; and (2) TVGH assisted the branches in keying in image reports using the CIDC 4,424 times; and (3) Implementation of the system has improved management, efficiency, speed and quality of care. Therefore, the results lead to the recommendation of continuing and expanding the cloud computing architecture to improve information sharing among branches in the healthcare network.

  1. The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud

    NASA Astrophysics Data System (ADS)

    Zeng, Fanyang; Zhong, Ruofei

    2014-03-01

    Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classification and modeling of point-cloud. Different types of digital cameras are used in different Mobile Measurement Systems (MMS).the principles and processes for generating color point-cloud in different systems are not the same. The most prominent feature of the panoramic images is the field of 360 degrees view angle in the horizontal direction, to obtain the image information around the camera as much as possible. In this paper, we introduce a method to generate color point-cloud with panoramic image and laser point-cloud, and deduce the equation of the correspondence between points in panoramic images and laser point-clouds. The fusion of panoramic image and laser point-cloud is according to the collinear principle of three points (the center of the omnidirectional multi-camera system, the image point on the sphere, the object point). The experimental results show that the proposed algorithm and formulae in this paper are correct.

  2. High-resolution Images of Diffuse Neutral Clouds in the Milky Way. I. Observations, Imaging, and Basic Cloud Properties

    NASA Astrophysics Data System (ADS)

    Pidopryhora, Y.; Lockman, Felix J.; Dickey, J. M.; Rupen, M. P.

    2015-08-01

    A set of diffuse interstellar clouds in the inner Galaxy within a few hundred parsecs of the Galactic plane has been observed at an angular resolution of ≈1&farcm0 combining data from the NRAO Green Bank Telescope and the Very Large Array. At the distance of the clouds, the linear resolution ranges from ˜1.9 to ˜2.8 pc. These clouds have been selected to be somewhat outside of the Galactic plane, and thus are not confused with unrelated emission, but in other respects they are a Galactic population. They are located near the tangent points in the inner Galaxy, and thus at a quantifiable distance: 2.3≤slant R≤slant 6.0 kpc from the Galactic Center and -1000≤slant z≤slant +610 pc from the Galactic plane. These are the first images of the diffuse neutral H i clouds that may constitute a considerable fraction of the interstellar medium (ISM). Peak H i column densities lie in the range NH i = 0.8-2.9 × 1020 cm-2. Cloud diameters vary between about 10 and 100 pc, and their H i mass spans the range from less than a hundred to a few thousands M⊙. The clouds show no morphological consistency of any kind, except that their shapes are highly irregular. One cloud may lie within the hot wind from the nucleus of the Galaxy, and some clouds show evidence of two distinct thermal phases as would be expected from equilibrium models of the ISM.

  3. A secure online image trading system for untrusted cloud environments.

    PubMed

    Munadi, Khairul; Arnia, Fitri; Syaryadhi, Mohd; Fujiyoshi, Masaaki; Kiya, Hitoshi

    2015-01-01

    In conventional image trading systems, images are usually stored unprotected on a server, rendering them vulnerable to untrusted server providers and malicious intruders. This paper proposes a conceptual image trading framework that enables secure storage and retrieval over Internet services. The process involves three parties: an image publisher, a server provider, and an image buyer. The aim is to facilitate secure storage and retrieval of original images for commercial transactions, while preventing untrusted server providers and unauthorized users from gaining access to true contents. The framework exploits the Discrete Cosine Transform (DCT) coefficients and the moment invariants of images. Original images are visually protected in the DCT domain, and stored on a repository server. Small representation of the original images, called thumbnails, are generated and made publicly accessible for browsing. When a buyer is interested in a thumbnail, he/she sends a query to retrieve the visually protected image. The thumbnails and protected images are matched using the DC component of the DCT coefficients and the moment invariant feature. After the matching process, the server returns the corresponding protected image to the buyer. However, the image remains visually protected unless a key is granted. Our target application is the online market, where publishers sell their stock images over the Internet using public cloud servers.

  4. Leveraging the Cloud for Robust and Efficient Lunar Image Processing

    NASA Technical Reports Server (NTRS)

    Chang, George; Malhotra, Shan; Wolgast, Paul

    2011-01-01

    The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes to hundreds of gigabytes in size with new data arriving every day. Despite this ever-increasing amount of data, LMMP must make the data readily available in a timely manner for users to view and analyze. This is accomplished by tiling large images into smaller images using Hadoop, a distributed computing software platform implementation of the MapReduce framework, running on a small cluster of machines locally. Additionally, the software is implemented to use Amazon's Elastic Compute Cloud (EC2) facility. We also developed a hybrid solution to serve images to users by leveraging cloud storage using Amazon's Simple Storage Service (S3) for public data while keeping private information on our own data servers. By using Cloud Computing, we improve upon our local solution by reducing the need to manage our own hardware and computing infrastructure, thereby reducing costs. Further, by using a hybrid of local and cloud storage, we are able to provide data to our users more efficiently and securely. 12 This paper examines the use of a distributed approach with Hadoop to tile images, an approach that provides significant improvements in image processing time, from hours to minutes. This paper describes the constraints imposed on the solution and the resulting techniques developed for the hybrid solution of a customized Hadoop infrastructure over local and cloud resources in managing this ever-growing data set. It examines the performance trade-offs of using the more plentiful resources of the cloud, such as those provided by S3, against the bandwidth limitations such use

  5. Underwater 3d Modeling: Image Enhancement and Point Cloud Filtering

    NASA Astrophysics Data System (ADS)

    Sarakinou, I.; Papadimitriou, K.; Georgoula, O.; Patias, P.

    2016-06-01

    This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images' radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

  6. Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

    NASA Technical Reports Server (NTRS)

    Knight, David; Powell, Mark

    2013-01-01

    Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

  7. Research on earthquake prediction from infrared cloud images

    NASA Astrophysics Data System (ADS)

    Fan, Jing; Chen, Zhong; Yan, Liang; Gong, Jing; Wang, Dong

    2015-12-01

    In recent years, the occurrence of large earthquakes is frequent all over the word. In the face of the inevitable natural disasters, the prediction of the earthquake is particularly important to avoid more loss of life and property. Many achievements in the field of predict earthquake from remote sensing images have been obtained in the last few decades. But the traditional prediction methods presented do have the limitations of can't forecast epicenter location accurately and automatically. In order to solve the problem, a new predicting earthquakes method based on extract the texture and emergence frequency of the earthquake cloud is proposed in this paper. First, strengthen the infrared cloud images. Second, extract the texture feature vector of each pixel. Then, classified those pixels and converted to several small suspected area. Finally, tracking the suspected area and estimate the possible location. The inversion experiment of Ludian earthquake show that this approach can forecast the seismic center feasible and accurately.

  8. Voyager imaging of Triton's clouds and hazes

    NASA Technical Reports Server (NTRS)

    Rages, Kathy; Pollack, James B.

    1992-01-01

    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.

  9. Modified control software for imaging ultracold atomic clouds

    SciTech Connect

    Whitaker, D. L.; Sharma, A.; Brown, J. M.

    2006-12-15

    A charge-coupled device (CCD) camera capable of taking high-quality images of ultracold atomic samples can often represent a significant portion of the equipment costs in atom trapping experiment. We have modified the commercial control software of a CCD camera designed for astronomical imaging to take absorption images of ultracold rubidium clouds. This camera is sensitive at 780 nm and has been modified to take three successive 16-bit images at full resolution. The control software can be integrated into a Matlab graphical user interface with fitting routines written as Matlab functions. This camera is capable of recording high-quality images at a fraction of the cost of similar cameras typically used in atom trapping experiments.

  10. Fast Track to the Cloud: Design Patterns for 12-Factor Earth Sciences Applications

    NASA Technical Reports Server (NTRS)

    Pawloski, Andrew; McLaughlin, Brett; Lynnes, Christopher

    2016-01-01

    As expanding service offerings and decreasing prices make the cloud increasingly attractive to Earth Science applications, there are nontrivial practical considerations which can hinder its meaningful use. In this talk, we will discuss architectural recommendations and lessons learned while working on EOSDIS' cloud efforts, particularly the NASA-compliant General Application Platform (NGAP) and its associated applications. Prominent in our findings is the importance of 12-factor design patterns and the powerful "wins" they enable in the cloud. We will share our strategies for "fast-tracking" applications to the cloud --whether they be legacy, planned for the future, or somewhere in between.

  11. CloudSat First Image of a Warm Front Storm Over the Norwegian Sea

    NASA Technical Reports Server (NTRS)

    2006-01-01

    [figure removed for brevity, see original site] Figure 1

    CloudSat's first image, of a warm front storm over the Norwegian Sea, was obtained on May 20, 2006. In this horizontal cross-section of clouds, warm air is seen rising over colder air as the satellite travels from right to left. The red colors are indicative of highly reflective particles such as water droplets (or rain) or larger ice crystals (or snow), while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.

  12. Optical-digital hybrid image search system in cloud environment

    NASA Astrophysics Data System (ADS)

    Ikeda, Kanami; Kodate, Kashiko; Watanabe, Eriko

    2016-09-01

    To improve the versatility and usability of optical correlators, we developed an optical-digital hybrid image search system consisting of digital servers and an optical correlator that can be used to perform image searches in the cloud environment via a web browser. This hybrid system employs a simple method to obtain correlation signals and has a distributed network design. The correlation signals are acquired by using an encoder timing signal generated by a rotating disk, and the distributed network design facilitates the replacement and combination of the digital correlation server and the optical correlator.

  13. An X-ray image of the large magellanic cloud

    NASA Technical Reports Server (NTRS)

    Snowden, S. L.; Petre, R.

    1994-01-01

    We have used archival ROSAT Position Sensitive Proportional Counter (PSPC) pointed observations to construct maps of the Large Magellanic Cloud (LMC) in four energy bands between 0.5 and 2.0 keV. These represent the most complete, deepest, and most detailed X-ray images of the LMC to date. While confirming the general morphology of the diffuse LMC emission observed by Wang et al. with Einstein IPC data, these images reveal a wealth of detailed structure of high statistical significance on angular scales from a few arcminutes to a few degrees. In addition, at least twice as many discrete sources are detected as were found using the IPC.

  14. Image Recognition Based on Biometric Pattern Recognition

    NASA Astrophysics Data System (ADS)

    Sun, Shuliang; Chen, Zhong; Liu, Chenglian; Guo, Yongning; Lin, Xueyun

    2011-09-01

    A new method, biomimetric pattern recognition, is mentioned to recognize images. At first, the image is pretreatment and feature extraction, then a high vector is got. A biomimetric pattern recognition model is designed. The judgment function is used to discriminate the classification of the samples. It is showed that the method is effective for little samples by experiment. It would be useful in many fields in future.

  15. Influence of atmospheric circulation patterns on local cloud and solar variability in Bergen, Norway

    NASA Astrophysics Data System (ADS)

    Parding, Kajsa; Olseth, Jan Asle; Liepert, Beate G.; Dagestad, Knut-Frode

    2016-08-01

    In a previous paper, we have shown that long-term cloud and solar observations (1965-2013) in Bergen, Norway (60.39°N, 5.33°E) are compatible with a largely cloud dominated radiative climate. Here, we explicitly address the relationship between the large scale circulation over Europe and local conditions in Bergen, identifying specific circulation shifts that have contributed to the observed cloud and solar variations. As a measure of synoptic weather patterns, we use the Grosswetterlagen (GWL), a daily classification of European weather for 1881-2013. Empirical models of cloud cover, cloud base, relative sunshine duration, and normalised global irradiance are constructed based on the GWL frequencies, extending the observational time series by more than 70 years. The GWL models successfully reproduce the observed increase in cloud cover and decrease in solar irradiance during the 1970s and 1980s. This cloud-induced dimming is traced to an increasing frequency of cyclonic and decreasing frequency of anticyclonic weather patterns over northern Europe. The changing circulation patterns in winter can be understood as a shift from the negative to the positive phase of the North Atlantic and Arctic Oscillation. A recent period of increasing solar irradiance is observed but not reproduce by the GWL models, suggesting this brightening is associated with factors other than large scale atmospheric circulation, possibly decreasing aerosol loads and local cloud shifts.

  16. Enabling outsourcing XDS for imaging on the public cloud.

    PubMed

    Ribeiro, Luís S; Rodrigues, Renato P; Costa, Carlos; Oliveira, José Luís

    2013-01-01

    Picture Archiving and Communication System (PACS) has been the main paradigm in supporting medical imaging workflows during the last decades. Despite its consolidation, the appearance of Cross-Enterprise Document Sharing for imaging (XDS-I), within IHE initiative, constitutes a great opportunity to readapt PACS workflow for inter-institutional data exchange. XDS-I provides a centralized discovery of medical imaging and associated reports. However, the centralized XDS-I actors (document registry and repository) must be deployed in a trustworthy node in order to safeguard patient privacy, data confidentiality and integrity. This paper presents XDS for Protected Imaging (XDS-p), a new approach to XDS-I that is capable of being outsourced (e.g. Cloud Computing) while maintaining privacy, confidentiality, integrity and legal concerns about patients' medical information.

  17. A novel point cloud registration using 2D image features

    NASA Astrophysics Data System (ADS)

    Lin, Chien-Chou; Tai, Yen-Chou; Lee, Jhong-Jin; Chen, Yong-Sheng

    2017-01-01

    Since a 3D scanner only captures a scene of a 3D object at a time, a 3D registration for multi-scene is the key issue of 3D modeling. This paper presents a novel and an efficient 3D registration method based on 2D local feature matching. The proposed method transforms the point clouds into 2D bearing angle images and then uses the 2D feature based matching method, SURF, to find matching pixel pairs between two images. The corresponding points of 3D point clouds can be obtained by those pixel pairs. Since the corresponding pairs are sorted by their distance between matching features, only the top half of the corresponding pairs are used to find the optimal rotation matrix by the least squares approximation. In this paper, the optimal rotation matrix is derived by orthogonal Procrustes method (SVD-based approach). Therefore, the 3D model of an object can be reconstructed by aligning those point clouds with the optimal transformation matrix. Experimental results show that the accuracy of the proposed method is close to the ICP, but the computation cost is reduced significantly. The performance is six times faster than the generalized-ICP algorithm. Furthermore, while the ICP requires high alignment similarity of two scenes, the proposed method is robust to a larger difference of viewing angle.

  18. Imaging sensor constellation for tomographic chemical cloud mapping.

    PubMed

    Cosofret, Bogdan R; Konno, Daisei; Faghfouri, Aram; Kindle, Harry S; Gittins, Christopher M; Finson, Michael L; Janov, Tracy E; Levreault, Mark J; Miyashiro, Rex K; Marinelli, William J

    2009-04-01

    A sensor constellation capable of determining the location and detailed concentration distribution of chemical warfare agent simulant clouds has been developed and demonstrated on government test ranges. The constellation is based on the use of standoff passive multispectral infrared imaging sensors to make column density measurements through the chemical cloud from two or more locations around its periphery. A computed tomography inversion method is employed to produce a 3D concentration profile of the cloud from the 2D line density measurements. We discuss the theoretical basis of the approach and present results of recent field experiments where controlled releases of chemical warfare agent simulants were simultaneously viewed by three chemical imaging sensors. Systematic investigations of the algorithm using synthetic data indicate that for complex functions, 3D reconstruction errors are less than 20% even in the case of a limited three-sensor measurement network. Field data results demonstrate the capability of the constellation to determine 3D concentration profiles that account for ~?86%? of the total known mass of material released.

  19. Analysis of interstellar cloud structure based on IRAS images

    NASA Technical Reports Server (NTRS)

    Scalo, John M.

    1992-01-01

    The goal of this project was to develop new tools for the analysis of the structure of densely sampled maps of interstellar star-forming regions. A particular emphasis was on the recognition and characterization of nested hierarchical structure and fractal irregularity, and their relation to the level of star formation activity. The panoramic IRAS images provided data with the required range in spatial scale, greater than a factor of 100, and in column density, greater than a factor of 50. In order to construct densely sampled column density maps of star-forming clouds, column density images of four nearby cloud complexes were constructed from IRAS data. The regions have various degrees of star formation activity, and most of them have probably not been affected much by the disruptive effects of young massive stars. The largest region, the Scorpius-Ophiuchus cloud complex, covers about 1000 square degrees (it was subdivided into a few smaller regions for analysis). Much of the work during the early part of the project focused on an 80 square degree region in the core of the Taurus complex, a well-studied region of low-mass star formation.

  20. High Quality Typhoon Cloud Image Restoration by Combining Genetic Algorithm with Contourlet Transform

    SciTech Connect

    Zhang Changjiang; Wang Xiaodong

    2008-11-06

    An efficient typhoon cloud image restoration algorithm is proposed. Having implemented contourlet transform to a typhoon cloud image, noise is reduced in the high sub-bands. Weight median value filter is used to reduce the noise in the contourlet domain. Inverse contourlet transform is done to obtain the de-noising image. In order to enhance the global contrast of the typhoon cloud image, in-complete Beta transform (IBT) is used to determine non-linear gray transform curve so as to enhance global contrast for the de-noising typhoon cloud image. Genetic algorithm is used to obtain the optimal gray transform curve. Information entropy is used as the fitness function of the genetic algorithm. Experimental results show that the new algorithm is able to well enhance the global for the typhoon cloud image while well reducing the noises in the typhoon cloud image.

  1. Neptune's wind speeds obtained by tracking clouds in Voyager images

    NASA Technical Reports Server (NTRS)

    Hammel, H. B.; Hansen, C. J.; Johnson, T. V.; Beebe, R. F.; De Jong, E. M.; Howell, C. D.; Ingersoll, A. P.; Limaye, S. S.; Magalhaes, J. A.; Pollack, J. B.

    1989-01-01

    Images of Neptune obtained by the narrow-angle camera of the Voyager 2 spacecraft reveal large-scale cloud features that persist for several months or longer. The features' periods of rotation about the planetary axis range from 15.8 to 18.4 hours. The atmosphere equatorward of -53 deg rotates with periods longer than the 16.05-hour period deduced from Voyager's planetary radio astronomy experiment (presumably the planet's internal rotation period). The wind speeds computed with respect to this radio period range from 20 meters per second eastward to 325 meters per second westward. Thus, the cloud-top wind speeds are roughly the same for all the planets ranging from Venus to Neptune, even though the solar energy inputs to the atmospheres vary by a factor of 1000.

  2. Research on texture feature of RS image based on cloud model

    NASA Astrophysics Data System (ADS)

    Wang, Zuocheng; Xue, Lixia

    2008-10-01

    This paper presents a new method applied to texture feature representation in RS image based on cloud model. Aiming at the fuzziness and randomness of RS image, we introduce the cloud theory into RS image processing in a creative way. The digital characteristics of clouds well integrate the fuzziness and randomness of linguistic terms in a unified way and map the quantitative and qualitative concepts. We adopt texture multi-dimensions cloud to accomplish vagueness and randomness handling of texture feature in RS image. The method has two steps: 1) Correlativity analyzing of texture statistical parameters in Grey Level Co-occurrence Matrix (GLCM) and parameters fuzzification. GLCM can be used to representing the texture feature in many aspects perfectly. According to the expressive force of texture statistical parameters and by Correlativity analyzing of texture statistical parameters, we can abstract a few texture statistical parameters that can best represent the texture feature. By the fuzziness algorithm, the texture statistical parameters can be mapped to fuzzy cloud space. 2) Texture multi-dimensions cloud model constructing. Based on the abstracted texture statistical parameters and fuzziness cloud space, texture multi-dimensions cloud model can be constructed in micro-windows of image. According to the membership of texture statistical parameters, we can achieve the samples of cloud-drop. By backward cloud generator, the digital characteristics of texture multi-dimensions cloud model can be achieved and the Mathematical Expected Hyper Surface(MEHS) of multi-dimensions cloud of micro-windows can be constructed. At last, the weighted sum of the 3 digital characteristics of micro-window cloud model was proposed and used in texture representing in RS image. The method we develop is demonstrated by applying it to texture representing in many RS images, various performance studies testify that the method is both efficient and effective. It enriches the cloud

  3. A Routing Mechanism for Cloud Outsourcing of Medical Imaging Repositories.

    PubMed

    Godinho, Tiago Marques; Viana-Ferreira, Carlos; Bastião Silva, Luís A; Costa, Carlos

    2016-01-01

    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 digital imaging and communications in medicine 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.

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

    NASA Astrophysics Data System (ADS)

    Diner, David

    2010-05-01

    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

  5. Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

    NASA Astrophysics Data System (ADS)

    Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

    2016-04-01

    The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

  6. Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications

    USGS Publications Warehouse

    Rastogi, Bharat; Williams, A. Park; Fischer, Douglas T.; Iacobellis, Sam F.; McEachern, Kathryn; Carvalho, Leila; Jones, Charles Leslie; Baguskas, Sara A.; Still, Christopher J.

    2016-01-01

    The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.

  7. ESA's Ice Cloud Imager on Metop Second Generation

    NASA Astrophysics Data System (ADS)

    Klein, Ulf; Loiselet, Marc; Mason, Graeme; Gonzalez, Raquel; Brandt, Michael

    2016-04-01

    Since 2006, the European contribution to operational meteorological observations from polar orbit has been provided by the Meteorological Operational (MetOp) satellites, which is the space segment of the EUMETSAT Polar System (EPS). The first MetOp satellite was launched in 2006, 2nd 2012 and 3rd satellite is planned for launch in 2018. As part of the next generation EUMETSAT Polar System (EPS-SG), the MetOp Second Generation (MetOp-SG) satellites will provide continuity and enhancement of these observations in the 2021 - 2042 timeframe. The noel Ice Cloud Imager (ICI) is one of the instruments selected to be on-board the MetOp-SG satellite "B". The main objective of the ICI is to enable cloud ice retrieval, with emphasis on cirrus clouds. ICI will provide information on cloud ice mean altitude, cloud ice water path and cloud ice effective radius. In addition, it will provide water vapour profile measurement capability. ICI is a 13-channel microwave/sub-millimetre wave radiometer, covering the frequency range from 183 GHz up to 664 GHz. The instrument is composed of a rotating part and a fixed part. The rotating part includes the main antenna, the feed assembly and the receiver electronics. The fixed part contains the hot calibration target, the reflector for viewing the cold sky and the electronics for the instrument control and interface with the platform. Between the fixed and the rotating part is the scan mechanism. Scan mechanism is not only responsible of rotating the instrument and providing its angular position, but it will also have pass through the power and data lines. The Scan mechanism is controlled by the fully redundant Control and Drive Electronics ICI is calibrated using an internal hot target and a cold sky mirror, which are viewed once per rotation. The internal hot target is a traditional pyramidal target. The hot target is covered by an annular shield during rotation with only a small opening for the feed horns to guarantee a stable environment

  8. Multiscale image enhancement of chromosome banding patterns

    NASA Astrophysics Data System (ADS)

    Wu, Qiang; Castleman, Kenneth R.

    1996-10-01

    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.

  9. Image transfer through cirrus clouds. I. Ray trace analysis and wave-front reconstruction.

    PubMed

    Landesman, B T; Kindilien, P J; Matson, C L; Caudill, T R

    2000-10-20

    A new technique for modeling image transfer through cirrus clouds is presented. The technique uses a ray trace to model beam propagation through a three-dimensional volume of polydisperse, hexagonal ice crystals. Beyond the cloud, the technique makes use of standard Huygens-Fresnel propagation methods. At the air-cloud interface, each wave front is resolved into a ray distribution for input to the ray trace software. Similarly, a wave front is reconstructed from the output ray distribution at the cloud-air interface. Simulation output from the ray trace program is presented and the modulation transfer function for stars imaged through cirrus clouds of varying depths is discussed.

  10. Statistical pattern recognition for rock joint images

    NASA Astrophysics Data System (ADS)

    Wang, Weixing; Bin, Cui

    2005-10-01

    As a cooperation project between Sweden and China, we sampled a number of rock specimens for analyze rock fracture network by optical image technique. The samples are resin injected, in which way; opened fractures can be seen clearly by means of UV (Ultraviolet) light illumination. In the study period, Recognition of rock fractures is crucial in many rock engineering applications. In order to successfully applying automatic image processing techniques for the problem of automatic (or semi-automatic) rock fracture detection and description, the key (and hardest task) is the automatic detection of fractures robustly in images. When statistical pattern recognition is used to segment a rock joint color image, features of different samples can be learned first, then, each pixel of the image is classified by these features. As the testing result showing, an attribute rock fracture image is segmented satisfactorily by using this way. The method can be widely used for other complicated images too. In this paper, Kernel Fisher discrimination (KFD) is employed to construct a statistical pattern recognition classifier. KFD can transform nonlinear discrimination in an attribute space with high dimension, into linear discrimination in a feature space with low dimension. While one needs not know the detailed mapping form from attribute space to feature space in the process of transformation. It is proved that this method performs well by segmenting complicated rock joint color images.

  11. Ice Cloud Optical Depth Retrievals from CRISM Multispectral Images

    NASA Astrophysics Data System (ADS)

    Klassen, David R.

    2014-11-01

    One set of data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on the Mars Reconnaissance Orbiter (MRO) is the multispectral survey that measured the visible-through-near-infrared reflectance of the entire planet of Mars at specific wavelengths. The spectral data from several sols were be combined to create multi-spectral maps of Mars. In addition, these maps can be zonally averaged to create a latitude vs season image cube of Mars. All of these image cubes can be fit using a full radiative transfer modeling in order to retrieve ice cloud optical depth—as a map for one of the particular dates, or as a latitude vs season record.To compare the data radiative transfer models, a measure of the actual surface reflectance is needed. There are several possible ways to model this, such as using a nearby region that is "close enough" or by looking at the same region at different times and assuming one of those is the actual surface reflectance. Neither of these is ideal for trying to process an entire map of data because aerosol clouds can be fairly extensive both spatially and temporally.Another technique is to assume that the surface can be modeled as a linear combination of a limited set of intrinsic spectral endmembers. A combination of Principal Component Analysis (PCA) and Target Transformation (TT) has been used to recover just such a set of spectral endmember shapes. The coefficients in the linear combination then become additional fitting parameters in the radiative transfer modeling of each map point—all parameters are adjusted until the RMS error between the model and the data is minimized. Based on previous work, the PCA of martian spectral image cubes is relatively consistent regardless of season, implying the underlying, large-scale, intrinsic traits that dominate the data variance are relatively constant. These overall PCA results can then be used to create a single set of spectral endmembers that can be used for any of the data

  12. Medical image segmentation using object atlas versus object cloud models

    NASA Astrophysics Data System (ADS)

    Phellan, Renzo; Falcão, Alexandre X.; Udupa, Jayaram K.

    2015-03-01

    Medical image segmentation is crucial for quantitative organ analysis and surgical planning. Since interactive segmentation is not practical in a production-mode clinical setting, automatic methods based on 3D object appearance models have been proposed. Among them, approaches based on object atlas are the most actively investigated. A key drawback of these approaches is that they require a time-costly image registration process to build and deploy the atlas. Object cloud models (OCM) have been introduced to avoid registration, considerably speeding up the whole process, but they have not been compared to object atlas models (OAM). The present paper fills this gap by presenting a comparative analysis of the two approaches in the task of individually segmenting nine anatomical structures of the human body. Our results indicate that OCM achieve a statistically significant better accuracy for seven anatomical structures, in terms of Dice Similarity Coefficient and Average Symmetric Surface Distance.

  13. Deployment of the third-generation infrared cloud imager: A two-year study of Arctic clouds at Barrow, Alaska

    NASA Astrophysics Data System (ADS)

    Nugent, Paul Winston

    Cloud cover is an important but poorly understood component of current climate models, and although climate change is most easily observed in the Arctic, cloud data in the Arctic is unreliable or simply unavailable. Ground-based infrared cloud imaging has the potential to fill this gap. This technique uses a thermal infrared camera to observe cloud amount, cloud optical depth, and cloud spatial distribution at a particular location. The Montana State University Optical Remote Sensor Laboratory has developed the ground-based Infrared Cloud Imager (ICI) instrument to measure spatial and temporal cloud data. To build an ICI for Arctic sites required the system to be engineered to overcome the challenges of this environment. Of particular challenge was keeping the system calibration and data processing accurate through the severe temperature changes. Another significant challenge was that weak emission from the cold, dry Arctic atmosphere pushed the camera used in the instrument to its operational limits. To gain an understanding of the operation of the ICI systems for the Arctic and to gather critical data on Arctic clouds, a prototype arctic ICI was deployed in Barrow, AK from July 2012 through July 2014. To understand the long-term operation of an ICI in the arctic, a study was conducted of the ICI system accuracy in relation to co-located active and passive sensors. Understanding the operation of this system in the Arctic environment required careful characterization of the full optical system, including the lens, filter, and detector. Alternative data processing techniques using decision trees and support vector machines were studied to improve data accuracy and reduce dependence on auxiliary instrument data and the resulting accuracy is reported here. The work described in this project was part of the effort to develop a fourth-generation ICI ready to be deployed in the Arctic. This system will serve a critical role in developing our understanding of cloud cover

  14. Congruence analysis of point clouds from unstable stereo image sequences

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

    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.

  15. A structural-stochastic model for the analysis and synthesis of cloud images

    NASA Technical Reports Server (NTRS)

    Garand, L.; Weinman, J. A.

    1986-01-01

    A structural-stochastic image model is developed for the analysis and synthesis of cloud images. The ability of the model to characterize the visual appearance of cloud fields observed by satellite with a limited number of parameters is demonstrated. The model merges structural and stochastic information, the stochastic model acting as a local statistical operator applied to the output of the structural model. The structural or large-scale organization of the scene is retrieved from the two-dimensional Fourier representation of the digital image. The pattern generated by the major Fourier components provides a first guess of the scene. The stochastic aspect is described by a Markov model of texture that assumes a binomial probability distribution for the local grey-level variability. This Markov model provides four parameters that represent the clustering strength in the horizontal, vertical and diagonal directions. These parameters are estimated by a standard maximum-likelihood technique. The image can be reproduced with a fair degree of verisimilitude from these parameters. The data compression factor is of the order of one hundred to several hundreds.

  16. LIDAR vs dense image matching point clouds in complex urban scenes

    NASA Astrophysics Data System (ADS)

    Maltezos, Evangelos; Kyrkou, Athanasia; Ioannidis, Charalabos

    2016-08-01

    This study aims to highlight the differences, in terms of robustness and efficiency, of the use of LIDAR point clouds compared to dense image matching (DIM) point clouds at urban areas that contain buildings with complex structure. The application is conducted over an area in the Greek island of Milos using two different types of data: (a) a dense point cloud which extracted by DIM using a variation of the stereo-method semi-global matching (SGM) at RGB digital aerial images, and (b) a georeferenced LIDAR point cloud. For the case of the DIM point cloud, the following steps were applied: aerial triangulation, rectification of the original images to epipolar images, extraction of disparity maps and application of a 3D similarity transformation. The evaluations that were executed included urban and rural areas. At first step, a direct cloud-to-cloud comparison between the georeferenced DIM and LIDAR point clouds was carried out. Then, the corresponding orthoimages generated by the DIM and LIDAR point clouds undergo a quality control. Although the results show that the LIDAR point clouds respond better at such complex scenes compared to DIM point clouds, the latter gave promising results. In this context, the Quality Assurance issue is also discussed so as to be more efficient towards the challenge of the increasingly greater demands for accurate and cost effective applications.

  17. Microwave Imager Measures Sea Surface Temperature Through Clouds

    NASA Technical Reports Server (NTRS)

    2002-01-01

    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

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    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.

  19. Astronomy In The Cloud: Using Mapreduce For Image Coaddition

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

    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

  20. Whole Sky Imager Characterization of Sky Obscuration by Clouds for the Starfire Optical Range

    DTIC Science & Technology

    2010-01-11

    good. Figure 27 shows a typical time series for scattered opaque clouds , and Figure 28 shows an example of contrails forming into cirrus . It...ATMOSPHERIC OPTICS GROUP January 2010 Scientific Report on Whole Sky Imager Characterization Of Sky Obscuration by Clouds For...08-10/1/09 Scientific Report on the Whole Sky Imager Characterization of Sky Obscuration by Clouds for the Starfire Optical Range FA9451-008-C-0226

  1. Automatic seagrass pattern identification on sonar images

    NASA Astrophysics Data System (ADS)

    Rahnemoonfar, Maryam; Rahman, Abdullah

    2016-05-01

    Natural and human-induced disturbances are resulting in degradation and loss of seagrass. Freshwater flooding, severe meteorological events and invasive species are among the major natural disturbances. Human-induced disturbances are mainly due to boat propeller scars in the shallow seagrass meadows and anchor scars in the deeper areas. Therefore, there is a vital need to map seagrass ecosystems in order to determine worldwide abundance and distribution. Currently there is no established method for mapping the pothole or scars in seagrass. One of the most precise sensors to map the seagrass disturbance is side scan sonar. Here we propose an automatic method which detects seagrass potholes in sonar images. Side scan sonar images are notorious for having speckle noise and uneven illumination across the image. Moreover, disturbance presents complex patterns where most segmentation techniques will fail. In this paper, by applying mathematical morphology technique and calculating the local standard deviation of the image, the images were enhanced and the pothole patterns were identified. The proposed method was applied on sonar images taken from Laguna Madre in Texas. Experimental results show the effectiveness of the proposed method.

  2. New cloud free line of sight statistics measured with digital whole sky imagers

    NASA Astrophysics Data System (ADS)

    Shields, Janet E.; Burden, Art R.; Johnson, Richard W.; Karr, Monette E.; Baker, Justin G.

    2005-08-01

    Cloud Free Line of Sight (CFLOS) statistics can be important to a number of applications involving transmittance of light through the atmosphere, including laser propagation, light propagation, and detection of objects by humans and instruments. This paper will discuss Cloud Free Line of Sight (CFLOS) and cloud persistence statistics determined from cloud measurements taken with Whole Sky Imagers (WSI). The WSIs are ground-based digital imaging systems that image the full upper hemisphere down to the horizon in wavebands in the visible and NIR. Digital automated WSI systems were originally developed by the Marine Physical Lab in the 1980's to address the CFLOS application, and then further developed for 24-hour day and night capability. Approximately three million image sets have been acquired with the Day/Night WSI in conjunction with DOE's ARM program. Recent advances in the cloud decision algorithms at Marine Physical Lab have enabled the extraction of processed cloud images of sufficient quality to obtain reliable cloud statistics. A test sample of approximately 4500 image sets has been processed to yield CFLOS statistics down to the horizon, as well as statistics related to the persistence of clouds and cloud holes. This talk will provide a brief overview of the instruments and current algorithm developments. The CFLOS results and sample persistence results will be presented.

  3. Visual pattern degradation based image quality assessment

    NASA Astrophysics Data System (ADS)

    Wu, Jinjian; Li, Leida; Shi, Guangming; Lin, Weisi; Wan, Wenfei

    2015-08-01

    In this paper, we introduce a visual pattern degradation based full-reference (FR) image quality assessment (IQA) method. Researches on visual recognition indicate that the human visual system (HVS) is highly adaptive to extract visual structures for scene understanding. Existing structure degradation based IQA methods mainly take local luminance contrast to represent structure, and measure quality as degradation on luminance contrast. In this paper, we suggest that structure includes not only luminance contrast but also orientation information. Therefore, we analyze the orientation characteristic for structure description. Inspired by the orientation selectivity mechanism in the primary visual cortex, we introduce a novel visual pattern to represent the structure of a local region. Then, the quality is measured as the degradations on both luminance contrast and visual pattern. Experimental results on Five benchmark databases demonstrate that the proposed visual pattern can effectively represent visual structure and the proposed IQA method performs better than the existing IQA metrics.

  4. Determination of cloud and aerosol layers using CALIPSO and image processing

    NASA Astrophysics Data System (ADS)

    Alias, A. N.; MatJafri, M. Z.; Lim, H. S.; Abdullah, K.; Saleh, N. Mohd.

    2008-10-01

    The height of cloud and aerosol layers in the atmosphere is believed to affect climate change and air pollution because both of them have important direct effects on the radiation balance of the earth. In this paper, we study the ability of Cloud Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) data to detect, locate and distinguish between cloud and aerosol layers in the atmosphere over Peninsula Malaysia. We also used image processing technique to differentiate between cloud and aerosol layers from the CALIPSO images. The cloud and aerosol layers mostly are seen at troposphere (>10 km) and lower stratosphere (>15km). The results shows that CALIPSO can be used to determine cloud and aerosol layers and image processing technique has successfully distinguished them in the atmosphere.

  5. Cloud Arcs

    Atmospheric Science Data Center

    2013-04-19

    ... 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 ...

  6. Automatic cloud detection for high resolution satellite stereo images and its application in terrain extraction

    NASA Astrophysics Data System (ADS)

    Wu, Teng; Hu, Xiangyun; Zhang, Yong; Zhang, Lulin; Tao, Pengjie; Lu, Luping

    2016-11-01

    The automatic extraction of terrain from high-resolution satellite optical images is very difficult under cloudy conditions. Therefore, accurate cloud detection is necessary to fully use the cloud-free parts of images for terrain extraction. This paper addresses automated cloud detection by introducing an image matching based method under a stereo vision framework, and the optimization usage of non-cloudy areas in stereo matching and the generation of digital surface models (DSMs). Given that clouds are often separated from the terrain surface, cloudy areas are extracted by integrating dense matching DSM, worldwide digital elevation model (DEM) (i.e., shuttle radar topography mission (SRTM)) and gray information from the images. This process consists of the following steps: an image based DSM is firstly generated through a multiple primitive multi-image matcher. Once it is aligned with the reference DEM based on common features, places with significant height differences between the DSM and the DEM will suggest the potential cloud covers. Detecting cloud at these places in the images then enables precise cloud delineation. In the final step, elevations of the reference DEM within the cloud covers are assigned to the corresponding region of the DSM to generate a cloud-free DEM. The proposed approach is evaluated with the panchromatic images of the Tianhui satellite and has been successfully used in its daily operation. The cloud detection accuracy for images without snow is as high as 95%. Experimental results demonstrate that the proposed method can significantly improve the usage of the cloudy panchromatic satellite images for terrain extraction.

  7. 3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

    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.

  8. Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

    PubMed

    Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

    2015-02-10

    Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

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

    NASA Astrophysics Data System (ADS)

    Fuchs, Julia; Bendix, Jörg; Cermak, Jan

    2013-04-01

    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

  10. An effective thin cloud removal procedure for visible remote sensing images

    NASA Astrophysics Data System (ADS)

    Shen, Huanfeng; Li, Huifang; Qian, Yan; Zhang, Liangpei; Yuan, Qiangqiang

    2014-10-01

    Clouds are obstructions for land-surface observation, which result in the regional information being blurred or even lost. Thin clouds are transparent, and images of regions covered by thin clouds contain information about both the atmosphere and the ground. Therefore, thin cloud removal is a challenging task as the ground information is easily affected when the thin cloud removal is performed. An efficient and effective thin cloud removal method is proposed for visible remote sensing images in this paper, with the aim being to remove the thin clouds and also restore the ground information. Since thin cloud is considered as low-frequency information, the proposed method is based on the classic homomorphic filter and is executed in the frequency domain. The optimal cut-off frequency for each channel is determined semi-automatically. In order to preserve the clear pixels and ensure the high fidelity of the result, cloudy pixels are detected and handled separately. As a particular kind of low-frequency information, cloud-free water surfaces are specially treated and corrected. Since only cloudy pixels are involved in the calculation, the method is highly efficient and is suited for large remote sensing scenes. Scenes including different land-cover types were selected to validate the proposed method, and a comparison analysis with other methods was also performed. The experimental results confirm that the proposed method is effective in correcting thin cloud contaminated images while preserving the true spectral information.

  11. How consistent are precipitation patterns predicted by GCMs in the absence of cloud radiative effects?

    NASA Astrophysics Data System (ADS)

    Popke, Dagmar; Bony, Sandrine; Mauritsen, Thorsten; Stevens, Bjorn

    2015-04-01

    Model simulations with state-of-the-art general circulation models reveal a strong disagreement concerning the simulated regional precipitation patterns and their changes with warming. The deviating precipitation response even persists when reducing the model experiment complexity to aquaplanet simulation with forced sea surface temperatures (Stevens and Bony, 2013). To assess feedbacks between clouds and radiation on precipitation responses we analyze data from 5 models performing the aquaplanet simulations of the Clouds On Off Klima Intercomparison Experiment (COOKIE), where the interaction of clouds and radiation is inhibited. Although cloud radiative effects are then disabled, the precipitation patterns among models are as diverse as with cloud radiative effects switched on. Disentangling differing model responses in such simplified experiments thus appears to be key to better understanding the simulated regional precipitation in more standard configurations. By analyzing the local moisture and moist static energy budgets in the COOKIE experiments we investigate likely causes for the disagreement among models. References Stevens, B. & S. Bony: What Are Climate Models Missing?, Science, 2013, 340, 1053-1054

  12. OpenID connect as a security service in Cloud-based diagnostic imaging systems

    NASA Astrophysics Data System (ADS)

    Ma, Weina; Sartipi, Kamran; Sharghi, Hassan; Koff, David; Bak, Peter

    2015-03-01

    The evolution of cloud computing is driving the next generation of diagnostic imaging (DI) systems. Cloud-based DI systems are able to deliver better services to patients without constraining to their own physical facilities. However, privacy and security concerns have been consistently regarded as the major obstacle for adoption of cloud computing by healthcare domains. Furthermore, traditional computing models and interfaces employed by DI systems are not ready for accessing diagnostic images through mobile devices. RESTful is an ideal technology for provisioning both mobile services and cloud computing. OpenID Connect, combining OpenID and OAuth together, is an emerging REST-based federated identity solution. It is one of the most perspective open standards to potentially become the de-facto standard for securing cloud computing and mobile applications, which has ever been regarded as "Kerberos of Cloud". We introduce OpenID Connect as an identity and authentication service in cloud-based DI systems and propose enhancements that allow for incorporating this technology within distributed enterprise environment. The objective of this study is to offer solutions for secure radiology image sharing among DI-r (Diagnostic Imaging Repository) and heterogeneous PACS (Picture Archiving and Communication Systems) as well as mobile clients in the cloud ecosystem. Through using OpenID Connect as an open-source identity and authentication service, deploying DI-r and PACS to private or community clouds should obtain equivalent security level to traditional computing model.

  13. Atmospheric Polarization Imaging with Variable Aerosols and Clouds

    DTIC Science & Technology

    2010-12-10

    made at the Mauna Loa Observatory (a mountaintop observatory in Hawaii) confirmed previous studies by Coulson and extended them to partly cloudy...grant: 1. Mr. Andrew Dahlberg – All-sky polarization imager deployment at Mauna Loa Observatory , Hawaii – M.S. Thesis, May 2010 (http...surface albedo appear to explain a morning-to-afternoon asymmetry in the observed polarization pattern in the sky above the Mauna Loa Observatory on the

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

    NASA Technical Reports Server (NTRS)

    Smith, William L.; Ebert, Elizabeth

    1990-01-01

    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

  15. Exploration for Improving the Efficiency of Photoelectric Telescope with the Cloud Imager

    NASA Astrophysics Data System (ADS)

    Fan, L.; Lei, C. M.

    2016-07-01

    The photoelectric telescope tracks space debris with the catalog. But for the night sky under cloud cover, it can not adjust the observation sequence according to the real-time cloud distribution, which results in a waste of telescope resources, and a decrease in the quantity of detected objects. The cloud imager is used for the real-time acquisition of all-sky infrared cloud image, and the observational scheduling strategy of telescope is optimized by determining the clouds' distribution and position. Optimized scheduling strategy is benefit for the telescope to shoot through the smallest breaks under cloud cover, allowing the observations to be carried out in the weather conditions previously thought to be too bad. Experimental tests show that the optimized scheduling strategy is feasible. It can make full use of existing resources, and significantly improve the efficiency of observation equipment.

  16. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE PAGES

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  17. A Data-Driven Point Cloud Simplification Framework for City-Scale Image-Based Localization.

    PubMed

    Cheng, Wentao; Lin, Weisi; Zhang, Xinfeng; Goesele, Michael; Sun, Ming-Ting

    2017-01-01

    City-scale 3D point clouds reconstructed via structure-from-motion from a large collection of Internet images are widely used in the image-based localization task to estimate a 6-DOF camera pose of a query image. Due to prohibitive memory footprint of city-scale point clouds, image-based localization is difficult to be implemented on devices with limited memory resources. Point cloud simplification aims to select a subset of points to achieve a comparable localization performance using the original point cloud. In this paper, we propose a data-driven point cloud simplification framework by taking it as a weighted K-Cover problem, which mainly includes two complementary parts. First, a utility-based parameter determination method is proposed to select a reasonable parameter K for K-Cover-based approaches by evaluating the potential of a point cloud for establishing sufficient 2D-3D feature correspondences. Second, we formulate the 3D point cloud simplification problem as a weighted K-Cover problem, and propose an adaptive exponential weight function based on the visibility probability of 3D points. The experimental results on three popular datasets demonstrate that the proposed point cloud simplification framework outperforms the state-of-the-art methods for the image-based localization application with a well predicted parameter in the K-Cover problem.

  18. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  19. Cloud top structure of Venus revealed by Subaru/COMICS mid-infrared images

    NASA Astrophysics Data System (ADS)

    Sato, T. M.; Sagawa, H.; Kouyama, T.; Mitsuyama, K.; Satoh, T.; Ohtsuki, S.; Ueno, M.; Kasaba, Y.; Nakamura, M.; Imamura, T.

    2014-11-01

    We have investigated the cloud top structure of Venus by analyzing ground-based images taken at the mid-infrared wavelengths of 8.66 μm and 11.34 μm. Venus at a solar phase angle of ∼90°, with the morning terminator in view, was observed by the Cooled Mid-Infrared Camera and Spectrometer (COMICS), mounted on the 8.2-m Subaru Telescope, during the period October 25-29, 2007. The disk-averaged brightness temperatures for the observation period are ∼230 K and ∼238 K at 8.66 μm and 11.34 μm, respectively. The obtained images with good signal-to-noise ratio and with high spatial resolution (∼200 km at the sub-observer point) provide several important findings. First, we present observational evidence, for the first time, of the possibility that the westward rotation of the polar features (the hot polar spots and the surrounding cold collars) is synchronized between the northern and southern hemispheres. Second, after high-pass filtering, the images reveal that streaks and mottled and patchy patterns are distributed over the entire disk, with typical amplitudes of ∼0.5 K, and vary from day to day. The detected features, some of which are similar to those seen in past UV images, result from inhomogeneities of both the temperature and the cloud top altitude. Third, the equatorial center-to-limb variations of brightness temperatures have a systematic day-night asymmetry, except those on October 25, that the dayside brightness temperatures are higher than the nightside brightness temperatures by 0-4 K under the same viewing geometry. Such asymmetry would be caused by the propagation of the migrating semidiurnal tide. Finally, by applying the lapse rates deduced from previous studies, we demonstrate that the equatorial center-to-limb curves in the two spectral channels give access to two parameters: the cloud scale height H and the cloud top altitude zc. The acceptable models for data on October 25 are obtained at H = 2.4-4.3 km and zc = 66-69 km; this supports

  20. Characterization of SEM speckle pattern marking and imaging distortion by digital image correlation

    NASA Astrophysics Data System (ADS)

    Guery, Adrien; Latourte, Félix; Hild, François; Roux, Stéphane

    2014-01-01

    Surface patterning by e-beam lithography and scanning electron microscope (SEM) imaging distortions are studied via digital image correlation. The global distortions from the reference pattern, which has been numerically generated, are first quantified from a digital image correlation procedure between the (virtual) reference pattern and the actual SEM image both in secondary and backscattered electron imaging modes. These distortions result from both patterning and imaging techniques. These two contributions can be separated (without resorting to an external caliper) based on the images of the same patterned surface acquired at different orientations. Patterning distortions are much smaller than those due to imaging on wide field images.

  1. Accuracy assessment of building point clouds automatically generated from iphone images

    NASA Astrophysics Data System (ADS)

    Sirmacek, B.; Lindenbergh, R.

    2014-06-01

    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 (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 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.

  2. Improving Assimilation of Microwave Radiances in Cloudy Situations with Collocated High Resolution Imager Cloud Mask

    NASA Astrophysics Data System (ADS)

    Han, H.; Li, J.; Goldberg, M.; Wang, P.; Li, Z.

    2014-12-01

    Tropical cyclones (TCs) accompanied with heavy rainfall and strong wind are high impact weather systems, often causing extensive property damage and even fatalities when landed. Better prediction of TCs can lead to substantial reduction of social and economic damage; there are growing interests in the enhanced satellite data assimilation for improving TC forecasts. Accurate cloud detection is one of the most important factors in satellite data assimilation due to the uncertainties of cloud properties and their impacts on satellite observed radiances. To enhance the accuracy of cloud detection and improve the TC forecasting, microwave measurements are collocated with high spatial resolution imager cloud mask. The collocated advanced microwave sounder measurements are assimilated for the hurricane Sandy (2012) and typhoon Haiyan (2013) forecasting using the Weather Research and Forecasting (WRF) model and the 3DVAR-based Gridpoint Statistical Interpolation (GSI) data assimilation system. Experiments will be carried out to determine a cloud cover threshold to distinguish between cloud affected and cloud unaffected footprints. The results indicate that the use of the high spatial resolution imager cloud mask can improve the accuracy of TC forecasts by eliminating cloud contaminated pixels. The methodology used in this study is applicable to advanced microwave sounders and high spatial resolution imagers, such as ATMS/VIIRS onboard NPP and JPSS, and IASI/AVHRR from Metop, for the improved TC track and intensity forecasts.

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

    PubMed

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

    2013-01-01

    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.

  4. Statistical pattern recognition algorithms for autofluorescence imaging

    NASA Astrophysics Data System (ADS)

    Kulas, Zbigniew; Bereś-Pawlik, Elżbieta; Wierzbicki, Jarosław

    2009-02-01

    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.

  5. Interpretation techniques. [image enhancement and pattern recognition

    NASA Technical Reports Server (NTRS)

    Dragg, J. L.

    1974-01-01

    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.

  6. Prediction of optical communication link availability: real-time observation of cloud patterns using a ground-based thermal infrared camera

    NASA Astrophysics Data System (ADS)

    Bertin, Clément; Cros, Sylvain; Saint-Antonin, Laurent; Schmutz, Nicolas

    2015-10-01

    The growing demand for high-speed broadband communications with low orbital or geostationary satellites is a major challenge. Using an optical link at 1.55 μm is an advantageous solution which potentially can increase the satellite throughput by a factor 10. Nevertheless, cloud cover is an obstacle for this optical frequency. Such communication requires an innovative management system to optimize the optical link availability between a satellite and several Optical Ground Stations (OGS). The Saint-Exupery Technological Research Institute (France) leads the project ALBS (French acronym for BroadBand Satellite Access). This initiative involving small and medium enterprises, industrial groups and research institutions specialized in aeronautics and space industries, is currently developing various solutions to increase the telecommunication satellite bandwidth. This paper presents the development of a preliminary prediction system preventing the cloud blockage of an optical link between a satellite and a given OGS. An infrared thermal camera continuously observes (night and day) the sky vault. Cloud patterns are observed and classified several times a minute. The impact of the detected clouds on the optical beam (obstruction or not) is determined by the retrieval of the cloud optical depth at the wavelength of communication. This retrieval is based on realistic cloud-modelling on libRadtran. Then, using subsequent images, cloud speed and trajectory are estimated. Cloud blockage over an OGS can then be forecast up to 30 minutes ahead. With this information, the preparation of the new link between the satellite and another OGS under a clear sky can be prepared before the link breaks due to cloud blockage.

  7. A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

    PubMed

    Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

    2015-01-01

    The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

  8. Image pattern recognition supporting interactive analysis and graphical visualization

    NASA Technical Reports Server (NTRS)

    Coggins, James M.

    1992-01-01

    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.

  9. Imaging fictive locomotor patterns in larval Drosophila

    PubMed Central

    Bayley, Timothy G.; Taylor, Adam L.; Berni, Jimena; Bate, Michael; Hedwig, Berthold

    2015-01-01

    We have established a preparation in larval Drosophila to monitor fictive locomotion simultaneously across abdominal and thoracic segments of the isolated CNS with genetically encoded Ca2+ indicators. The Ca2+ signals closely followed spiking activity measured electrophysiologically in nerve roots. Three motor patterns are analyzed. Two comprise waves of Ca2+ signals that progress along the longitudinal body axis in a posterior-to-anterior or anterior-to-posterior direction. These waves had statistically indistinguishable intersegmental phase delays compared with segmental contractions during forward and backward crawling behavior, despite being ∼10 times slower. During these waves, motor neurons of the dorsal longitudinal and transverse muscles were active in the same order as the muscle groups are recruited during crawling behavior. A third fictive motor pattern exhibits a left-right asymmetry across segments and bears similarities with turning behavior in intact larvae, occurring equally frequently and involving asymmetry in the same segments. Ablation of the segments in which forward and backward waves of Ca2+ signals were normally initiated did not eliminate production of Ca2+ waves. When the brain and subesophageal ganglion (SOG) were removed, the remaining ganglia retained the ability to produce both forward and backward waves of motor activity, although the speed and frequency of waves changed. Bilateral asymmetry of activity was reduced when the brain was removed and abolished when the SOG was removed. This work paves the way to studying the neural and genetic underpinnings of segmentally coordinated motor pattern generation in Drosophila with imaging techniques. PMID:26311188

  10. Advanced infrared sounder subpixel cloud detection with imagers and its impact on radiance assimilation in NWP

    NASA Astrophysics Data System (ADS)

    Wang, Pei; Li, Jun; Li, Jinlong; Li, Zhenglong; Schmit, Timothy J.; Bai, Wenguang

    2014-03-01

    Accurate cloud detection is very important for infrared (IR) radiance assimilation; improved cloud detection could reduce cloud contamination and hence improve the assimilation. Although operational numerical weather prediction (NWP) centers are using IR sounder radiance data for cloud detection, collocated high spatial resolution imager data could help sounder subpixel cloud detection and characterization. IR sounder radiances with improved cloud detection using Atmospheric Infrared Sounder (AIRS)/Moderate Resolution Imaging Spectroradiometer (MODIS) were assimilated for Hurricane Sandy (2012). Forecast experiments were run with Weather Research and Forecasting (WRF) as the forecast model and the Three-Dimensional Variational Assimilation (3DVAR)-based Gridpoint Statistical Interpolation (GSI) as the analysis system. Results indicate that forecasts of both hurricane track and intensity are substantially improved when the collocated high spatial resolution MODIS cloud mask is used for AIRS subpixel cloud detection for assimilating radiances. This methodology can be applied to process Crosstrack Infrared Sounder (CRIS)/Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi-NPOESS Preparatory Project (NPP)/Joint Polar Satellite System (JPSS) and Infrared Atmospheric Sounding Interferometer (IASI)/Advanced Very High Resolution Radiometer (AVHRR) onboard the Metop series for improved radiance assimilation in NWP.

  11. Cloud Removal from SENTINEL-2 Image Time Series Through Sparse Reconstruction from Random Samples

    NASA Astrophysics Data System (ADS)

    Cerra, D.; Bieniarz, J.; Müller, R.; Reinartz, P.

    2016-06-01

    In this paper we propose a cloud removal algorithm for scenes within a Sentinel-2 satellite image time series based on synthetisation of the affected areas via sparse reconstruction. For this purpose, a clouds and clouds shadow mask must be given. With respect to previous works, the process has an increased automation degree. Several dictionaries, on the basis of which the data are reconstructed, are selected randomly from cloud-free areas around the cloud, and for each pixel the dictionary yielding the smallest reconstruction error in non-corrupted images is chosen for the restoration. The values below a cloudy area are therefore estimated by observing the spectral evolution in time of the non-corrupted pixels around it. The proposed restoration algorithm is fast and efficient, requires minimal supervision and yield results with low overall radiometric and spectral distortions.

  12. University of California, San Diego (UCSD) Sky Imager Cloud Position Study Field Campaign Report

    SciTech Connect

    Kleissl, J.; Urquhart, B.; Ghonima, M.; Dahlin, E.; Nguyen, A.; Kurtz, B.; Chow, C. W.; Mejia, F. A.

    2016-04-01

    During the University of California, San Diego (UCSD) Sky Imager Cloud Position Study, two University of California, San Diego Sky Imagers (USI) (Figure 1) were deployed the U.S. Department of Energy(DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains SGP) research facility. The UCSD Sky Imagers were placed 1.7 km apart to allow for stereographic determination of the cloud height for clouds over approximately 1.5 km. Images with a 180-degree field of view were captured from both systems during daylight hours every 30 seconds beginning on March 11, 2013 and ending on November 4, 2013. The spatial resolution of the images was 1,748 × 1,748, and the intensity resolution was 16 bits using a high-dynamic-range capture process. The cameras use a fisheye lens, so the images are distorted following an equisolid angle projection.

  13. Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds

    NASA Astrophysics Data System (ADS)

    Boerner, R.; Kröhnert, M.

    2016-06-01

    3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.

  14. The identification of cloud types in LANDSAT MSS images. [Great Britain

    NASA Technical Reports Server (NTRS)

    Barrett, E. C. (Principal Investigator); Grant, C. K.

    1976-01-01

    The author has identified the following significant results. Five general families of clouds were identified: cumulonimbiform, cumuliform, stratiform, stratocumuliform, and cirriform. Four members of this five-fold primary division of clouds were further divided into a number of subgroups. The MSS observed and recorded earth radiation in four different wavebands. Two of these bands (4 and 5) image in the visible portion of the electromagnetic spectrum, while the others (6 and 7) image the short wave portion, or just into the infrared. The main differences between the appearances of clouds in the four wavebands are related to the background brightness of land and sea surfaces.

  15. Stereo Reconstruction of Atmospheric Cloud Surfaces from Fish-Eye Camera Images

    NASA Astrophysics Data System (ADS)

    Katai-Urban, G.; Otte, V.; Kees, N.; Megyesi, Z.; Bixel, P. S.

    2016-06-01

    In this article a method for reconstructing atmospheric cloud surfaces using a stereo camera system is presented. The proposed camera system utilizes fish-eye lenses in a flexible wide baseline camera setup. The entire workflow from the camera calibration to the creation of the 3D point set is discussed, but the focus is mainly on cloud segmentation and on the image processing steps of stereo reconstruction. Speed requirements, geometric limitations, and possible extensions of the presented method are also covered. After evaluating the proposed method on artificial cloud images, this paper concludes with results and discussion of possible applications for such systems.

  16. OpenID Connect as a security service in cloud-based medical imaging systems.

    PubMed

    Ma, Weina; Sartipi, Kamran; Sharghigoorabi, Hassan; Koff, David; Bak, Peter

    2016-04-01

    The evolution of cloud computing is driving the next generation of medical imaging systems. However, privacy and security concerns have been consistently regarded as the major obstacles for adoption of cloud computing by healthcare domains. OpenID Connect, combining OpenID and OAuth together, is an emerging representational state transfer-based federated identity solution. It is one of the most adopted open standards to potentially become the de facto standard for securing cloud computing and mobile applications, which is also regarded as "Kerberos of cloud." We introduce OpenID Connect as an authentication and authorization service in cloud-based diagnostic imaging (DI) systems, and propose enhancements that allow for incorporating this technology within distributed enterprise environments. The objective of this study is to offer solutions for secure sharing of medical images among diagnostic imaging repository (DI-r) and heterogeneous picture archiving and communication systems (PACS) as well as Web-based and mobile clients in the cloud ecosystem. The main objective is to use OpenID Connect open-source single sign-on and authorization service and in a user-centric manner, while deploying DI-r and PACS to private or community clouds should provide equivalent security levels to traditional computing model.

  17. Pattern Recognition and Image Processing of Infrared Astronomical Satellite Images

    NASA Astrophysics Data System (ADS)

    He, Lun Xiong

    1996-01-01

    The Infrared Astronomical Satellite (IRAS) images with wavelengths of 60 mu m and 100 mu m contain mainly information on both extra-galactic sources and low-temperature interstellar media. The low-temperature interstellar media in the Milky Way impose a "cirrus" screen of IRAS images, especially in images with 100 mu m wavelength. This dissertation deals with the techniques of removing the "cirrus" clouds from the 100 mu m band in order to achieve accurate determinations of point sources and their intensities (fluxes). We employ an image filtering process which utilizes mathematical morphology and wavelet analysis as the key tools in removing the "cirrus" foreground emission. The filtering process consists of extraction and classification of the size information, and then using the classification results in removal of the cirrus component from each pixel of the image. Extraction of size information is the most important step in this process. It is achieved by either mathematical morphology or wavelet analysis. In the mathematical morphological method, extraction of size information is done using the "sieving" process. In the wavelet method, multi-resolution techniques are employed instead. The classification of size information distinguishes extra-galactic sources from cirrus using their averaged size information. The cirrus component for each pixel is then removed by using the averaged cirrus size information. The filtered image contains much less cirrus. Intensity alteration for extra-galactic sources in the filtered image are discussed. It is possible to retain the fluxes of the point sources when we weigh the cirrus component differently pixel by pixel. The importance of the uni-directional size information extractions are addressed in this dissertation. Such uni-directional extractions are achieved by constraining the structuring elements, or by constraining the sieving process to be sequential. The generalizations of mathematical morphology operations based

  18. Searching for Pulsars Using Image Pattern Recognition

    NASA Astrophysics Data System (ADS)

    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

    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

  19. Searching for pulsars using image pattern recognition

    SciTech Connect

    Zhu, W. W.; Berndsen, A.; Madsen, E. C.; Tan, M.; Stairs, I. H.; Brazier, A.; Lazarus, P.; Lynch, R.; Scholz, P.; Stovall, K.; Cohen, S.; Dartez, L. P.; Lunsford, G.; Martinez, J. G.; Mata, A.; Ransom, S. M.; Banaszak, S.; Biwer, C. M.; Flanigan, J.; Rohr, M. E-mail: berndsen@phas.ubc.ca; and others

    2014-02-01

    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

  20. Weekly cycle of lightning and associated patterns of rainfall, cloud, and aerosols over Korea and adjacent oceans during boreal summer

    NASA Astrophysics Data System (ADS)

    Kim, J.; Kim, K.

    2011-12-01

    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 land area. 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 coastal 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.

  1. 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)

    Kim, Ji-In; Kim, Kyu-Myong

    2011-01-01

    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.

  2. The use of MISR Multiangle Image Data to Visualize Cloud Morphology and Motion

    NASA Astrophysics Data System (ADS)

    Realmuto, V. J.; Moroney, C. M.; Davies, R.

    2002-12-01

    The Multiangle Imaging SpectroRadiometer (MISR), currently orbiting the Earth aboard NASA's Terra spacecraft, acquires image data at 9 distinct viewing angles simultaneously. This multiangle imaging is accomplished through the use of 9 cameras, with one camera providing a nadir view and the remaining cameras providing views 26.1, 45.6, 60.0, and 70.5 degrees fore and aft of nadir. Each camera, in turn, measures scene radiance in 4 spectral bands (red, green, blue, and near infrared). One of the objectives of the MISR mission is to infer the physical properties of atmospheric aerosols, clouds, and land cover (including snow, ice, and vegetation) from angular variations in scene radiance. One step in the operational processing of MISR data is to map these data into a Space Oblique Mercator projection. As a result of this projection, features at elevations above or below the reference ellipsoid (WGS 84) exhibit an apparent displacement, known as parallax or disparity, in the off-nadir images. The disparities exhibited by clouds can be used to estimate the height of the clouds, and cloud-top height maps are an operational MISR data product. Although the 9 MISR cameras acquire data simultaneously, approximately 7 minutes are required to obtain a suite of fore- and aft-viewing images that depict the same scene. This time lag allows MISR to capture the motion of clouds due to winds, and maps of wind direction and wind speed are operational data products. Visualization of the cloud properties measured by MISR presents several unique challenges, such as registration of the angular distribution of radiance above a cloud with its surface morphology and depiction of cloud motion independent of the disparity resulting from cloud height. We will present some of the tools and animation techniques developed to address these challenges. For example, MISR_Shift is an interactive tool that allows us to evaluate the effects of changes (or uncertainties) in cloud height and wind speed

  3. A method of periodic pattern localization on document images

    NASA Astrophysics Data System (ADS)

    Chernov, Timofey S.; Nikolaev, Dmitry P.; Kliatskine, Vitali M.

    2015-12-01

    Periodic patterns often present on document images as holograms, watermarks or guilloche elements which are mostly used for fraud protection. Localization of such patterns lets an embedded OCR system to vary its settings depending on pattern presence in particular image regions and improves the precision of pattern removal to preserve as much useful data as possible. Many document images' noise detection and removal methods deal with unstructured noise or clutter on documents with simple background. In this paper we propose a method of periodic pattern localization on document images which uses discrete Fourier transform that works well on documents with complex background.

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

    SciTech Connect

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

    1994-03-01

    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.

  5. Parallel optimization of pixel purity index algorithm for massive hyperspectral images in cloud computing environment

    NASA Astrophysics Data System (ADS)

    Chen, Yufeng; Wu, Zebin; Sun, Le; Wei, Zhihui; Li, Yonglong

    2016-04-01

    With the gradual increase in the spatial and spectral resolution of hyperspectral images, the size of image data becomes larger and larger, and the complexity of processing algorithms is growing, which poses a big challenge to efficient massive hyperspectral image processing. Cloud computing technologies distribute computing tasks to a large number of computing resources for handling large data sets without the limitation of memory and computing resource of a single machine. This paper proposes a parallel pixel purity index (PPI) algorithm for unmixing massive hyperspectral images based on a MapReduce programming model for the first time in the literature. According to the characteristics of hyperspectral images, we describe the design principle of the algorithm, illustrate the main cloud unmixing processes of PPI, and analyze the time complexity of serial and parallel algorithms. Experimental results demonstrate that the parallel implementation of the PPI algorithm on the cloud can effectively process big hyperspectral data and accelerate the algorithm.

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

    SciTech Connect

    Davis, A. B.

    2002-01-01

    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.

  7. Thirty Years of Cloud Cover Patterns from Satellite Data: Fog in California's Central Valley and Coast

    NASA Astrophysics Data System (ADS)

    Waller, E.; Baldocchi, D. D.

    2012-12-01

    In an effort to assess long term trends in winter fog in the Central Valley of California, custom maps of daily cloud cover from an approximately 30 year record of AVHRR (1981-1999) and MODIS (2000-2012) satellite data were generated. Spatial rules were then used to differentiate between fog and general cloud cover. Differences among the sensors (e.g., spectral content, spatial resolution, overpass time) presented problems of consistency, but concurrent climate station data were used to resolve systematic differences in products, and to confirm long term trends. The frequency and extent of Central Valley ("Tule") fog appear to have some periodic oscillation, but also appear to be on the decline, especially in the Sacramento Valley and in the "shoulder" months of November and February. These results may have strong implications for growers of fruit and nut trees in the Central Valley dependent on winter chill hours that are augmented by the foggy daytime conditions. Conclusions about long term trends in fog are limited to daytime patterns, as results are primarily derived from reflectance-based products. Similar analyses of daytime cloud cover are performed on other areas of concern, such as the coastal fog belt of California. Large area and long term patterns here appear to have periodic oscillation similar to that for the Central Valley. However, the relatively coarse spatial resolution of the AVHRR LTDR (Long Term Data Record) data (~5-km) may be limiting for fine-scale analysis of trends.

  8. Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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

  9. Limb Observations of Solar Scattered Light by the Imaging Ultraviolet Spectrograph on MAVEN: New Constraints on Martian Mesospheric Cloud Variability

    NASA Astrophysics Data System (ADS)

    Stevens, Michael H.; Siskind, David E.; Evans, Scott; Schneider, Nicholas M.; Stewart, A. Ian F.; Deighan, Justin; Jain, Sonal Kumar; Crismani, Matteo; Stiepen, Arnaud; Chaffin, Michael S.; McClintock, William; Holsclaw, Gregory; Lefevre, Franck; Montmessin, Franck; Lo, Daniel; Clarke, John T.; Jakosky, Bruce

    2016-10-01

    The Imaging Ultraviolet Spectrograph (IUVS) on NASA's Mars Atmosphere and Volatile Evolution (MAVEN) mission observed the Martian upper atmosphere in late 2015 (Ls ~ 70) and early 2016 (Ls ~ 150). Although designed to measure the dayglow between 90-200 km IUVS also scans the limb down to 60 km, where solar scattered light dominates the mid-ultraviolet (MUV) signal. Occasionally, this MUV light shows enhanced scattering between 60-90 km indicating the presence of aerosols in the mesosphere. We quantify the solar scattering for each daylight scan obtained between October and December, 2015 and between April and June, 2016. We then identify over 100 scans of enhanced scattering between 60-90 km and assemble them both geographically and diurnally. The geographical distribution of the enhancements in 2015 is preferentially located near the equator, consistent with previous observations of mesospheric clouds for this part of the season. A wave three pattern in equatorial cloud occurrence suggests forcing from a non-migrating tide, possibly linked to the longitudinal variation of Mars surface topography. At the same time, there are indications of a diurnal variation such that the clouds seen in 2015 and 2016 are preferentially observed in the early morning, between 0600-0900 local solar time. This suggests an important role for a migrating temperature tide controlling the formation of Martian mesospheric clouds.

  10. Volcanic ash cloud detection from MODIS image based on CPIWS method

    NASA Astrophysics Data System (ADS)

    Liu, Lan; Li, Chengfan; Lei, Yongmei; Yin, Jingyuan; Zhao, Junjuan

    2017-02-01

    Volcanic ash cloud detection has been a difficult problem in moderate-resolution imaging spectroradiometer (MODIS) multispectral remote sensing application. Principal component analysis (PCA) and independent component analysis (ICA) are effective feature extraction methods based on second-order and higher order statistical analysis, and the support vector machine (SVM) can realize the nonlinear classification in low-dimensional space. Based on the characteristics of MODIS multispectral remote sensing image, via presenting a new volcanic ash cloud detection method, named combined PCA-ICA-weighted and SVM (CPIWS), the current study tested the real volcanic ash cloud detection cases, i.e., Sangeang Api volcanic ash cloud of 30 May 2014. Our experiments suggest that the overall accuracy and Kappa coefficient of the proposed CPIWS method reach 87.20 and 0.7958%, respectively, under certain conditions with the suitable weighted values; this has certain feasibility and practical significance.

  11. A hybrid approach to estimate the complex motions of clouds in sky images

    DOE PAGES

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

    2016-09-14

    Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

  12. A hybrid approach to estimate the complex motions of clouds in sky images

    SciTech Connect

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Kalb, Paul

    2016-09-14

    Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approach with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.

  13. A Cloud-Based Infrastructure for Feedback-Driven Training and Image Recognition.

    PubMed

    Abedini, Mani; von Cavallar, Stefan; Chakravorty, Rajib; Davis, Matthew; Garnavi, Rahil

    2015-01-01

    Advanced techniques in machine learning combined with scalable "cloud" computing infrastructure are driving the creation of new and innovative health diagnostic applications. We describe a service and application for performing image training and recognition, tailored to dermatology and melanoma identification. The system implements new machine learning approaches to provide a feedback-driven training loop. This training sequence enhances classification performance by incrementally retraining the classifier model from expert responses. To easily provide this application and associated web service to clinical practices, we also describe a scalable cloud infrastructure, deployable in public cloud infrastructure and private, on-premise systems.

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    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.

  15. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

    NASA Astrophysics Data System (ADS)

    Champion, Nicolas

    2016-06-01

    Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

  16. Vacuum Ultraviolet Images of the Large Magellanic Cloud: Erratum

    NASA Astrophysics Data System (ADS)

    Smith, Andrew M.; Cornett, Robert H.; Hill, Robert S.

    1990-06-01

    In the paper "Vacuum Ultraviolet Images of the Large Magellanic Cloud" by Andrew M. Smith, Robert H. Cornett, and Robert S. Hill (Ap. J., 320, 609 [1987]), an error was made in the dereddening formulae for vacuum ultraviolet (VUV) magnitudes on page 613. For 30 Dor dereddening, the formulae should be m_0(1500)_ = m_1500_ - 10.47 x E(B - V)_LMC_ - 8.05 x E(B - V)_Gal_, and m_0(1900)_ = m_1900_ - 8.87 x E(B - V)_LMC_ - 8.28 x E(B - V)_Gal_. For non-30 Dor dereddening, the formulae should be m_0(1500)_ = m_1500_ -8.72 x E(B - V)_LMC_ - 8.05 x E(B - V)_Gal_, and m_0(1900) = m_1900_ - 8.21 x E(B - V)_LMC_ - 8.28 x E(B - V)_Gal_. The ramifications of this error spread through several results. However, it must be noted that the overall effect is to make our original estimates of intrinsic VUV flux too low. As a result, our primary argument on energetics actually becomes stronger: there is ample energy flux in the southwestern Large Magellanic Cloud (LMC) to sustain into the next generation of stars the star-formation front visible in our VUV images. The three tables of observational results are replaced by the results given here in Table 1, in which intrinsic VUV fluxes are corrected (other quantities remain as they were). The discussion of Table 2 needs to be amended. This table compares ionizing fluxes computed by different methods for VUV sources (OB associations) that can be identified with 6 cm radio sources (H II regions). The aggregate ionizing fluxes for this set of objects derived from the two wavelength regimes are no longer so nearly equal as they were. However, as we pointed out, any such equality would be fortuitous, since the two derivations yield results differing by typically a factor of 2 for any given individual association. The discussion of Table 3 also needs to be amended. This table combines ionizing fluxes from OB associations (derived from VU photometry) with ionizing fluxes from 6 cm sources that do not coincide with any OB association. In this

  17. Improved Cloud and Surface Properties By Combining Conventional and L-1 Satellite Imager Data

    NASA Astrophysics Data System (ADS)

    Minnis, P.; Doelling, D.; Nguyen, L.; Palikonda, R.; Spangenberg, D. A.; Hong, G.; Yi, Y.

    2011-12-01

    Imagers on geostationary (GEOSat) and low-earth orbiting (LEOSat) satellites are often used to derive information about clouds and the surface, but are limited in their angular coverage of a given scene by their particular orbits. A GEOSat views an area through its entire diurnal cycle covering the full range of solar zenith angles (SZAs) while viewing from a constant viewing zenith angle (VZA) and varying relative azimuth angle (RAA). Most polar-orbiting satellites are sun-synchronous and view a given area at one time of day from various VZAs and RAAs, but a over a small SZA range. A few imagers such as MISR or AATSR are on LEOSats and can provide views over a greater range of RAA and VZA, but are still constrained by SZA. The Deep Space Climate Observatory (DSCOVR) will orbit at the L-1 position in a near backscatter angle (~168°) relative to the Earth and sun. It carries an imager, EPIC, that has several UV, visible, and near-infrared channels measuring radiances at a nadir 10-km resolution. Because it views most of the sunlit Earth at high frequency, it can provide unprecedented coverage of the daylight portion of the diurnal cycle for a given area at over the full range of SZAs and VZAs at a nearly constant RAA. Because of this coverage, pixels from the EPIC can be matched with those from any other satellite passing over the sunlit hemisphere. Although cloud information such as cloud amount, optical depth, and height can be derived from the EPIC channels, the combination of EPIC data with that from higher resolution GEOSats and LEOSats will be more useful than either by itself. Because of its low resolution and lack of infrared data, broken and scattered and cirrus cloud fields are likely to be misinterpreted using the EPIC data alone. Matching the more conventional satellite data and associated cloud products with the EPIC data will enhance the information from the EPIC as its field of view increases as 1/cos(VZA). The cloud heights derived from oxygen A and

  18. Cloud Base Height Measurements at Manila Observatory: Initial Results from Constructed Paired Sky Imaging Cameras

    NASA Astrophysics Data System (ADS)

    Lagrosas, N.; Tan, F.; Antioquia, C. T.

    2014-12-01

    Fabricated all sky imagers are efficient and cost effective instruments for cloud detection and classification. Continuous operation of this instrument can result in the determination of cloud occurrence and cloud base heights for the paired system. In this study, a fabricated paired sky imaging system - consisting two commercial digital cameras (Canon Powershot A2300) enclosed in weatherproof containers - is developed in Manila Observatory for the purpose of determining cloud base heights at the Manila Observatory area. One of the cameras is placed on the rooftop of Manila Observatory and the other is placed on the rooftop of the university dormitory, 489m from the first camera. The cameras are programmed to simultaneously gather pictures every 5 min. Continuous operation of these cameras were implemented since the end of May of 2014 but data collection started end of October 2013. The data were processed following the algorithm proposed by Kassianov et al (2005). The processing involves the calculation of the merit function that determines the area of overlap of the two pictures. When two pictures are overlapped, the minimum of the merit function corresponds to the pixel column positions where the pictures have the best overlap. In this study, pictures of overcast sky prove to be difficult to process for cloud base height and were excluded from processing. The figure below shows the initial results of the hourly average of cloud base heights from data collected from November 2013 to July 2014. Measured cloud base heights ranged from 250m to 1.5km. These are the heights of cumulus and nimbus clouds that are dominant in this part of the world. Cloud base heights are low in the early hours of the day indicating low convection process during these times. However, the increase in the convection process in the atmosphere can be deduced from higher cloud base heights in the afternoon. The decrease of cloud base heights after 15:00 follows the trend of decreasing solar

  19. Sub-atom shot noise Faraday imaging of ultracold atom clouds

    NASA Astrophysics Data System (ADS)

    Kristensen, M. A.; Gajdacz, M.; Pedersen, P. L.; Klempt, C.; Sherson, J. F.; Arlt, J. J.; Hilliard, A. J.

    2017-02-01

    We demonstrate that a dispersive imaging technique based on the Faraday effect can measure the atom number in a large, ultracold atom cloud with a precision below the atom shot noise level. The minimally destructive character of the technique allows us to take multiple images of the same cloud, which enables sub-atom shot noise measurement precision of the atom number and allows for an in situ determination of the measurement precision. We have developed a noise model that quantitatively describes the noise contributions due to photon shot noise in the detected light and the noise associated with single atom loss. This model contains no free parameters and is calculated through an analysis of the fluctuations in the acquired images. For clouds containing N∼ 5× {10}6 atoms, we achieve a precision more than a factor of two below the atom shot noise level.

  20. Pattern recognition in hyperspectral persistent imaging

    NASA Astrophysics Data System (ADS)

    Rosario, Dalton; Romano, Joao; Borel, Christoph

    2015-05-01

    We give updates on a persistent imaging experiment dataset, being considered for public release in a foreseeable future, and present additional observations analyzing a subset of the dataset. The experiment is a long-term collaborative effort among the Army Research Laboratory, Army Armament RDEC, and Air Force Institute of Technology that focuses on the collection and exploitation of longwave infrared (LWIR) hyperspectral imagery. We emphasize the inherent challenges associated with using remotely sensed LWIR hyperspectral imagery for material recognition, and show that this data type violates key data assumptions conventionally used in the scientific community to develop detection/ID algorithms, i.e., normality, independence, identical distribution. We treat LWIR hyperspectral imagery as Longitudinal Data and aim at proposing a more realistic framework for material recognition as a function of spectral evolution through time, and discuss limitations. The defining characteristic of a longitudinal study is that objects are measured repeatedly through time and, as a result, data are dependent. This is in contrast to cross-sectional studies in which the outcomes of a specific event are observed by randomly sampling from a large population of relevant objects in which data are assumed independent. Researchers in the remote sensing community generally assume the problem of object recognition to be cross-sectional. But through a longitudinal analysis of a fixed site with multiple material types, we quantify and argue that, as data evolve through a full diurnal cycle, pattern recognition problems are longitudinal in nature and that by applying this knowledge may lead to better algorithms.

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

    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 degrees 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).

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

    SciTech Connect

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

    2005-03-18

    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).

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

    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.

  4. Orientation of airborne laser scanning point clouds with multi-view, multi-scale image blocks.

    PubMed

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

    2009-01-01

    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.

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

    PubMed Central

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

    2009-01-01

    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

  6. Peering through Jupiter’s clouds with radio spectral imaging

    NASA Astrophysics Data System (ADS)

    de Pater, Imke; Sault, R. J.; Butler, Bryan; DeBoer, David; Wong, Michael H.

    2016-06-01

    Radio wavelengths can probe altitudes in Jupiter’s atmosphere below its visible cloud layers. We used the Very Large Array to map this unexplored region down to ~8 bar, ~100 kilometers below the visible clouds. Our maps reveal a dynamically active planet at pressures less than 2 to 3 bar. A radio-hot belt exists, consisting of relatively transparent regions (a low ammonia concentration, NH3 being the dominant source of opacity) probing depths to over ~8 bar; these regions probably coincide with 5-micrometer hot spots. Just to the south we distinguish an equatorial wave, bringing up ammonia gas from Jupiter’s deep atmosphere. This wave has been theorized to produce the 5-micrometer hot spots; we observed the predicted radio counterpart of such hot spots.

  7. Peering through Jupiter's clouds with radio spectral imaging.

    PubMed

    de Pater, Imke; Sault, R J; Butler, Bryan; DeBoer, David; Wong, Michael H

    2016-06-03

    Radio wavelengths can probe altitudes in Jupiter's atmosphere below its visible cloud layers. We used the Very Large Array to map this unexplored region down to ~8 bar, ~100 kilometers below the visible clouds. Our maps reveal a dynamically active planet at pressures less than 2 to 3 bar. A radio-hot belt exists, consisting of relatively transparent regions (a low ammonia concentration, NH3 being the dominant source of opacity) probing depths to over ~8 bar; these regions probably coincide with 5-micrometer hot spots. Just to the south we distinguish an equatorial wave, bringing up ammonia gas from Jupiter's deep atmosphere. This wave has been theorized to produce the 5-micrometer hot spots; we observed the predicted radio counterpart of such hot spots.

  8. Time evolution of surface chlorophyll patterns from cross-spectrum analysis of satellite color images

    NASA Technical Reports Server (NTRS)

    Denman, Kenneth L.; Abbott, Mark R.

    1988-01-01

    The rate of decorrelation of surface chlorophyll patterns as a function of the time separation between pairs of images was determined from two sequences of CZCS images of the Pacific Ocean area adjacent to Vancouver Island, Canada; cloud-free subareas were selected that were common to several images separated in time by 1-17 days. Image pairs were subjected to two-dimensional autospectrum and cross-spectrum analysis in an array processor, and squared coherence estimates found for several wave bands were plotted against time separation, in analogy with a time-lagged cross correlation function. It was found that, for wavelengths of 50-150 km, significant coherence was lost after 7-10 days, while for wavelengths of 25-50 km, significant coherence was lost after only 5-7 days. In both cases, offshore regions maintained coherence longer than coastal regions.

  9. On the camparability of cloud fractions derived from whole sky imager and ceilometer data

    SciTech Connect

    Rodriguez, D.

    1998-01-30

    The Atmospheric Radiation Measurement (ARM) Program`s most heavily instrumented site is its central facility in Lamont, OK. With respect to cloud observations, the instrumentation included a whole sky imager, ceilometers, lidar, millimeter cloud radar, microwave profilers, and radiosondes. Data from three of these instrument--the Whole Sky Imager (WSI), Belfort Laser Ceilometer (BLC) and Micropulse Lidar (MPL)-- are used in this study primarily to investigate the utility of using ceilometers, now strategically emplaced at four additional locations along the perimeter of the site.

  10. Cumulus cloud field morphology and spatial patterns derived from high spatial resolution Landsat imagery

    NASA Technical Reports Server (NTRS)

    Sengupta, S. K.; Welch, R. M.; Navar, M. S.; Berendes, T. A.; Chen, D. W.

    1990-01-01

    Using high-spatial-resolution Landsat MSS imagery, the cumulus cloud morphology, cloud nearest-neighbor distributions, and cloud clumping scales were investigated. It is shown that the cloud-size distribution can be represented by a mixture of two power laws; clouds of diameters less than 1 km have power-law slope range of 1.4-2.3, while larger clouds have slopes from 2.1 to 4.75. The break in power-law slope occurs at the cloud size that makes the largest contribution to cloud cover. Results suggest that larger clouds grow at the expense of smaller clouds. It was also found that the cloud inhomogeneities have significant impact on radiative fluxes.

  11. Observation of a cavitation cloud in tissue using correlation between ultrafast ultrasound images.

    PubMed

    Prieur, Fabrice; Zorgani, Ali; Catheline, Stefan; Souchon, Rémi; Mestas, Jean-Louis; Lafond, Maxime; Lafon, Cyril

    2015-07-01

    The local application of ultrasound is known to improve drug intake by tumors. Cavitating bubbles are one of the contributing effects. A setup in which two ultrasound transducers are placed confocally is used to generate cavitation in ex vivo tissue. As the transducers emit a series of short excitation bursts, the evolution of the cavitation activity is monitored using an ultrafast ultrasound imaging system. The frame rate of the system is several thousands of images per second, which provides several tens of images between consecutive excitation bursts. Using the correlation between consecutive images for speckle tracking, a decorrelation of the imaging signal appears due to the creation, fast movement, and dissolution of the bubbles in the cavitation cloud. By analyzing this area of decorrelation, the cavitation cloud can be localized and the spatial extent of the cavitation activity characterized.

  12. Mitigation Approaches for Optical Imaging through Clouds and Fog

    DTIC Science & Technology

    2009-11-01

    b) Image pixels as detected on the photo-detector array; (c) Compensated image pixels after convergence of the adaptive deconvolution; (d... Convergence properties of the MSE with iterations. ............................................................. 101 Fig. 7.10: Restored Image Using Inverse... Convergence of the Cost Function

  13. Ground-based imaging remote sensing of ice clouds: uncertainties caused by sensor, method and atmosphere

    NASA Astrophysics Data System (ADS)

    Zinner, Tobias; Hausmann, Petra; Ewald, Florian; Bugliaro, Luca; Emde, Claudia; Mayer, Bernhard

    2016-09-01

    In this study a method is introduced for the retrieval of optical thickness and effective particle size of ice clouds over a wide range of optical thickness from ground-based transmitted radiance measurements. Low optical thickness of cirrus clouds and their complex microphysics present a challenge for cloud remote sensing. In transmittance, the relationship between optical depth and radiance is ambiguous. To resolve this ambiguity the retrieval utilizes the spectral slope of radiance between 485 and 560 nm in addition to the commonly employed combination of a visible and a short-wave infrared wavelength.An extensive test of retrieval sensitivity was conducted using synthetic test spectra in which all parameters introducing uncertainty into the retrieval were varied systematically: ice crystal habit and aerosol properties, instrument noise, calibration uncertainty and the interpolation in the lookup table required by the retrieval process. The most important source of errors identified are uncertainties due to habit assumption: Averaged over all test spectra, systematic biases in the effective radius retrieval of several micrometre can arise. The statistical uncertainties of any individual retrieval can easily exceed 10 µm. Optical thickness biases are mostly below 1, while statistical uncertainties are in the range of 1 to 2.5.For demonstration and comparison to satellite data the retrieval is applied to observations by the Munich hyperspectral imager specMACS (spectrometer of the Munich Aerosol and Cloud Scanner) at the Schneefernerhaus observatory (2650 m a.s.l.) during the ACRIDICON-Zugspitze campaign in September and October 2012. Results are compared to MODIS and SEVIRI satellite-based cirrus retrievals (ACRIDICON - Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems; MODIS - Moderate Resolution Imaging Spectroradiometer; SEVIRI - Spinning Enhanced Visible and Infrared Imager). Considering the identified

  14. Evaluation of Methods for Coregistration and Fusion of Rpas-Based 3d Point Clouds and Thermal Infrared Images

    NASA Astrophysics Data System (ADS)

    Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.

    2016-06-01

    This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

  15. Pattern Recognition Software and Techniques for Biological Image Analysis

    PubMed Central

    Shamir, Lior; Delaney, John D.; Orlov, Nikita; Eckley, D. Mark; Goldberg, Ilya G.

    2010-01-01

    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays. PMID:21124870

  16. Pattern recognition software and techniques for biological image analysis.

    PubMed

    Shamir, Lior; Delaney, John D; Orlov, Nikita; Eckley, D Mark; Goldberg, Ilya G

    2010-11-24

    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays.

  17. HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

    NASA Astrophysics Data System (ADS)

    Beck, Alexander; Henneberger, Jan; Schöpfer, Sarah; Fugal, Jacob; Lohmann, Ulrike

    2017-02-01

    In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s-1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

  18. Optical Imaging of Flow Pattern and Phantom

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    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

  19. Imaging Patterns of Intratumoral Calcification in the Abdominopelvic Cavity

    PubMed Central

    Yu, Mi Hye; Park, Hee Sun; Jung, Sung Il; Jeon, Hae Jeong

    2017-01-01

    Intratumoral calcification is one of the most noticeable of radiologic findings. It facilitates detection and provides information important for correctly diagnosing tumors. In the abdominopelvic cavity, a wide variety of tumors have calcifications with various imaging features, though the majority of such calcifications are dystrophic in nature. In this article, we classify the imaging patterns of intratumoral calcification according to number, location, and morphology. Then, we describe commonly-encountered abdominopelvic tumors containing typical calcification patterns, focusing on their differentiable characteristics using the imaging patterns of intratumoral calcification. PMID:28246512

  20. Cloud top structure of Venus revealed by Subaru/COMICS mid-infrared images

    NASA Astrophysics Data System (ADS)

    Sato, T. M.; Sagawa, H.; Kouyama, T.; Mitsuyama, K.; Satoh, T.; Ohtsuki, S.; Ueno, M.; Kasaba, Y.; Nakamura, M.; Imamura, T.

    2014-04-01

    We have investigated the cloud top structure of Venus by analyzing ground-based images obtained by the Cooled Mid-Infrared Camera and Spectrometer (COMICS), mounted on the 8.2-m Subaru Telescope. In this presentation, we will overview the observational results and discuss their interpretations.

  1. Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance Images

    PubMed Central

    Kang, Zhizhong; Li, Jonathan; Zhang, Liqiang; Zhao, Qile; Zlatanova, Sisi

    2009-01-01

    This paper presents a new approach to the automatic registration of terrestrial laser scanning (TLS) point clouds using panoramic reflectance images. The approach follows a two-step procedure that includes both pair-wise registration and global registration. The pair-wise registration consists of image matching (pixel-to-pixel correspondence) and point cloud registration (point-to-point correspondence), as the correspondence between the image and the point cloud (pixel-to-point) is inherent to the reflectance images. False correspondences are removed by a geometric invariance check. The pixel-to-point correspondence and the computation of the rigid transformation parameters (RTPs) are integrated into an iterative process that allows for the pair-wise registration to be optimised. The global registration of all point clouds is obtained by a bundle adjustment using a circular self-closure constraint. Our approach is tested with both indoor and outdoor scenes acquired by a FARO LS 880 laser scanner with an angular resolution of 0.036° and 0.045°, respectively. The results show that the pair-wise and global registration accuracies are of millimetre and centimetre orders, respectively, and that the process is fully automatic and converges quickly. PMID:22574036

  2. Crowdsourcing Precision Cerebrovascular Health: Imaging and Cloud Seeding A Million Brains Initiative™.

    PubMed

    Liebeskind, David S

    2016-01-01

    Crowdsourcing, an unorthodox approach in medicine, creates an unusual paradigm to study precision cerebrovascular health, eliminating the relative isolation and non-standardized nature of current imaging data infrastructure, while shifting emphasis to the astounding capacity of big data in the cloud. This perspective envisions the use of imaging data of the brain and vessels to orient and seed A Million Brains Initiative™ that may leapfrog incremental advances in stroke and rapidly provide useful data to the sizable population around the globe prone to the devastating effects of stroke and vascular substrates of dementia. Despite such variability in the type of data available and other limitations, the data hierarchy logically starts with imaging and can be enriched with almost endless types and amounts of other clinical and biological data. Crowdsourcing allows an individual to contribute to aggregated data on a population, while preserving their right to specific information about their own brain health. The cloud now offers endless storage, computing prowess, and neuroimaging applications for postprocessing that is searchable and scalable. Collective expertise is a windfall of the crowd in the cloud and particularly valuable in an area such as cerebrovascular health. The rise of precision medicine, rapidly evolving technological capabilities of cloud computing and the global imperative to limit the public health impact of cerebrovascular disease converge in the imaging of A Million Brains Initiative™. Crowdsourcing secure data on brain health may provide ultimate generalizability, enable focused analyses, facilitate clinical practice, and accelerate research efforts.

  3. Crowdsourcing Precision Cerebrovascular Health: Imaging and Cloud Seeding A Million Brains Initiative™

    PubMed Central

    Liebeskind, David S.

    2016-01-01

    Crowdsourcing, an unorthodox approach in medicine, creates an unusual paradigm to study precision cerebrovascular health, eliminating the relative isolation and non-standardized nature of current imaging data infrastructure, while shifting emphasis to the astounding capacity of big data in the cloud. This perspective envisions the use of imaging data of the brain and vessels to orient and seed A Million Brains Initiative™ that may leapfrog incremental advances in stroke and rapidly provide useful data to the sizable population around the globe prone to the devastating effects of stroke and vascular substrates of dementia. Despite such variability in the type of data available and other limitations, the data hierarchy logically starts with imaging and can be enriched with almost endless types and amounts of other clinical and biological data. Crowdsourcing allows an individual to contribute to aggregated data on a population, while preserving their right to specific information about their own brain health. The cloud now offers endless storage, computing prowess, and neuroimaging applications for postprocessing that is searchable and scalable. Collective expertise is a windfall of the crowd in the cloud and particularly valuable in an area such as cerebrovascular health. The rise of precision medicine, rapidly evolving technological capabilities of cloud computing and the global imperative to limit the public health impact of cerebrovascular disease converge in the imaging of A Million Brains Initiative™. Crowdsourcing secure data on brain health may provide ultimate generalizability, enable focused analyses, facilitate clinical practice, and accelerate research efforts. PMID:27921034

  4. Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance Images.

    PubMed

    Kang, Zhizhong; Li, Jonathan; Zhang, Liqiang; Zhao, Qile; Zlatanova, Sisi

    2009-01-01

    This paper presents a new approach to the automatic registration of terrestrial laser scanning (TLS) point clouds using panoramic reflectance images. The approach follows a two-step procedure that includes both pair-wise registration and global registration. The pair-wise registration consists of image matching (pixel-to-pixel correspondence) and point cloud registration (point-to-point correspondence), as the correspondence between the image and the point cloud (pixel-to-point) is inherent to the reflectance images. False correspondences are removed by a geometric invariance check. The pixel-to-point correspondence and the computation of the rigid transformation parameters (RTPs) are integrated into an iterative process that allows for the pair-wise registration to be optimised. The global registration of all point clouds is obtained by a bundle adjustment using a circular self-closure constraint. Our approach is tested with both indoor and outdoor scenes acquired by a FARO LS 880 laser scanner with an angular resolution of 0.036° and 0.045°, respectively. The results show that the pair-wise and global registration accuracies are of millimetre and centimetre orders, respectively, and that the process is fully automatic and converges quickly.

  5. NMR imaging of thermal convection patterns.

    PubMed

    Weis, J; Kimmich, R; Müller, H P

    1996-01-01

    Two special magnetic resonance imaging techniques were applied to the Rayleigh/Bénard problem of thermal convection for the first time. The methods were tested using a water cell with horizontal bottom and top covers kept at different temperatures with a downward gradient. Using Fourier encoding velocity imaging (FEVI) a five-dimensional image data set was recorded referring to two space dimensions of slice-selective images and all three components of the local velocity vector. On this basis, the fields of the velocity components or of the velocity magnitude were evaluated quantitatively and rendered as gray shade images. Furthermore the convection rolls were visualized with the aid of two- or three-dimensional multistripe/multiplane tagging imaging pulse sequences based on two or three DANTE combs for the space directions to be probed. Movies illustrating the fluid motions by convection in all three space dimensions were produced. It is demonstrated that the full spatial information of the convection rolls is accessible with microscopic resolution of typically 100 x 100 x 100 microns3. This resolution is effectively limited by flow displacements in the echo time, which should be well within the voxel dimension. The main perspective of this work is that the combined application of FEVI and multistripe/multiplane tagging imaging permits quantitative examinations of thermal convection for arbitrary boundary conditions and with imposed through-flow apart from the direct visualization of convective flow in the form of movies.

  6. A marked bounding box method for image data reduction and reconstruction of sole patterns

    NASA Astrophysics Data System (ADS)

    Wang, Xingyue; Wu, Jianhua; Zhao, Qingmin; Cheng, Jian; Zhu, Yican

    2012-01-01

    A novel and efficient method called marked bounding box method based on marching cubes is presented for the point cloud data reduction of sole patterns. This method is characterized in that each bounding box is marked with an index during the process of data reduction and later for use of data reconstruction. The data reconstruction is implemented from the simplified data set by using triangular meshes, the indices being used to search the nearest points from adjacent bounding boxes. Afterwards, the normal vectors are estimated to determine the strength and direction of the surface reflected light. The proposed method is used in a sole pattern classification and query system which uses OpenGL under Visual C++ to render the image of sole patterns. Digital results are given to demonstrate the efficiency and novelty of our method. Finally, conclusion and discussions are made.

  7. A marked bounding box method for image data reduction and reconstruction of sole patterns

    NASA Astrophysics Data System (ADS)

    Wang, Xingyue; Wu, Jianhua; Zhao, Qingmin; Cheng, Jian; Zhu, Yican

    2011-12-01

    A novel and efficient method called marked bounding box method based on marching cubes is presented for the point cloud data reduction of sole patterns. This method is characterized in that each bounding box is marked with an index during the process of data reduction and later for use of data reconstruction. The data reconstruction is implemented from the simplified data set by using triangular meshes, the indices being used to search the nearest points from adjacent bounding boxes. Afterwards, the normal vectors are estimated to determine the strength and direction of the surface reflected light. The proposed method is used in a sole pattern classification and query system which uses OpenGL under Visual C++ to render the image of sole patterns. Digital results are given to demonstrate the efficiency and novelty of our method. Finally, conclusion and discussions are made.

  8. A Multi-Frequency Wide-Swath Spaceborne Cloud and Precipitation Imaging Radar

    NASA Technical Reports Server (NTRS)

    Li, Lihua; Racette, Paul; Heymsfield, Gary; McLinden, Matthew; Venkatesh, Vijay; Coon, Michael; Perrine, Martin; Park, Richard; Cooley, Michael; Stenger, Pete; Spence, Thomas; Retelny, Tom

    2016-01-01

    Microwave and millimeter-wave radars have proven their effectiveness in cloud and precipitation observations. The NASA Earth Science Decadal Survey (DS) Aerosol, Cloud and Ecosystems (ACE) mission calls for a dual-frequency cloud radar (W band 94 GHz and Ka-band 35 GHz) for global measurements of cloud microphysical properties. Recently, there have been discussions of utilizing a tri-frequency (KuKaW-band) radar for a combined ACE and Global Precipitation Measurement (GPM) follow-on mission that has evolved into the Cloud and Precipitation Process Mission (CaPPM) concept. In this presentation we will give an overview of the technology development efforts at the NASA Goddard Space Flight Center (GSFC) and at Northrop Grumman Electronic Systems (NGES) through projects funded by the NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP). Our primary objective of this research is to advance the key enabling technologies for a tri-frequency (KuKaW-band) shared-aperture spaceborne imaging radar to provide unprecedented, simultaneous multi-frequency measurements that will enhance understanding of the effects of clouds and precipitation and their interaction on Earth climate change. Research effort has been focused on concept design and trade studies of the tri-frequency radar; investigating architectures that provide tri-band shared-aperture capability; advancing the development of the Ka band active electronically scanned array (AESA) transmitreceive (TR) module, and development of the advanced radar backend electronics.

  9. A low-cost digital holographic imager for calibration and validation of cloud microphysics remote sensing

    NASA Astrophysics Data System (ADS)

    Chambers, Thomas E.; Hamilton, Murray W.; Reid, Iain M.

    2016-10-01

    Clouds cover approximately 70% of the Earth's surface and therefore play a crucial rule in governing both the climate system and the hydrological cycle. The microphysical properties of clouds such as the cloud particle size distribution, shape distribution and spatial homogeneity contribute significantly to the net radiative effect of clouds and these properties must therefore be measured and understood to determine the exact contribution of clouds to the climate system. Significant discrepancies are observed between meteorological models and observations, particularly in polar regions that are most sensitive to changes in climate, suggesting a lack of understanding of these complex microphysical processes. Remote sensing techniques such as polarimetric LIDAR and radar allow microphysical cloud measurements with high temporal and spatial resolution however these instruments must be calibrated and validated by direct in situ measurements. To this end a low cost, light weight holographic imaging device has been developed and experimentally tested that is suitable for deployment on a weather balloon or tower structure to significantly increase the availability of in situ microphysics retrievals.

  10. Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

    NASA Astrophysics Data System (ADS)

    Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

    2016-04-01

    Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

  11. Imaging diffuse clouds: bright and dark gas mapped in CO

    NASA Astrophysics Data System (ADS)

    Liszt, H. S.; Pety, J.

    2012-05-01

    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

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

    PubMed Central

    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

    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

  13. Imaging spatial correlations of Rydberg excitations in cold atom clouds

    NASA Astrophysics Data System (ADS)

    Schwarzkopf, Andrew; Sapiro, Rachel; Raithel, Georg

    2011-05-01

    Previously, Rydberg excitation blockades have been shown to cause a saturation of Rydberg excitation numbers in atom samples and a narrowing of the excitation number statistics, and they have been employed in quantum information experiments. In the experiment described in this talk, we present measurements of structures in the Rydberg pair correlation function similar to those predicted in. To achieve sufficient spatial magnification, we use the principle of field ion microscopy. A tungsten tip is placed close to a cold atom cloud in which several Rydberg excitations are prepared using a narrow-linewidth laser. To read out the sample, the tip voltage is suddenly switched to a high value. The Rydberg atoms are field-ionized, and the resultant ions are projected onto a nearby position-sensitive detector. We present the dependence of the pair correlation function on the principle quantum number and other parameters. We gratefully acknowledge support from AFOSR and NSF-FOCUS.

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

    NASA Astrophysics Data System (ADS)

    Rastogi, Bharat

    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.

  15. An objective classification of Saturn cloud features from Cassini ISS images

    NASA Astrophysics Data System (ADS)

    Del Genio, Anthony D.; Barbara, John M.

    2016-06-01

    A k-means clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturn's northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible-infrared images of Earth. It provides a new perspective on giant planet cloud morphology and its relationship to the dynamics and a meteorological context for the analysis of other types of simultaneous Saturn observations. The method identifies 6 clusters that exhibit distinct morphology, vertical structure, and preferred latitudes of occurrence. These correspond to areas dominated by deep convective cells; low contrast areas, some including thinner and thicker clouds possibly associated with baroclinic instability; regions with possible isolated thin cirrus clouds; darker areas due to thinner low level clouds or clearer skies due to downwelling, or due to absorbing particles; and fields of relatively shallow cumulus clouds. The spatial associations among these cloud types suggest that dynamically, there are three distinct types of latitude bands on Saturn: deep convectively disturbed latitudes in cyclonic shear regions poleward of the eastward jets; convectively suppressed regions near and surrounding the westward jets; and baroclinically unstable latitudes near eastward jet cores and in the anti-cyclonic regions equatorward of them. These are roughly analogous to some of the features of Earth's tropics, subtropics, and midlatitudes, respectively. This classification may be more useful for dynamics purposes than the traditional belt-zone partitioning. Temporal variations of feature contrast and cluster occurrence suggest that the upper tropospheric haze in the northern hemisphere may have thickened by 2014. The results suggest that routine use of clustering may be a worthwhile complement to many different types of planetary atmospheric data analysis.

  16. An Objective Classification of Saturn Cloud Features from Cassini ISS Images

    NASA Technical Reports Server (NTRS)

    Del Genio, Anthony D.; Barbara, John M.

    2016-01-01

    A k -means clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturn's northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible- infrared images of Earth. It provides a new perspective on giant planet cloud morphology and its relationship to the dynamics and a meteorological context for the analysis of other types of simultaneous Saturn observations. The method identifies 6 clusters that exhibit distinct morphology, vertical structure, and preferred latitudes of occurrence. These correspond to areas dominated by deep convective cells; low contrast areas, some including thinner and thicker clouds possibly associated with baroclinic instability; regions with possible isolated thin cirrus clouds; darker areas due to thinner low level clouds or clearer skies due to downwelling, or due to absorbing particles; and fields of relatively shallow cumulus clouds. The spatial associations among these cloud types suggest that dynamically, there are three distinct types of latitude bands on Saturn: deep convectively disturbed latitudes in cyclonic shear regions poleward of the eastward jets; convectively suppressed regions near and surrounding the westward jets; and baro-clinically unstable latitudes near eastward jet cores and in the anti-cyclonic regions equatorward of them. These are roughly analogous to some of the features of Earth's tropics, subtropics, and midlatitudes, respectively. This classification may be more useful for dynamics purposes than the traditional belt-zone partitioning. Temporal variations of feature contrast and cluster occurrence suggest that the upper tropospheric haze in the northern hemisphere may have thickened by 2014. The results suggest that routine use of clustering may be a worthwhile complement to many different types of planetary atmospheric data analysis.

  17. The method of cloud statistics measured with digital holographic imaging system

    NASA Astrophysics Data System (ADS)

    Li, Baosheng; Ma, Fei; Huang, Meng

    2015-11-01

    Due to the structure of clouds has so many complicated factors, the cloud seeding area is difficult to accurately determined. How to accurately understand the structures of the particle parameters has great significance for weather modification. Digital holographic technology is widely used in particle measurement, because it can realize the three-dimensional particle field measurement and get detail parameters. This paper, based on the research of the holographic reconstruction and image processing algorithm, calculate the equivalent diameter of particle, and obtain the distribution of the particles, for the estimation of the population parameter of particle is put forward a feasible method.

  18. [The processing of point clouds for brain deformation existing in image guided neurosurgery system].

    PubMed

    Yao, Xufeng; Lin, Yixun; Song, Zhijian

    2008-08-01

    The finite element method (FEM) plays an important role in solving the brain deformation problem in the image guided neurosurgery system. The position of the brain cortex during the surgery provides the boundary condition for the FEM model. In this paper, the information of brain cortex is represented by the unstructured points and the boundary condition is achieved by the processing of unstructured points. The processing includes the mapping of texture, segmentation, simplification and denoising. The method of k-nearest clustering based on local surface properties is used to simplify and denoise the unstructured point clouds. The results of experiment prove the efficiency of point clouds processing.

  19. PET Image Reconstruction and Deformable Motion Correction Using Unorganized Point Clouds.

    PubMed

    Klyuzhin, Ivan; Sossi, Vesna

    2017-03-02

    Quantitative PET imaging often requires correcting the image data for deformable motion. With cyclic motion, this is traditionally achieved by separating the coincidence data into a relatively small number of gates, and incorporating the inter-gate image transformation matrices into the reconstruction algorithm. In the presence of non-cyclic deformable motion, this approach may be impractical due to a large number of required gates. In this work, we propose an alternative approach to iterative image reconstruction with correction for deformable motion, wherein unorganized point clouds are used to model the imaged objects in the image space, and motion is corrected for explicitly by introducing a time-dependency into the point coordinates. The image function is represented using constant basis functions with finite support determined by the boundaries of the Voronoi cells in the point cloud. We validate the quantitative accuracy and stability of the proposed approach by reconstructing noise-free and noisy projection data from digital and physical phantoms. The pointcloud based MLEM and one-pass list-mode OSEM algorithms are validated. The results demonstrate that images reconstructed using the proposed method are quantitatively stable, with noise and convergence properties comparable to image reconstruction based on the use of rectangular and radially-symmetric basis functions.

  20. Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

    NASA Astrophysics Data System (ADS)

    Ai, Yufei; Li, Jun; Shi, Wenjing; Schmit, Timothy J.; Cao, Changyong; Li, Wanbiao

    2017-02-01

    Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.

  1. Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

    NASA Astrophysics Data System (ADS)

    Champion, N.

    2012-08-01

    Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

  2. New public dataset for spotting patterns in medieval document images

    NASA Astrophysics Data System (ADS)

    En, Sovann; Nicolas, Stéphane; Petitjean, Caroline; Jurie, Frédéric; Heutte, Laurent

    2017-01-01

    With advances in technology, a large part of our cultural heritage is becoming digitally available. In particular, in the field of historical document image analysis, there is now a growing need for indexing and data mining tools, thus allowing us to spot and retrieve the occurrences of an object of interest, called a pattern, in a large database of document images. Patterns may present some variability in terms of color, shape, or context, making the spotting of patterns a challenging task. Pattern spotting is a relatively new field of research, still hampered by the lack of available annotated resources. We present a new publicly available dataset named DocExplore dedicated to spotting patterns in historical document images. The dataset contains 1500 images and 1464 queries, and allows the evaluation of two tasks: image retrieval and pattern localization. A standardized benchmark protocol along with ad hoc metrics is provided for a fair comparison of the submitted approaches. We also provide some first results obtained with our baseline system on this new dataset, which show that there is room for improvement and that should encourage researchers of the document image analysis community to design new systems and submit improved results.

  3. Investigation of Optimal Digital Image Correlation Patterns for Deformation Measurement

    NASA Technical Reports Server (NTRS)

    Bomarito, G. F.; Ruggles, T. J.; Hochhalter, J. D.; Cannon, A. H.

    2016-01-01

    Digital image correlation (DIC) relies on the surface texture of a specimen to measure deformation. When the specimen itself has little or no texture, a pattern is applied to the surface which deforms with the specimen and acts as an artificial surface texture. Because the applied pattern has an effect on the accuracy of DIC, an ideal pattern is sought for which the error introduced into DIC measurements is minimal. In this work, a study is performed in which several DIC pattern quality metrics from the literature are correlated to DIC measurement error. The resulting correlations give insight on the optimality of DIC patterns in general. Optimizations are then performed to produce patterns which are well suited for DIC. These patterns are tested to show their relative benefits. Chief among these benefits are a reduction in error of approximately 30 with respect to a randomly generated pattern.

  4. Optimizing Cloud Based Image Storage, Dissemination and Processing Through Use of Mrf and Lerc

    NASA Astrophysics Data System (ADS)

    Becker, Peter; Plesea, Lucian; Maurer, Thomas

    2016-06-01

    The volume and numbers of geospatial images being collected continue to increase exponentially with the ever increasing number of airborne and satellite imaging platforms, and the increasing rate of data collection. As a result, the cost of fast storage required to provide access to the imagery is a major cost factor in enterprise image management solutions to handle, process and disseminate the imagery and information extracted from the imagery. Cloud based object storage offers to provide significantly lower cost and elastic storage for this imagery, but also adds some disadvantages in terms of greater latency for data access and lack of traditional file access. Although traditional file formats geoTIF, JPEG2000 and NITF can be downloaded from such object storage, their structure and available compression are not optimum and access performance is curtailed. This paper provides details on a solution by utilizing a new open image formats for storage and access to geospatial imagery optimized for cloud storage and processing. MRF (Meta Raster Format) is optimized for large collections of scenes such as those acquired from optical sensors. The format enables optimized data access from cloud storage, along with the use of new compression options which cannot easily be added to existing formats. The paper also provides an overview of LERC a new image compression that can be used with MRF that provides very good lossless and controlled lossy compression.

  5. Cloud detection in all-sky images via multi-scale neighborhood features and multiple supervised learning techniques

    NASA Astrophysics Data System (ADS)

    Cheng, Hsu-Yung; Lin, Chih-Lung

    2017-01-01

    Cloud detection is important for providing necessary information such as cloud cover in many applications. Existing cloud detection methods include red-to-blue ratio thresholding and other classification-based techniques. In this paper, we propose to perform cloud detection using supervised learning techniques with multi-resolution features. One of the major contributions of this work is that the features are extracted from local image patches with different sizes to include local structure and multi-resolution information. The cloud models are learned through the training process. We consider classifiers including random forest, support vector machine, and Bayesian classifier. To take advantage of the clues provided by multiple classifiers and various levels of patch sizes, we employ a voting scheme to combine the results to further increase the detection accuracy. In the experiments, we have shown that the proposed method can distinguish cloud and non-cloud pixels more accurately compared with existing works.

  6. Cirrus cloud detection from airborne imaging spectrometer data using the 1.38 micron water vapor band

    NASA Technical Reports Server (NTRS)

    Gao, Bo-Cai; Goetz, Alexander F. H.; Wiscombe, Warren J.

    1993-01-01

    Using special images acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) at 20 km altitude, we show that wavelengths close to the center of the strong 1.38 micron water vapor band are useful for detecting thin cirrus clouds. The detection makes use of the fact that cirrus clouds are located above almost all the atmospheric water vapor. Because of the strong water vapor absorption in the lower atmosphere, AVIRIS channels near 1.38 micron receive little scattered solar radiance from the surface of low level clouds. When cirrus clouds are present, however, these channels receive large amounts of scattered solar radiance from the cirrus clouds. Our ability to determine cirrus cloud cover using space-based remote sensing will be improved if channels near the center of the 1.38 micron water vapor band are added to future satellites.

  7. Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

    NASA Astrophysics Data System (ADS)

    Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

    2016-04-01

    Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

  8. Estimating errors in cloud amount and cloud optical thickness due to limited spatial sampling using a satellite imager as a proxy for nadir-view sensors

    NASA Astrophysics Data System (ADS)

    Liu, Yinghui

    2015-07-01

    Cloud climatologies from space-based active sensors have been used in climate and other studies without their uncertainties specified. This study quantifies the errors in monthly mean cloud amount and optical thickness due to the limited spatial sampling of space-based active sensors. Nadir-view observations from a satellite imager, the Moderate Resolution Imaging Spectroradiometer (MODIS), serve as a proxy for those active sensors and observations within 10° of the sensor's nadir view serve as truth for data from 2003 to 2013 in the Arctic. June-July monthly mean cloud amount and liquid water and ice cloud optical thickness from MODIS for both observations are calculated and compared. Results show that errors increase with decreasing sample numbers for monthly means in cloud amount and cloud optical thickness. The root-mean-square error of monthly mean cloud amount from nadir-view observations increases with lower latitudes, with 0.7% (1.4%) at 80°N and 4.2% (11.2%) at 60°N using data from 2003 to 2013 (from 2012). For a 100 km resolution Equal-Area Scalable Earth Grid (EASE-Grid) cell of 1000 sample numbers, the absolute differences in these two monthly mean cloud amounts are less than 6.5% (9.0%, 11.5%) with an 80 (90, 95)%chance; such differences decrease to 4.0% (5.0%, 6.5%) with 5000 sample numbers. For a 100 km resolution EASE-Grid of 1000 sample numbers, the absolute differences in these two monthly mean cloud optical thicknesses are less than 2.7 (3.8) with a 90% chance for liquid water cloud (ice cloud); such differences decrease to 1.3 (1.0) for 5000 sample numbers. The uncertainties in monthly mean cloud amount and optical thickness estimated in this study may provide useful information for applying cloud climatologies from active sensors in climate studies and suggest the need for future spaceborne active sensors with a wide swath.

  9. Multiscale vector fields for image pattern recognition

    NASA Technical Reports Server (NTRS)

    Low, Kah-Chan; Coggins, James M.

    1990-01-01

    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.

  10. Looking back, looking forward: Scientific and technological advances in multiangle imaging of aerosols and clouds

    NASA Astrophysics Data System (ADS)

    Diner, David J.; Garay, Michael J.

    2017-02-01

    Passive optical multiangle observations enable retrieval of information about atmospheric structure than cannot be obtained with single-angle sensors. This paper highlights several applications to studies of aerosols and clouds, using data from the Multi-angle Imaging SpectroRadiometer (MISR), currently in its 17th year in Earth orbit aboard NASA's Terra spacecraft, and the airborne Multiangle SpectroPolarimetric Imager (AirMSPI), which flies aboard NASA's ER-2 high-altitude aircraft. The recently selected Multi-Angle Imager for Aerosols (MAIA), which will launch into Earth orbit early in the next decade, is also discussed.

  11. Ice cloud properties in ice-over-water cloud systems using Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and TRMM Microwave Imager data

    NASA Astrophysics Data System (ADS)

    Minnis, Patrick; Huang, Jianping; Lin, Bing; Yi, Yuhong; Arduini, Robert F.; Fan, Tai-Fang; Ayers, J. Kirk; Mace, Gerald G.

    2007-03-01

    A multilayered cloud retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water clouds using Visible and Infrared Scanner (VIRS) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) measurements acquired over the Tropics between January and August 1998. Lookup tables of top-of-atmosphere 0.65-μm reflectance are developed for ice-over-water cloud systems using radiative transfer calculations for various combinations of ice-over-water cloud layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave (MW), visible (VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level cloud properties to select the proper lookup table. The properties of the upper-level ice clouds, such as optical depth and effective size, are then derived using the Visible-Infrared Solar-infrared Split-Window technique (VISST), which matches the VIRS IR, 3.9 μm, and VIS data to the multilayer cloud lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped clouds by 42 and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water cloud systems. The tropical distribution of ice-over-water clouds is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values and exceed those of single-layered clouds by 7 and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped clouds over two surface sites, and the standard deviations of the differences are similar to those for single-layered clouds. Examples of

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

    NASA Technical Reports Server (NTRS)

    Dhuria, Harbans L.

    1992-01-01

    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.

  13. Registration of Vehicle-Borne Point Clouds and Panoramic Images Based on Sensor Constellations.

    PubMed

    Yao, Lianbi; Wu, Hangbin; Li, Yayun; Meng, Bin; Qian, Jinfei; Liu, Chun; Fan, Hongchao

    2017-04-11

    A mobile mapping system (MMS) is usually utilized to collect environmental data on and around urban roads. Laser scanners and panoramic cameras are the main sensors of an MMS. This paper presents a new method for the registration of the point clouds and panoramic images based on sensor constellation. After the sensor constellation was analyzed, a feature point, the intersection of the connecting line between the global positioning system (GPS) antenna and the panoramic camera with a horizontal plane, was utilized to separate the point clouds into blocks. The blocks for the central and sideward laser scanners were extracted with the segmentation feature points. Then, the point clouds located in the blocks were separated from the original point clouds. Each point in the blocks was used to find the accurate corresponding pixel in the relative panoramic images via a collinear function, and the position and orientation relationship amongst different sensors. A search strategy is proposed for the correspondence of laser scanners and lenses of panoramic cameras to reduce calculation complexity and improve efficiency. Four cases of different urban road types were selected to verify the efficiency and accuracy of the proposed method. Results indicate that most of the point clouds (with an average of 99.7%) were successfully registered with the panoramic images with great efficiency. Geometric evaluation results indicate that horizontal accuracy was approximately 0.10-0.20 m, and vertical accuracy was approximately 0.01-0.02 m for all cases. Finally, the main factors that affect registration accuracy, including time synchronization amongst different sensors, system positioning and vehicle speed, are discussed.

  14. Cloud discrimination and spectral radiance estimation from a digital sky images

    NASA Astrophysics Data System (ADS)

    Saito, M.; Iwabuchi, H.; Murata, I.

    2015-12-01

    Clouds cover more than 60% of the globe with high impacts on incoming solar irradiance on the ground as well as the radiative energy transfer in the Earth-atmosphere system. Several method for detecting clouds from sky images have been developed, and digital signals available from the JPEG image have nonlinear relationship with the corresponding spectral radiances, which may lead to cloud misclassifications. In this work, a method for cloud discrimination from sky images in RAW format taken from a commercial digital camera is developed. The method uses the clear sky index (CSI). In order to take into account the spectral response in red-green-blue (RGB) channels of the camera as well as lens characteristics, these characteristics are first inferred very accurately with a laboratory experiment. Spectral radiance is represented in a simple form with spectra of incoming solar radiation at the top of atmosphere and ozone transmittance and a polynominal with three coefficients that include the intensity index, the molecular index (MI) and the small particle index (SPI). These coefficients can be obtained from the digital RGB RAW counts by linear transformation. The MI and the SPI can be converted to the CSI, which takes different value from that at clear sky and cloudy pixels. Simultaneous observations with the lidar and the digital camera at Tohoku University show that the CSI can discriminate cloud and clear sky at every pixel with correct discrimination rate more than 90%. Furthermore, spectral distribution of sky radiance can also be estimated at every pixel, and estimated ones are consistent with those from spectrometer and those from radiative transfer simulations under various sky conditions in a wavelength range of 430-680 nm with mean biases lower than 3% and bias standard deviations smaller than 1%.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    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.

  16. Data integration: Combined Imaging and Electrophysiology data in the cloud

    PubMed Central

    Kini, Lohith G.; Davis, Kathryn A.; Wagenaar, Joost B.

    2015-01-01

    There has been an increasing effort to correlate electrophysiology data with imaging in patients with refractory epilepsy over recent years. IEEG.org provides a free-access, rapidly growing archive of imaging data combined with electrophysiology data and patient metadata. It currently contains over 1200 human and animal datasets, with multiple data modalities associated with each dataset (neuroimaging, EEG, EKG, de-identified clinical and experimental data, etc.). The platform is developed around the concept that scientific data sharing requires a flexible platform that allows sharing of data from multiple file-formats. IEEG.org provides high and low-level access to the data in addition to providing an environment in which domain experts can find, visualize, and analyze data in an intuitive manner. Here, we present a summary of the current infrastructure of the platform, available datasets and goals for the near future. PMID:26044858

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

    PubMed

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

    1995-06-23

    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.

  18. Retrieval of Cloud Phase Using the Moderate Resolution Imaging Spectroradiometer Data during the Mixed-Phase Arctic Cloud Experiment

    SciTech Connect

    Spangenberg, D.; Minnis, P.; Shupe, M.; Uttal, T.; Poellot, M.

    2005-03-18

    Improving climate model predictions over Earth's polar regions requires a comprehensive knowledge of polar cloud microphysics. Over the Arctic, there is minimal contrast between the clouds and background snow surface, making it difficult to detect clouds and retrieve their phase from space. Snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds make it even more difficult to determine cloud phase. Also, since determining cloud phase is the first step toward analyzing cloud optical depth, particle size, and water content, it is vital that the phase be correct in order to obtain accurate microphysical and bulk properties. Changes in these cloud properties will, in turn, affect the Arctic climate since clouds are expected to play a critical role in the sea ice albedo feedback. In this paper, the IR trispectral technique (IRTST) is used as a starting point for a WV and 11-{micro}m brightness temperature (T11) parameterization (WVT11P) of cloud phase using MODIS data. In addition to its ability to detect mixed-phase clouds, the WVT11P also has the capability to identify thin cirrus clouds overlying mixed or liquid phase clouds (multiphase ice). Results from the Atmospheric Radiation Measurement (ARM) MODIS phase model (AMPHM) are compared to the surface-based cloud phase retrievals over the ARM North Slope of Alaska (NSA) Barrow site and to in-situ data taken from University of North Dakota Citation (CIT) aircraft which flew during the Mixed-Phase Arctic Cloud Experiment (MPACE). It will be shown that the IRTST and WVT11P combined to form the AMPHM can achieve a relative high accuracy of phase discrimination compared to the surface-based retrievals. Since it only uses MODIS WV and IR channels, the AMPHM is robust in the sense that it can be applied to daytime, twilight, and nighttime scenes with no discontinuities in the output phase.

  19. Pattern based 3D image Steganography

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

    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.

  20. Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

    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.

  1. Partial difference operators on weighted graphs for image processing on surfaces and point clouds.

    PubMed

    Lozes, Francois; Elmoataz, Abderrahim; Lezoray, Olivier

    2014-09-01

    Partial difference equations (PDEs) and variational methods for image processing on Euclidean domains spaces are very well established because they permit to solve a large range of real computer vision problems. With the recent advent of many 3D sensors, there is a growing interest in transposing and solving PDEs on surfaces and point clouds. In this paper, we propose a simple method to solve such PDEs using the framework of PDEs on graphs. This latter approach enables us to transcribe, for surfaces and point clouds, many models and algorithms designed for image processing. To illustrate our proposal, three problems are considered: (1) p -Laplacian restoration and inpainting; (2) PDEs mathematical morphology; and (3) active contours segmentation.

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    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).

  3. Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

    NASA Astrophysics Data System (ADS)

    Chen, Yi-Chen; Lin, Chao-Hung

    2016-06-01

    With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

    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

  5. The Direct Registration of LIDAR Point Clouds and High Resolution Image Based on Linear Feature by Introducing AN Unknown Parameter

    NASA Astrophysics Data System (ADS)

    Chunjing, Y.; Guang, G.

    2012-07-01

    The registration between optical images and point clouds is the first task when the combination of these two datasets is concerned. Due to the discrete nature of the point clouds, and the 2D-3D transformation in particular, a tie points based registration strategy which is commonly adopted in image-to-image registration is hard to be used directly in this scenario. A derived collinear equation describing the map relationship between an image point and a ground point is used as the mathematical model for registration, with the point in the LiDAR space expressed by its parametric form. such a map relation can be viewed as the mathematical model which registers the image pixels to point clouds. This model is not only suitable for a single image registration but also applicable to multiple consecutive images. We also studied scale problem in image and point clouds registration, with scale problem is defined by the optimal corresponding between the image resolution and the density of point clouds. Test dataset includes the DMC images and point clouds acquired by the Leica ALS50 II over an area in Henan Prov., China. Main contributions of the paper includes: [1] an derived collinear equation is introduced by which a ground point is expressed by its parametric form, which makes it possible to replace point feature by linear feature, hence avoiding the problem that it is almost impossible to find a point in the point clouds which is accurately corresponds to a point in the image space; [2] least square method is used to calculate the registration transformation parameters and the unknown parameter λ in the same time;[3] scale problem is analyzed semi-quantitatively and to the authors' best knowledge, it is the first time in literature that clearly defines the scale problem and carries out semi-quantitative analysis in the context of LiDAR data processing.

  6. Image continuity at different levels of zoom for fringe patterns.

    PubMed

    Abolbashari, Mehrdad; Gerges, Awad S; Davies, Angela; Farahi, Faramarz

    2012-01-02

    Fringe patterns are raw output data from many measurement systems including laser interferometers and moiré systems. For instruments with a range of zoom levels to measure the object at different scales, a technique (algorithm) is needed to combine and/or compare data to obtain information at different levels of details. A technique to keep the continuity of output images both at different levels of zoom and within the same level of zoom is developed and demonstrated. Image registration is used to correlate images, find relative zoom values, and obtain shift between images in the lateral plane. Fringe patterns from a moiré system and a laser interferometer are used as images to be stitched and demonstrate the technique. Interferomteric fringes are used to find the required parameters to inter-relate locations and scale of the fringe patterns at different levels of zoom. The calculated parameters are scale and translation in both directions; these parameters make it possible to locate the coordinates of the region that the measurement system is zoomed in on, related to the area with lower magnification and relative locations of images within the same level of zoom. Results show that this technique is capable of finding the scale and shift parameters within the resolution of one pixel and therefore can restore continuity between images at different levels of zoom.

  7. Cloud Ozone Dust Imager (CODI). Volume 1; Investigation and Technical Plan

    NASA Technical Reports Server (NTRS)

    Clancy, R. Todd; Dusenbery, Paul; Wolff, Michael; James, Phil; Allen, Mark; Goguen, Jay; Kahn, Ralph; Gladstone, Rany; Murphy, Jim

    1995-01-01

    The Cloud Ozone Dust Imager (CODI) is proposed to investigate the current climatic balance of the Mars atmosphere, with particular emphasis on the important but poorly understood roles which dust and water ice aerosols play in this balance. The large atmospheric heating (20-50 K) resulting from global dust storms around Mars perihelion is well recognized. However, groundbased observations of Mars atmospheric temperatures, water vapor, and clouds since the Viking missions have identified a much colder, cloudier atmosphere around Mars aphelion that may prove as important as global dust storms in determining the interannual and long-term behavior of the Mars climate. The key climate issues CODI is designed to investigate are: 1) the degree to which non-linear interactions between atmospheric dust heating, water vapor saturation, and cloud nucleation influence the seasonal and interannual variability of the Mars atmosphere, and 2) whether the strong orbital forcing of atmospheric dust loading, temperatures and water vapor saturation determines the long-term balance of Mars water, as reflected in the north-south hemispheric asymmetries of atmospheric water vapor and polar water ice abundances. The CODI experiment will measure the daily, seasonal and (potentially) interannual variability of atmospheric dust and cloud opacities, and the key physical properties of these aerosols which determine their role in the climate cycles of Mars. CODI is a small (1.2 kg), fixed pointing camera, in which four wide-angle (+/- 70 deg) lenses illuminate fixed filters and CCD arrays. Simultaneous sky/surface imaging of Mars is obtained at an angular resolution of 0.28 deg/pixel for wavelengths of 255, 336, 502, and 673 nm (similar to Hubble Space Telescope filters). These wavelengths serve to measure atmospheric ozone (255 and 336 nm), discriminate ice and dust aerosols (336 and 673 nm), and construct color images (336, 502, and 673 nm). The CODI images are detected on four 512 x 512

  8. Reconstruction of Indoor Models Using Point Clouds Generated from Single-Lens Reflex Cameras and Depth Images

    NASA Astrophysics Data System (ADS)

    Tsai, F.; Wu, T.-S.; Lee, I.-C.; Chang, H.; Su, A. Y. S.

    2015-05-01

    This paper presents a data acquisition system consisting of multiple RGB-D sensors and digital single-lens reflex (DSLR) cameras. A systematic data processing procedure for integrating these two kinds of devices to generate three-dimensional point clouds of indoor environments is also developed and described. In the developed system, DSLR cameras are used to bridge the Kinects and provide a more accurate ray intersection condition, which takes advantage of the higher resolution and image quality of the DSLR cameras. Structure from Motion (SFM) reconstruction is used to link and merge multiple Kinect point clouds and dense point clouds (from DSLR color images) to generate initial integrated point clouds. Then, bundle adjustment is used to resolve the exterior orientation (EO) of all images. Those exterior orientations are used as the initial values to combine these point clouds at each frame into the same coordinate system using Helmert (seven-parameter) transformation. Experimental results demonstrate that the design of the data acquisition system and the data processing procedure can generate dense and fully colored point clouds of indoor environments successfully even in featureless areas. The accuracy of the generated point clouds were evaluated by comparing the widths and heights of identified objects as well as coordinates of pre-set independent check points against in situ measurements. Based on the generated point clouds, complete and accurate three-dimensional models of indoor environments can be constructed effectively.

  9. Single-pixel optical imaging with compressed reference intensity patterns

    NASA Astrophysics Data System (ADS)

    Chen, Wen; Chen, Xudong

    2015-03-01

    Ghost imaging with single-pixel bucket detector has attracted more and more current attention due to its marked physical characteristics. However, in ghost imaging, a large number of reference intensity patterns are usually required for object reconstruction, hence many applications based on ghost imaging (such as tomography and optical security) may be tedious since heavy storage or transmission is requested. In this paper, we report that the compressed reference intensity patterns can be used for object recovery in computational ghost imaging (with single-pixel bucket detector), and object verification can be further conducted. Only a small portion (such as 2.0% pixels) of each reference intensity pattern is used for object reconstruction, and the recovered object is verified by using nonlinear correlation algorithm. Since statistical characteristic and speckle averaging property are inherent in ghost imaging, sidelobes or multiple peaks can be effectively suppressed or eliminated in the nonlinear correlation outputs when random pixel positions are selected from each reference intensity pattern. Since pixel positions can be randomly selected from each 2D reference intensity pattern (such as total measurements of 20000), a large key space and high flexibility can be generated when the proposed method is applied for authenticationbased cryptography. When compressive sensing is used to recover the object with a small number of measurements, the proposed strategy could still be feasible through further compressing the recorded data (i.e., reference intensity patterns) followed by object verification. It is expected that the proposed method not only compresses the recorded data and facilitates the storage or transmission, but also can build up novel capability (i.e., classical or quantum information verification) for ghost imaging.

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

    SciTech Connect

    Watson, A.I.; Lopez, R.E.; Holle, R.L.

    1994-08-01

    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.

  11. Hubble space telescope imaging of decoupled dust clouds in the ram pressure stripped Virgo spirals NGC 4402 and NGC 4522

    SciTech Connect

    Abramson, Anne; Kenney, Jeffrey D. P. E-mail: jeff.kenney@yale.edu

    2014-03-01

    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 + H{sub 2} 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 (∼10{sup 4}-10{sup 5} M {sub ☉}), we estimate that only a small fraction (∼1%-10%) of the original H I + H{sub 2} remains in the parts of the disks with decoupled clouds. Based on Hα 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.

  12. Local structure co-occurrence pattern for image retrieval

    NASA Astrophysics Data System (ADS)

    Zhang, Ke; Zhang, Fan; Lu, Jia; Lu, Yinghua; Kong, Jun; Zhang, Ming

    2016-03-01

    Image description and annotation is an active research topic in content-based image retrieval. How to utilize human visual perception is a key approach to intelligent image feature extraction and representation. This paper has proposed an image feature descriptor called the local structure co-occurrence pattern (LSCP). LSCP extracts the whole visual perception for an image by building a local binary structure, and it is represented by a color-shape co-occurrence matrix which explores the relationship of multivisual feature spaces according to visual attention mechanism. As a result, LSCP not only describes low-level visual features integrated with texture feature, color feature, and shape feature but also bridges high-level semantic comprehension. Extensive experimental results on an image retrieval task on the benchmark datasets, corel-10,000, MIT VisTex, and INRIA Holidays, have demonstrated the usefulness, effectiveness, and robustness of the proposed LSCP.

  13. CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency

    PubMed Central

    2015-01-01

    Background The Internet has greatly enhanced health care, helping patients stay up-to-date on medical issues and general knowledge. Many cancer patients use the Internet for cancer diagnosis and related information. Recently, cloud computing has emerged as a new way of delivering health services but currently, there is no generic and fully automated cloud-based self-management intervention for breast cancer patients, as practical guidelines are lacking. Objective We investigated the prevalence and predictors of cloud use for medical diagnosis among women with breast cancer to gain insight into meaningful usage parameters to evaluate the use of generic, fully automated cloud-based self-intervention, by assessing how breast cancer survivors use a generic self-management model. The goal of this study was implemented and evaluated with a new prototype called “CIMIDx”, based on representative association rules that support the diagnosis of medical images (mammograms). Methods The proposed Cloud-Based System Support Intelligent Medical Image Diagnosis (CIMIDx) prototype includes two modules. The first is the design and development of the CIMIDx training and test cloud services. Deployed in the cloud, the prototype can be used for diagnosis and screening mammography by assessing the cancers detected, tumor sizes, histology, and stage of classification accuracy. To analyze the prototype’s classification accuracy, we conducted an experiment with data provided by clients. Second, by monitoring cloud server requests, the CIMIDx usage statistics were recorded for the cloud-based self-intervention groups. We conducted an evaluation of the CIMIDx cloud service usage, in which browsing functionalities were evaluated from the end-user’s perspective. Results We performed several experiments to validate the CIMIDx prototype for breast health issues. The first set of experiments evaluated the diagnostic performance of the CIMIDx framework. We collected medical information

  14. Image analysis of dye stained patterns in soils

    NASA Astrophysics Data System (ADS)

    Bogner, Christina; Trancón y Widemann, Baltasar; Lange, Holger

    2013-04-01

    Quality of surface water and groundwater is directly affected by flow processes in the unsaturated zone. In general, it is difficult to measure or model water flow. Indeed, parametrization of hydrological models is problematic and often no unique solution exists. To visualise flow patterns in soils directly dye tracer studies can be done. These experiments provide images of stained soil profiles and their evaluation demands knowledge in hydrology as well as in image analysis and statistics. First, these photographs are converted to binary images classifying the pixels in dye stained and non-stained ones. Then, some feature extraction is necessary to discern relevant hydrological information. In our study we propose to use several index functions to extract different (ideally complementary) features. We associate each image row with a feature vector (i.e. a certain number of image function values) and use these features to cluster the image rows to identify similar image areas. Because images of stained profiles might have different reasonable clusterings, we calculate multiple consensus clusterings. An expert can explore these different solutions and base his/her interpretation of predominant flow mechanisms on quantitative (objective) criteria. The complete workflow from reading-in binary images to final clusterings has been implemented in the free R system, a language and environment for statistical computing. The calculation of image indices is part of our own package Indigo, manipulation of binary images, clustering and visualization of results are done using either build-in facilities in R, additional R packages or the LATEX system.

  15. Patterns in Saccharomyces cerevisiae yeast colonies via magnetic resonance imaging.

    PubMed

    Tenório, Rômulo P; Barros, Wilson

    2017-01-23

    We report the use of high-resolution magnetic resonance imaging methods to observe pattern formation in colonies of Saccharomyces cerevisiae. Our results indicate substantial signal loss localized in specific regions of the colony rendering useful imaging contrast. This imaging contrast is recognizable as being due to discontinuities in magnetic susceptibility (χ) between different spatial regions. At the microscopic pixel level, the local variations in the magnetic susceptibility (Δχ) induce a loss in the NMR signal, which was quantified via T2 and T2* maps, permitting estimation of Δχ values for different regions of the colony. Interestingly the typical petal/wrinkling patterns present in the colony have a high degree of correlation with the estimated susceptibility distribution. We conclude that the presence of magnetic susceptibility inclusions, together with their spatial arrangement within the colony, may be a potential cause of the susceptibility distribution and therefore the contrast observed on the images.

  16. Hex-square moire patterns in imagers using microchannel plates

    NASA Technical Reports Server (NTRS)

    Lawrence, George M.

    1989-01-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

    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.

  18. High-speed imaging of blood splatter patterns

    SciTech Connect

    McDonald, T.E.; Albright, K.A.; King, N.S.P.; Yates, G.J. ); Levine, G.F. . Bureau of Forensic Services)

    1993-01-01

    The interpretation of blood splatter patterns is an important element in reconstructing the events and circumstances of an accident or crime scene. Unfortunately, the interpretation of patterns and stains formed by blood droplets is not necessarily intuitive and study and analysis are required to arrive at a correct conclusion. A very useful tool in the study of blood splatter patterns is high-speed photography. Scientists at the Los Alamos National Laboratory, Department of Energy (DOE), and Bureau of Forensic Services, State of California, have assembled a high-speed imaging system designed to image blood splatter patterns. The camera employs technology developed by Los Alamos for the underground nuclear testing program and has also been used in a military mine detection program. The camera uses a solid-state CCD sensor operating at approximately 650 frames per second (75 MPixels per second) with a microchannel plate image intensifier that can provide shuttering as short as 5 ns. The images are captured with a laboratory high-speed digitizer and transferred to an IBM compatible PC for display and hard copy output for analysis. The imaging system is described in this paper.

  19. High-speed imaging of blood splatter patterns

    SciTech Connect

    McDonald, T.E.; Albright, K.A.; King, N.S.P.; Yates, G.J.; Levine, G.F.

    1993-05-01

    The interpretation of blood splatter patterns is an important element in reconstructing the events and circumstances of an accident or crime scene. Unfortunately, the interpretation of patterns and stains formed by blood droplets is not necessarily intuitive and study and analysis are required to arrive at a correct conclusion. A very useful tool in the study of blood splatter patterns is high-speed photography. Scientists at the Los Alamos National Laboratory, Department of Energy (DOE), and Bureau of Forensic Services, State of California, have assembled a high-speed imaging system designed to image blood splatter patterns. The camera employs technology developed by Los Alamos for the underground nuclear testing program and has also been used in a military mine detection program. The camera uses a solid-state CCD sensor operating at approximately 650 frames per second (75 MPixels per second) with a microchannel plate image intensifier that can provide shuttering as short as 5 ns. The images are captured with a laboratory high-speed digitizer and transferred to an IBM compatible PC for display and hard copy output for analysis. The imaging system is described in this paper.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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 μm and 8.65-12.05 μm, 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 (α, in m-1) are established for cloud temperatures between 190 and 233 K. An average global power law relationship IWC = 75. α1.23 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

  1. Automatic Detection of Building Points from LIDAR and Dense Image Matching Point Clouds

    NASA Astrophysics Data System (ADS)

    Maltezos, E.; Ioannidis, C.

    2015-08-01

    This study aims to detect automatically building points: (a) from LIDAR point cloud using simple techniques of filtering that enhance the geometric properties of each point, and (b) from a point cloud which is extracted applying dense image matching at high resolution colour-infrared (CIR) digital aerial imagery using the stereo method semi-global matching (SGM). At first step, the removal of the vegetation is carried out. At the LIDAR point cloud, two different methods are implemented and evaluated using initially the normals and the roughness values afterwards: (1) the proposed scan line smooth filtering and a thresholding process, and (2) a bilateral filtering and a thresholding process. For the case of the CIR point cloud, a variation of the normalized differential vegetation index (NDVI) is computed for the same purpose. Afterwards, the bare-earth is extracted using a morphological operator and removed from the rest scene so as to maintain the buildings points. The results of the extracted buildings applying each approach at an urban area in northern Greece are evaluated using an existing orthoimage as reference; also, the results are compared with the corresponding classified buildings extracted from two commercial software. Finally, in order to verify the utility and functionality of the extracted buildings points that achieved the best accuracy, the 3D models in terms of Level of Detail 1 (LoD 1) and a 3D building change detection process are indicatively performed on a sub-region of the overall scene.

  2. IMAGE RELEASE: New Hydrogen Clouds in the M81 Group of Galaxies

    NASA Astrophysics Data System (ADS)

    2008-01-01

    A composite radio-optical image shows five new clouds of hydrogen gas discovered using the National Science Foundation's Robert C. Byrd Green Bank Telescope (GBT). The spiral galaxy M81 and its satellite, M82, are seen in visible light (white); intergalactic hydrogen gas revealed by the GBT is shown in red; and additional hydrogen gas earlier detected by the Very Large Array is shown in green. The M81 Group of galaxies, 11.8 million light-years from Earth, are interacting gravitationally with each other, as shown clearly by the gas streaming among them. The newly-discovered gas clouds, each containing from 14 to 57 million times the mass of our Sun, are similar to gas clouds also found near our own Milky Way Galaxy. Astronomers analyzing these M81 Group clouds conclude that they are likely remnants of earlier interactions among the galaxies and that this indicates that their analogs near the Milky Way had a similar origin. The research team is: Katie Chynoweth, a graduate student at Vanderbilt University; Glen Langston of the National Radio Astronomy Observatory (NRAO); Min Yun of the University of Massachusetts; Felix J. Lockman of NRAO; Kate Rubin of Lick Observatory; and Sarah Scoles of Cornell University. The astronomers presented their findings to the American Astronomical Society's meeting in Austin, Texas. Credit: Chynoweth et al., NRAO/AUI/NSF, Digital Sky Survey. The National Radio Astronomy Observatory is a facility of the National Science Foundation, operated under cooperative agreement by Associated Universities, Inc.

  3. A bayesian approach to deformed pattern matching of iris images.

    PubMed

    Thornton, Jason; Savvides, Marios; Vijaya Kumar, B V K

    2007-04-01

    We describe a general probabilistic framework for matching patterns that experience in-plane nonlinear deformations, such as iris patterns. Given a pair of images, we derive a maximum a posteriori probability (MAP) estimate of the parameters of the relative deformation between them. Our estimation process accomplishes two things simultaneously: It normalizes for pattern warping and it returns a distortion-tolerant similarity metric which can be used for matching two nonlinearly deformed image patterns. The prior probability of the deformation parameters is specific to the pattern-type and, therefore, should result in more accurate matching than an arbitrary general distribution. We show that the proposed method is very well suited for handling iris biometrics, applying it to two databases of iris images which contain real instances of warped patterns. We demonstrate a significant improvement in matching accuracy using the proposed deformed Bayesian matching methodology. We also show that the additional computation required to estimate the deformation is relatively inexpensive, making it suitable for real-time applications.

  4. a Robust Registration Algorithm for Point Clouds from Uav Images for Change Detection

    NASA Astrophysics Data System (ADS)

    Al-Rawabdeh, A.; Al-Gurrani, H.; Al-Durgham, K.; Detchev, I.; He, F.; El-Sheimy, N.; Habib, A.

    2016-06-01

    Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP) registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV) action camera which facilitated capturing high-resolution geo-tagged images in two epochs

  5. Infrared image acquisition system for vein pattern analysis

    NASA Astrophysics Data System (ADS)

    Castro-Ortega, R.; Toxqui-Quitl, C.; Padilla-Vivanco, A.; Solís-Villarreal, J.

    2016-09-01

    The physical shape of the hand vascular distribution contains useful information that can be used for identifying and authenticating purposes; which provide a high level of security as a biometric. Furthermore, this pattern can be used widely in health field such as venography and venipuncture. In this paper, we analyze different IR imaging systems in order to obtain high visibility images of the hand vein pattern. The images are acquired in the range of 400 nm to 1300 nm, using infrared and thermal cameras. For the first image acquisition system, we use a CCD camera and a light source with peak emission in the 880 nm obtaining the images by reflection. A second system consists only of a ThermaCAM P65 camera acquiring the naturally emanating infrared light from the hand. A method of digital image analysis is implemented using Contrast Limited Adaptive Histogram Equalization (CLAHE) to remove noise. Subsequently, adaptive thresholding and mathematical morphology operations are implemented to get the vein pattern distribution.

  6. Natural aerosols explain seasonal and spatial patterns of Southern Ocean cloud albedo

    PubMed Central

    McCoy, Daniel T.; Burrows, Susannah M.; Wood, Robert; Grosvenor, Daniel P.; Elliott, Scott M.; Ma, Po-Lun; Rasch, Phillip J.; Hartmann, Dennis L.

    2015-01-01

    Atmospheric aerosols, suspended solid and liquid particles, act as nucleation sites for cloud drop formation, affecting clouds and cloud properties—ultimately influencing the cloud dynamics, lifetime, water path, and areal extent that determine the reflectivity (albedo) of clouds. The concentration Nd of droplets in clouds that influences planetary albedo is sensitive to the availability of aerosol particles on which the droplets form. Natural aerosol concentrations affect not only cloud properties themselves but also modulate the sensitivity of clouds to changes in anthropogenic aerosols. It is shown that modeled natural aerosols, principally marine biogenic primary and secondary aerosol sources, explain more than half of the spatiotemporal variability in satellite-observed Nd. Enhanced Nd is spatially correlated with regions of high chlorophyll a, and the spatiotemporal variability in Nd is found to be driven primarily by high concentrations of sulfate aerosol at lower Southern Ocean latitudes (35o to 45oS) and by organic matter in sea spray aerosol at higher latitudes (45o to 55oS). Biogenic sources are estimated to increase the summertime mean reflected solar radiation in excess of 10 W m–2 over parts of the Southern Ocean, which is comparable to the annual mean increases expected from anthropogenic aerosols over heavily polluted regions of the Northern Hemisphere. PMID:26601216

  7. Natural aerosols explain seasonal and spatial patterns of Southern Ocean cloud albedo.

    PubMed

    McCoy, Daniel T; Burrows, Susannah M; Wood, Robert; Grosvenor, Daniel P; Elliott, Scott M; Ma, Po-Lun; Rasch, Phillip J; Hartmann, Dennis L

    2015-07-01

    Atmospheric aerosols, suspended solid and liquid particles, act as nucleation sites for cloud drop formation, affecting clouds and cloud properties-ultimately influencing the cloud dynamics, lifetime, water path, and areal extent that determine the reflectivity (albedo) of clouds. The concentration N d of droplets in clouds that influences planetary albedo is sensitive to the availability of aerosol particles on which the droplets form. Natural aerosol concentrations affect not only cloud properties themselves but also modulate the sensitivity of clouds to changes in anthropogenic aerosols. It is shown that modeled natural aerosols, principally marine biogenic primary and secondary aerosol sources, explain more than half of the spatiotemporal variability in satellite-observed N d. Enhanced N d is spatially correlated with regions of high chlorophyll a, and the spatiotemporal variability in N d is found to be driven primarily by high concentrations of sulfate aerosol at lower Southern Ocean latitudes (35(o) to 45(o)S) and by organic matter in sea spray aerosol at higher latitudes (45(o) to 55(o)S). Biogenic sources are estimated to increase the summertime mean reflected solar radiation in excess of 10 W m(-2) over parts of the Southern Ocean, which is comparable to the annual mean increases expected from anthropogenic aerosols over heavily polluted regions of the Northern Hemisphere.

  8. Natural Aerosols Explain Seasonal and Spatial Patterns of Southern Ocean Cloud Albedo

    SciTech Connect

    McCoy, Daniel; Burrows, Susannah M.; Wood, R.; Grosvenor, Daniel P.; Elliott, Scott; Ma, Po-Lun; Rasch, Philip J.; Hartmann, Dennis L.

    2015-07-17

    Small particles called aerosols act as nucleation sites for cloud drop formation, affecting clouds and cloud properties – ultimately influencing the cloud dynamics, lifetime, water path and areal extent that determine the reflectivity (albedo) of clouds. The concentration Nd of droplets in clouds that influences planetary albedo is sensitive to the availability of aerosol particles on which the droplets form. Natural aerosol concentrations not only affect cloud properties themselves, but also modulate the sensitivity of clouds to changes in anthropogenic aerosols. Here, it is shown that modeled natural aerosols, principally marine biogenic primary and secondary aerosol sources, explain more than half of the spatiotemporal variability in satellite-observed Nd. Enhanced Nd over regions of high biological activity is found to be driven primarily by high concentrations of sulfate aerosol at lower Southern Ocean latitudes (35-45°S) and by organic matter in sea spray aerosol at higher latitudes (45-55°S). Biogenic sources are estimated to increase the summertime mean reflected solar radiation in excess of 10 W m-2 over parts of the Southern Ocean, which is comparable to the annual mean increases expected from anthropogenic aerosols over heavily polluted regions of the Northern Hemisphere.

  9. 3D Image Reconstruction: Determination of Pattern Orientation

    SciTech Connect

    Blankenbecler, Richard

    2003-03-13

    The problem of determining the euler angles of a randomly oriented 3-D object from its 2-D Fraunhofer diffraction patterns is discussed. This problem arises in the reconstruction of a positive semi-definite 3-D object using oversampling techniques. In such a problem, the data consists of a measured set of magnitudes from 2-D tomographic images of the object at several unknown orientations. After the orientation angles are determined, the object itself can then be reconstructed by a variety of methods using oversampling, the magnitude data from the 2-D images, physical constraints on the image and then iteration to determine the phases.

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

    SciTech Connect

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

    1995-10-01

    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.

  11. Day/night whole sky imagers for 24-h cloud and sky assessment: history and overview.

    PubMed

    Shields, Janet E; Karr, Monette E; Johnson, Richard W; Burden, Art R

    2013-03-10

    A family of fully automated digital whole sky imagers (WSIs) has been developed at the Marine Physical Laboratory over many years, for a variety of research and military applications. The most advanced of these, the day/night whole sky imagers (D/N WSIs), acquire digital imagery of the full sky down to the horizon under all conditions from full sunlight to starlight. Cloud algorithms process the imagery to automatically detect the locations of cloud for both day and night. The instruments can provide absolute radiance distribution over the full radiance range from starlight through daylight. The WSIs were fielded in 1984, followed by the D/N WSIs in 1992. These many years of experience and development have resulted in very capable instruments and algorithms that remain unique. This article discusses the history of the development of the D/N WSIs, system design, algorithms, and data products. The paper cites many reports with more detailed technical documentation. Further details of calibration, day and night algorithms, and cloud free line-of-sight results will be discussed in future articles.

  12. Two Methods for Retrieving UV Index for All Cloud Conditions from Sky Imager Products or Total SW Radiation Measurements

    SciTech Connect

    Badosa, Jordi; Calbo, J.; McKenzie, R. L.; Liley, Ben; Gonzalez, J. A.; Forgan, B. W.; Long, Charles N.

    2014-07-01

    In the present study, we assess the cloud effects on UV Index (UVI) and total solar radiation (TR) as a function of cloud cover estimations and sunny conditions (from sky imaging products) as well as of solar zenith angle (SZA). These analyses are undertaken for a southern-hemisphere mid-latitude site where a 10-years dataset is available. It is confirmed that clouds reduce TR more than UV, in particular for obscured Sun conditions, low cloud fraction (< 60%) and large SZA (> 60º). Similarly, clouds enhance TR more than UV, mainly for visible Sun conditions, large cloud fraction and large SZA. Two methods to estimate UVI are developed: 1) from sky imaging cloud cover and sunny conditions, and 2) from TR measurements. Both methods may be used in practical operational applications, although Method 2 shows overall the best performance, since TR allows accounting for cloud optical properties. The mean absolute differences of Method 2 estimations with respect to measured values are 0.17 UVI units (for 1-minute data) and 0.79 Standard Erythemal Dose (SED) units (for daily integrations). Method 1 shows less accurate results but it is still suitable to estimate UVI: mean absolute differences are 0.37 UVI units and 1.6 SED.

  13. Photographic patterns in macular images: representation by a mathematical model.

    PubMed

    Smith, R Theodore; Nagasaki, Takayuki; Sparrow, Janet R; Barbazetto, Irene; Koniarek, Jan P; Bickmann, Lee J

    2004-01-01

    Normal macular photographic patterns are geometrically described and mathematically modeled. Forty normal color fundus photographs were digitized. The green channel gray-level data were filtered and contrast enhanced, then analyzed for concentricity, convexity, and radial resolution. The foveal data for five images were fit with elliptic quadratic polynomials in two zones: a central ellipse and a surrounding annulus. The ability of the model to reconstruct the entire foveal data from selected pixel values was tested. The gray-level patterns were nested sets of concentric ellipses. Gray levels increased radially, with retinal vessels changing the patterns to star shaped in the peripheral fovea. The elliptic polynomial model could fit a high-resolution green channel foveal image with mean absolute errors of 6.1% of the gray-level range. Foveal images were reconstructed from small numbers of selected pixel values with mean errors of 7.2%. Digital analysis of normal fundus photographs shows finely resolved concentric elliptical foveal and star-shaped parafoveal patterns, which are consistent with anatomical structures. A two-zone elliptic quadratic polynomial model can approximate foveal data, and can also reconstruct it from small subsets, allowing improved macular image analysis.

  14. Learning Multi-instance Deep Discriminative Patterns for Image Classification.

    PubMed

    Tang, Peng; Wang, Xinggang; Feng, Bin; Liu, Wenyu

    2016-12-21

    Finding an effective and efficient representation is very important for image classification. The most common approach is to extract a set of local descriptors, and then aggregate them into a high-dimensional, more semantic feature vector, like unsupervised Bag-of-Features (BoF) and weakly supervised partbased models. The later one is usually more discriminative than the former due to the use of information from image labels. In this work, we propose a weakly supervised strategy that using Multi-Instance Learning (MIL) to learn discriminative patterns for image representation. Specially, we extend traditional multiinstance methods to explicitly learn more than one patterns in positive class, and find the "most positive" instance for each pattern. Furthermore, as the positiveness of instance is treated as a continuous variable, we can use stochastic gradient decent (SGD) to maximize the margin between different patterns meanwhile considering MIL constraints. To make the learned patterns more discriminative, local descriptors extracted by Deep Convolutional Neural Networks (DCNN) are chosen instead of hand-crafted descriptors. Some experimental results are reported on several widely used benchmarks (Action 40, Caltech 101, Scene 15, MIT-indoor, SUN 397), showing that our method can achieve very remarkable performance.

  15. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    NASA Astrophysics Data System (ADS)

    Mader, Kevin; Stampanoni, Marco

    2016-01-01

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

  16. IMAGING OF THE CCS 22.3 GHz EMISSION IN THE TAURUS MOLECULAR CLOUD COMPLEX

    SciTech Connect

    Roy, Nirupam; Momjian, Emmanuel; Datta, Abhirup; Sarma, Anuj P.

    2011-09-20

    Thioxoethenylidene (CCS) is an abundant interstellar molecule and a good tracer of high density and evolutionary stage of dense molecular clouds. It is also a suitable candidate for Zeeman splitting observations for its high splitting factor and narrow thermal line widths. We report here Expanded Very Large Array 22.3 GHz observations of three dense molecular cores TMC-1, TMC-1C, and L1521B in the Taurus molecular cloud complex to image the CCS 2{sub 1}-1{sub 0} transition. For all three sources, the clumpy CCS emission is most likely tracing the starless cores. However, these compact structures account for only {approx}1%-13% of the integrated emission detected in single-dish observations, indicating the presence of significant large-scale diffuse emission in favorable conditions for producing CCS.

  17. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    SciTech Connect

    Mader, Kevin; Stampanoni, Marco

    2016-01-28

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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

  19. Thin cloud removal from remote sensing images using multidirectional dual tree complex wavelet transform and transfer least square support vector regression

    NASA Astrophysics Data System (ADS)

    Hu, Gensheng; Li, Xiaoyi; Liang, Dong

    2015-01-01

    The existence of clouds affects the interpretation and utilization of remote sensing images. A thin cloud removal algorithm for cloud-contaminated remote sensing images is proposed by combining a multidirectional dual tree complex wavelet transform (M-DTCWT) with domain adaptation transfer least square support vector regression (T-LSSVR). First, M-DTCWT is constructed by using the hourglass filter bank in combination with DTCWT, which is used to decompose remote sensing images into multiscale and multidirectional subbands. Then the low-frequency subband coefficients of the cloud-free regions on target images and source domain images are used as samples for a T-LSSVR model, which can be used to predict those of the cloud regions on cloud-contaminated images. Finally, by enhancing the high-frequency coefficients and replacing the low-frequency coefficients, the thin clouds on cloud-contaminated images are removed. Experimental results show that M-DTCWT contributes to keeping the details of the ground objects of cloud-contaminated images, and the T-LSSVR model can effectively learn the contour information from multisource and multitemporal images, therefore, the proposed method achieves a good effect of thin cloud removal.

  20. Preliminary Results from the MSX Satellite: Infrared Images of the Small Magellanic Cloud

    NASA Astrophysics Data System (ADS)

    Egan, M. P.; Shipman, R. F.; Price, S. D.

    1996-12-01

    We present infrared images of the Small Magellanic Cloud (SMC)taken by the infrared telescope on board the Midcourse Space Experiment (MSX). We compare MSX radiometer band A (6 - 11 microns ) images to the IRAS 12 microns image from the ISSA plates. The resolution of the MSX images is about 0.3 arcmin, compared to about 5 arcmin for the IRAS Sky Survey Atlas (ISSA) images. The primary feature in the 12 microns ISSA image of the SMC is a diffuse ring of emission. MSX resolves this ring into numerous individual point sources. The SMC is a region of high source density, and due to confusion problems was not included in the IRAS Faint Source Catalog. The IRAS Point Source Catalog (PSC) lists 120 objects in the region covered by the MSX observation. With the superior resolution of the MSX instrument we are able to extract over twice as many point sources in this field. We also compare the MSX image to a full resolution (about 0.25 by 1.5 arcmin) image constructed from raw IRAS scans.

  1. Complex Clouds

    Atmospheric Science Data Center

    2013-04-16

    ...     View Larger Image The complex structure and beauty of polar clouds are highlighted by these images acquired ... corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds. The right-hand panel ...

  2. Global pattern analysis and classification of dermoscopic images using textons

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

    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%.

  3. Reconstruction of 3D Shapes of Opaque Cumulus Clouds from Airborne Multiangle Imaging: A Proof-of-Concept

    NASA Astrophysics Data System (ADS)

    Davis, A. B.; Bal, G.; Chen, J.

    2015-12-01

    Operational remote sensing of microphysical and optical cloud properties is invariably predicated on the assumption of plane-parallel slab geometry for the targeted cloud. The sole benefit of this often-questionable assumption about the cloud is that it leads to one-dimensional (1D) radiative transfer (RT)---a textbook, computationally tractable model. We present new results as evidence that, thanks to converging advances in 3D RT, inverse problem theory, algorithm implementation, and computer hardware, we are at the dawn of a new era in cloud remote sensing where we can finally go beyond the plane-parallel paradigm. Granted, the plane-parallel/1D RT assumption is reasonable for spatially extended stratiform cloud layers, as well as the smoothly distributed background aerosol layers. However, these 1D RT-friendly scenarios exclude cases that are critically important for climate physics. 1D RT---whence operational cloud remote sensing---fails catastrophically for cumuliform clouds that have fully 3D outer shapes and internal structures driven by shallow or deep convection. For these situations, the first order of business in a robust characterization by remote sensing is to abandon the slab geometry framework and determine the 3D geometry of the cloud, as a first step toward bone fide 3D cloud tomography. With this specific goal in mind, we deliver a proof-of-concept for an entirely new kind of remote sensing applicable to 3D clouds. It is based on highly simplified 3D RT and exploits multi-angular suites of cloud images at high spatial resolution. Airborne sensors like AirMSPI readily acquire such data. The key element of the reconstruction algorithm is a sophisticated solution of the nonlinear inverse problem via linearization of the forward model and an iteration scheme supported, where necessary, by adaptive regularization. Currently, the demo uses a 2D setting to show how either vertical profiles or horizontal slices of the cloud can be accurately reconstructed

  4. Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

    NASA Astrophysics Data System (ADS)

    Mejia, Felipe A.; Kurtz, Ben; Murray, Keenan; Hinkelman, Laura M.; Sengupta, Manajit; Xie, Yu; Kleissl, Jan

    2016-08-01

    A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red-blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red-blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλτc, θ0, ϑs, ϑz, and RBRτc, θ0, ϑs, ϑz are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeasϑs, ϑz, in addition to RBRmeasϑs, ϑz, to obtain a unique solution for τc. The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003) method for overcast skies. τc values ranged from 0 to 80 with values over 80, being capped and registered as 80. A τc RMSE of 2.5 between the Min et al. (2003) method and the USI are observed. The MWR and USI have an RMSE of 2.2, which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms.

  5. Optical imaging of cloud-to-stratosphere/mesosphere lightning over the Amazon Basin (CS/LAB)

    NASA Technical Reports Server (NTRS)

    Sentman, Davis D.; Wescott, Eugene M.

    1995-01-01

    The purpose of the CS/LAB project was to obtain images of cloud to stratosphere lightning discharges from aboard NASA's DC-8 Airborne Laboratory while flying in the vicinity of thunderstorms over the Amazon Basin. We devised a low light level imaging package as an add-on experiment to an airborne Laboratory deployment to South America during May-June, 1993. We were not successful in obtaining the desired images during the South American deployment. However, in a follow up flight over the American Midwest during the night of July 8-9, 1993 we recorded nineteen examples of the events over intense thunderstorms. From the observations were estimated absolute brightness, terminal altitudes, flash duration, horizontal extents, emission volumes, and frequencies relative to negative and positive ground strokes.

  6. InSAR imaging of volcanic deformation over cloud-prone areas - Aleutian islands

    USGS Publications Warehouse

    Lu, Zhong

    2007-01-01

    Interferometric synthetic aperture radar (INSAR) is capable of measuring ground-surface deformation with centimeter-tosubcentimeter precision and spatial resolution of tens-of meters over a relatively large region. With its global coverage and all-weather imaging capability, INSAR is an important technique for measuring ground-surface deformation of volcanoes over cloud-prone and rainy regions such as the Aleutian Islands, where only less than 5 percent of optical imagery is usable due to inclement weather conditions. The spatial distribution of surface deformation data, derived from INSAR images, enables the construction of detailed mechanical models to enhance the study of magmatic processes. This paper reviews the basics of INSAR for volcanic deformation mapping and the INSAR studies of ten Aleutian volcanoes associated with both eruptive and noneruptive activity. These studies demonstrate that all-weather INSAR imaging can improve our understanding of how the Aleutian volcanoes work and enhance our capability to predict future eruptions and associated hazards.

  7. Comparison of eye imaging pattern recognition using neural network

    NASA Astrophysics Data System (ADS)

    Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.

    2015-05-01

    The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.

  8. Feature extraction from 3D lidar point clouds using image processing methods

    NASA Astrophysics Data System (ADS)

    Zhu, Ling; Shortridge, Ashton; Lusch, David; Shi, Ruoming

    2011-10-01

    Airborne LiDAR data have become cost-effective to produce at local and regional scales across the United States and internationally. These data are typically collected and processed into surface data products by contractors for state and local communities. Current algorithms for advanced processing of LiDAR point cloud data are normally implemented in specialized, expensive software that is not available for many users, and these users are therefore unable to experiment with the LiDAR point cloud data directly for extracting desired feature classes. The objective of this research is to identify and assess automated, readily implementable GIS procedures to extract features like buildings, vegetated areas, parking lots and roads from LiDAR data using standard image processing tools, as such tools are relatively mature with many effective classification methods. The final procedure adopted employs four distinct stages. First, interpolation is used to transfer the 3D points to a high-resolution raster. Raster grids of both height and intensity are generated. Second, multiple raster maps - a normalized surface model (nDSM), difference of returns, slope, and the LiDAR intensity map - are conflated to generate a multi-channel image. Third, a feature space of this image is created. Finally, supervised classification on the feature space is implemented. The approach is demonstrated in both a conceptual model and on a complex real-world case study, and its strengths and limitations are addressed.

  9. A geometric photography model for determining cloud top heights using MISR images

    NASA Astrophysics Data System (ADS)

    He, Yongjian; Qiu, Xinfa; Sun, Zhian; Li, Qiang

    2015-10-01

    Cloud top height (CTH) is an important factor in weather forecasting and monitoring. An accurate CTH has scientific significance for improving the quality of both weather analyses and numerical weather prediction. The three-dimensional geometric method has been widely recognized as a CTH calculation method that provides relatively high accuracy. In this paper, we used the theory of digital photogrammetry and remote sensing technology to establish a geometric photography model (GPM) that can simultaneously determine CTHs and cloud movement speed (CMS) by introducing the CMS into the collinearity equation of photogrammetry. The CTH is derived by constructing three-dimensional image pairs of multitemporal Multiangle Imaging Spectroradiometer (MISR) red spectral band images from three angles. Compared with CTHs observed by ground-based lidar at the United States Southern Great Plains, the difference of CTHs using the GPM relative to the reference value was less than 300 m. By analyzing the ground control points, the GPM error is estimated to be approximately 300 m. Compared with MISR CTH data, the CTHs calculated in this study were similar to that of MISR without wind.

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

    SciTech Connect

    Doerry, Armin W.

    2013-04-30

    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.

  11. High-resolution imaging and target designation through clouds or smoke

    DOEpatents

    Perry, Michael D.

    2003-01-01

    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.

  12. A Cost-Benefit Study of Doing Astrophysics On The Cloud: Production of Image Mosaics

    NASA Astrophysics Data System (ADS)

    Berriman, G. B.; Good, J. C. Deelman, E.; Singh, G. Livny, M.

    2009-09-01

    Utility grids such as the Amazon EC2 and Amazon S3 clouds offer computational and storage resources that can be used on-demand for a fee by compute- and data-intensive applications. The cost of running an application on such a cloud depends on the compute, storage and communication resources it will provision and consume. Different execution plans of the same application may result in significantly different costs. We studied via simulation the cost performance trade-offs of different execution and resource provisioning plans by creating, under the Amazon cloud fee structure, mosaics with the Montage image mosaic engine, a widely used data- and compute-intensive application. Specifically, we studied the cost of building mosaics of 2MASS data that have sizes of 1, 2 and 4 square degrees, and a 2MASS all-sky mosaic. These are examples of mosaics commonly generated by astronomers. We also study these trade-offs in the context of the storage and communication fees of Amazon S3 when used for long-term application data archiving. Our results show that by provisioning the right amount of storage and compute resources cost can be significantly reduced with no significant impact on application performance.

  13. Comparison Between Two Generic 3d Building Reconstruction Approaches - Point Cloud Based VS. Image Processing Based

    NASA Astrophysics Data System (ADS)

    Dahlke, D.; Linkiewicz, M.

    2016-06-01

    This paper compares two generic approaches for the reconstruction of buildings. Synthesized and real oblique and vertical aerial imagery is transformed on the one hand into a dense photogrammetric 3D point cloud and on the other hand into photogrammetric 2.5D surface models depicting a scene from different cardinal directions. One approach evaluates the 3D point cloud statistically in order to extract the hull of structures, while the other approach makes use of salient line segments in 2.5D surface models, so that the hull of 3D structures can be recovered. With orders of magnitudes more analyzed 3D points, the point cloud based approach is an order of magnitude more accurate for the synthetic dataset compared to the lower dimensioned, but therefor orders of magnitude faster, image processing based approach. For real world data the difference in accuracy between both approaches is not significant anymore. In both cases the reconstructed polyhedra supply information about their inherent semantic and can be used for subsequent and more differentiated semantic annotations through exploitation of texture information.

  14. Using Geotags to Derive Rich Tag-Clouds for Image Annotation

    NASA Astrophysics Data System (ADS)

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

    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.

  15. Spectral imaging of martian water ice clouds and their diurnal behavior during the 1999 aphelion season ( Ls = 130°)

    NASA Astrophysics Data System (ADS)

    Glenar, David A.; Samuelson, Robert E.; Pearl, John C.; Bjoraker, Gordon L.; Blaney, Diana

    2003-02-01

    We report high-spectral-resolution (λ/δλ = 800-2300) near-infrared mapping observations of Mars at Ls = 130° (April 1999), which were obtained by drift-scanning the cryogenic long-slit spectrometer at the KPNO 2.2-m telescope across the disk. Data were reformatted into calibrated spectral image cubes ( x,y,λ) spanning 2.19 to 4.12 μm, which distinguish atmospheric CO 2 features, solar lines, and surface and aerosol features. Maps of relative band depth between 3.0 and 3.5 μm trace water ice clouds and show the diurnal evolution of features in the persistent northern summer aphelion cloud belt, which was mapped contemporaneously but at fixed local time by the Mars Global Surveyor Thermal Emission Spectrometer (MGS/TES). Cloud optical depth, particle sizes, and ice aerosol content were estimated using a two-stream, single-layer scattering model, with Mie coefficients derived from recently published ice optical constants, followed by a linear spectral deconvolution process. A comparison of data and model spectra shows evaporating nighttime clouds in the morning followed by afternoon growth of a prominent orographic cloud feature on the west flank of Elysium Mons. Cloud optical depth at 3.2 μm evolved to 0.28 ± 0.13 and ice aerosol column abundance to 0.9 ± 0.3 pr μm in the afternoon. Column abundances as large as 0.17 pr μm were retrieved in nonorographic clouds within the aphelion cloud band around midday. These clouds exhibit a modest decline in optical depth during the afternoon. Results show that ice particle radii from <2 μm to >4 μm exist in both cloud types. However, large particles dominate the spectra, consistent with recent MGS/TES emission phase function measurements of aphelion cloud aerosol properties.

  16. Two methods for retrieving UV index for all cloud conditions from sky imager products or total SW radiation measurements.

    PubMed

    Badosa, Jordi; Calbó, Josep; Mckenzie, Richard; Liley, Ben; González, Josep-Abel; Forgan, Bruce; Long, Charles N

    2014-01-01

    Cloud effects on UV Index (UVI) and total solar radiation (TR) as a function of cloud cover and sunny conditions (from sky images) as well as of solar zenith angle (SZA) are assessed. These analyses are undertaken for a southern-hemisphere mid-latitude site where a 10-years dataset is available. It is confirmed that clouds reduce TR more than UV, in particular for obscured Sun conditions, low cloud fraction (<60%) and large SZA (>60°). Similarly, local short-time enhancement effects are stronger for TR than for UV, mainly for visible Sun conditions, large cloud fraction and large SZA. Two methods to estimate UVI are developed: (1) from sky imaging cloud cover and sunny conditions, and (2) from TR measurements. Both methods may be used in practical applications, although Method 2 shows overall the best performance, as TR allows considering cloud optical properties. The mean absolute (relative) differences of Method 2 estimations with respect to measured values are 0.17 UVI units (6.7%, for 1 min data) and 0.79 Standard Erythemal Dose (SED) units (3.9%, for daily integrations). Method 1 shows less accurate results but it is still suitable to estimate UVI: mean absolute differences are 0.37 UVI units (15%) and 1.6 SED (8.0%).

  17. Component pattern analysis of chemicals using multispectral THz imaging system

    NASA Astrophysics Data System (ADS)

    Kawase, Kodo; Ogawa, Yuichi; Watanabe, Yuki

    2004-04-01

    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.

  18. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.

    1998-01-01

    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

  19. 3D CARS image reconstruction and pattern recognition on SHG images

    NASA Astrophysics Data System (ADS)

    Medyukhina, Anna; Vogler, Nadine; Latka, Ines; Dietzek, Benjamin; Cicchi, Riccardo; Pavone, Francesco S.; Popp, Jürgen

    2012-06-01

    Nonlinear optical imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or second-harmonic generation (SHG) show great potential for in-vivo investigations of tissue. While the microspectroscopic imaging tools are established, automized data evaluation, i.e. image pattern recognition and automized image classification, of nonlinear optical images still bares great possibilities for future developments towards an objective clinical diagnosis. This contribution details the capability of nonlinear microscopy for both 3D visualization of human tissues and automated discrimination between healthy and diseased patterns using ex-vivo human skin samples. By means of CARS image alignment we show how to obtain a quasi-3D model of a skin biopsy, which allows us to trace the tissue structure in different projections. Furthermore, the potential of automated pattern and organization recognition to distinguish between healthy and keloidal skin tissue is discussed. A first classification algorithm employs the intrinsic geometrical features of collagen, which can be efficiently visualized by SHG microscopy. The shape of the collagen pattern allows conclusions about the physiological state of the skin, as the typical wavy collagen structure of healthy skin is disturbed e.g. in keloid formation. Based on the different collagen patterns a quantitative score characterizing the collagen waviness - and hence reflecting the physiological state of the tissue - is obtained. Further, two additional scoring methods for collagen organization, respectively based on a statistical analysis of the mutual organization of fibers and on FFT, are presented.

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

    SciTech Connect

    McFarquhar, GM; Um, J

    2012-02-17

    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.

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

    PubMed

    Seenivasagam, V; Velumani, R

    2013-01-01

    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.

  2. Classification of large-scale fundus image data sets: a cloud-computing framework.

    PubMed

    Roychowdhury, Sohini; Roychowdhury, Sohini; Roychowdhury, Sohini

    2016-08-01

    Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized method that finds optimal image-based feature sets that reduce computational time complexity while maximizing overall classification accuracy for detection of diabetic retinopathy (DR). First, region-based and pixel-based features are extracted from fundus images for classification of DR lesions and vessel-like structures. Next, feature ranking strategies are used to distinguish the optimal classification feature sets. DR lesion and vessel classification accuracies are computed using the boosted decision tree and decision forest classifiers in the Microsoft Azure Machine Learning Studio platform, respectively. For images from the DIARETDB1 data set, 40 of its highest-ranked features are used to classify four DR lesion types with an average classification accuracy of 90.1% in 792 seconds. Also, for classification of red lesion regions and hemorrhages from microaneurysms, accuracies of 85% and 72% are observed, respectively. For images from STARE data set, 40 high-ranked features can classify minor blood vessels with an accuracy of 83.5% in 326 seconds. Such cloud-based fundus image analysis systems can significantly enhance the borderline classification performances in automated screening systems.

  3. On the automatic classification of rain patterns on radar images

    NASA Astrophysics Data System (ADS)

    Pawlina Bonati, Apolonia

    The automation of the process of identification and classification of rain patterns on radar derived images is approached using some tools of digital image interpretation adapted to the specific application. The formal characterization of rain patterns and their partition in classes related to the type of precipitation is the main problem addressed in the paper, as the standard well established criteria for such classification are not defined. The digital maps of rain at horizontal plane derived from three-dimensional radar scans are processed by the interpretation package which identifies and classifies rain structures present on the map. The results generated by this package are illustrated in the paper and offered for discussion. The interpretation procedure is tailored for the radio-meteorology applications but the method is adaptable to other field requirements.

  4. Imaging patterns of brain development and their relationship to cognition.

    PubMed

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

    2015-06-01

    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.

  5. Integration of Point Clouds Originated from Laser Scaner and Photogrammetric Images for Visualization of Complex Details of Historical Buildings

    NASA Astrophysics Data System (ADS)

    Altuntas, C.

    2015-02-01

    Three-dimensional (3D) models of historical buildings are created for documentation and virtual realization of them. Laser scanning and photogrammetry are extensively used to perform for these aims. The selection of the method that will be used in threedimensional modelling study depends on the scale and shape of the object, and also applicability of the method. Laser scanners are high cost instruments. However, the cameras are low cost instruments. The off-the-shelf cameras are used for taking the photogrammetric images. The camera is imaging the object details by carrying on hand while the laser scanner makes ground based measurement. Laser scanner collect high density spatial data in a short time from the measurement area. On the other hand, image based 3D (IB3D) measurement uses images to create 3D point cloud data. The image matching and the creation of the point cloud can be done automatically. Historical buildings include more complex details. Thus, all details cannot be measured by terrestrial laser scanner (TLS) due to the blocking the details with each others. Especially, the artefacts which have complex shapes cannot be measured in full details. They cause occlusion on the point cloud model. However it is possible to record photogrammetric images and creation IB3D point cloud for these areas. Thus the occlusion free 3D model is created by the integration of point clouds originated from the TLS and photogrammetric images. In this study, usability of laser scanning in conjunction with image based modelling for creation occlusion free three-dimensional point cloud model of historical building was evaluated. The IB3D point cloud was created in the areas that could not been measured by TLS. Then laser scanning and IB3D point clouds were integrated in the common coordinate system. The registration point clouds were performed with the iterative closest point (ICP) and georeferencing methods. Accuracy of the registration was evaluated by convergency and its

  6. Pattern recognition and image processing for environmental monitoring

    NASA Astrophysics Data System (ADS)

    Siddiqui, Khalid J.; Eastwood, DeLyle

    1999-12-01

    Pattern recognition (PR) and signal/image processing methods are among the most powerful tools currently available for noninvasively examining spectroscopic and other chemical data for environmental monitoring. Using spectral data, these systems have found a variety of applications employing analytical techniques for chemometrics such as gas chromatography, fluorescence spectroscopy, etc. An advantage of PR approaches is that they make no a prior assumption regarding the structure of the patterns. However, a majority of these systems rely on human judgment for parameter selection and classification. A PR problem is considered as a composite of four subproblems: pattern acquisition, feature extraction, feature selection, and pattern classification. One of the basic issues in PR approaches is to determine and measure the features useful for successful classification. Selection of features that contain the most discriminatory information is important because the cost of pattern classification is directly related to the number of features used in the decision rules. The state of the spectral techniques as applied to environmental monitoring is reviewed. A spectral pattern classification system combining the above components and automatic decision-theoretic approaches for classification is developed. It is shown how such a system can be used for analysis of large data sets, warehousing, and interpretation. In a preliminary test, the classifier was used to classify synchronous UV-vis fluorescence spectra of relatively similar petroleum oils with reasonable success.

  7. Cloud retrieval algorithm for the imaging spectro-polarimeter on board EUMETSAT Polar System - Second Generation (EPS-SG)

    NASA Astrophysics Data System (ADS)

    Kokhanovsky, Alexander; Munro, Rose

    2015-04-01

    The atmospheric remote sensing benefits a lot from the use of spectro - polarimetric imagers on board satellite platforms. Due to the movement of the spacecraft, any given scene can be observed from many directions by an imaging polarimeter. This concept has been proven with the measurements of POLDER - 1, 2, and 3 on board ADEOS and PARASOL platforms. POLDER has performed measurements of the Stokes vector (first three components) of reflected light in 16 directions at several wavelengths in the visible and near - infrared. The 3MI (Multi-viewing, Multi-channel, Multi-polarization Imaging) on board of a future (2021) EPS-SG mission is very similar to POLDER. However, the measurements are performed at more spectral channels as compared to POLDER and also at a better spatial resolution (4*4km). In particular, the measurements of the Stokes vector components (I, Q, U) of the reflected solar light are performed at the wavelengths 410, 443, 490, 555, 670, 865, 1650, and 2130nm. In addition, the intensity of reflected light is measured at 763, 765, 910, and 1370nm. The FWHM of the channel at 763nm is 10nm and it is 20 nm at other channels (except at 765nm, 865nm, 1650nm, and 2130nm, where FWHM is equal to 40nm). The imaging spectro-polarimeter enables enhanced retrievals of aerosol and cloud properties using spaceborne observations. In particular, the following parameters of clouds can be retrieved: cloud top altitude, liquid water path, the average size of particles in the clouds, and the cloud thermodynamic state. The cloud albedo, cloud optical thickness, single scattering albedo and other optical parameters of clouds can be derived as well. In this presentation we describe the cloud retrieval algorithm CROP developed at EUMETSAT for the retrievals of cloud microphysical, geometrical, and optical characteristics using 3MI observations. The retrievals are performed only for completely cloudy pixels. The measurements at channels 763 and 765nm are used to get cloud top

  8. Discovering significant evolution patterns from satellite image time series.

    PubMed

    Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

    2011-12-01

    Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

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

    PubMed Central

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

    2013-01-01

    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

  10. A classification algorithm based on Cloude decomposition model for fully polarimetric SAR image

    NASA Astrophysics Data System (ADS)

    Xiang, Hongmao; Liu, Shanwei; Zhuang, Ziqi; Zhang, Naixin

    2016-11-01

    Remote sensing is an important technology for monitoring coastal zone, but it is difficult to get effective optical data in cloudy or rainy weather. SAR is an important data source for monitoring the coastal zone because it cannot be restricted in all-weather. Fully polarimetric SAR data is more abundant than single polarization and multi-polarization SAR data. The experiment selected the fully polarimetric SAR image of Radarsat-2, which covered the Yellow River Estuary. In view of the features of the study area, we carried out the H/ α unsupervised classification, the H/ α -Wishart unsupervised classification and the H/ α -Wishart unsupervised classification based on the results of Cloude decomposition. A new classification method is proposed which used the Wishart supervised classification based on the result of H/ α -Wishart unsupervised classification. The experimental results showed that the new method effectively overcome the shortcoming of unsupervised classification and improved the classification accuracy significantly. It was also shown that the classification result of SAR image had the similar precision with that of Landsat-7 image by the same classification method, SAR image had a better precision of water classification due to its sensitivity for water, and Landsat-7 image had a better precision of vegetation types.

  11. Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr. (Principal Investigator)

    1984-01-01

    Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

  12. Smart cloud system with image processing server in diagnosing brain diseases dedicated for hospitals with limited resources.

    PubMed

    Fahmi, Fahmi; Nasution, Tigor H

    2017-01-19

    The use of medical imaging in diagnosing brain disease is growing. The challenges are related to the big size of data and complexity of the image processing. High standard of hardware and software are demanded, which can only be provided in big hospitals. Our purpose was to provide a smart cloud system to help diagnosing brain diseases for hospital with limited infrastructure. The expertise of neurologists was first implanted in cloud server to conduct an automatic diagnosis in real time using image processing technique developed based on ITK library and web service. Users upload images through website and the result, in this case the size of tumor was sent back immediately. A specific image compression technique was developed for this purpose. The smart cloud system was able to measure the area and location of tumors, with average size of 19.91 ± 2.38 cm2 and an average response time 7.0 ± 0.3 s. The capability of the server decreased when multiple clients accessed the system simultaneously: 14 ± 0 s (5 parallel clients) and 27 ± 0.2 s (10 parallel clients). The cloud system was successfully developed to process and analyze medical images for diagnosing brain diseases in this case for tumor.

  13. 3D registration method based on scattered point cloud from B-model ultrasound image

    NASA Astrophysics Data System (ADS)

    Hu, Lei; Xu, Xiaojun; Wang, Lifeng; Guo, Na; Xie, Feng

    2017-01-01

    The paper proposes a registration method on 3D point cloud of the bone tissue surface extracted by B-mode ultrasound image and the CT model . The B-mode ultrasound is used to get two-dimensional images of the femur tissue . The binocular stereo vision tracker is used to obtain spatial position and orientation of the optical positioning device fixed on the ultrasound probe. The combining of the two kind of data generates 3D point cloud of the bone tissue surface. The pixel coordinates of the bone surface are automatically obtained from ultrasound image using an improved local phase symmetry (phase symmetry, PS) . The mapping of the pixel coordinates on the ultrasound image and 3D space is obtained through a series of calibration methods. In order to detect the effect of registration, six markers are implanted on a complete fresh pig femoral .The actual coordinates of the marks are measured with two methods. The first method is to get the coordinates with measuring tools under a coordinate system. The second is to measure the coordinates of the markers in the CT model registered with 3D point cloud using the ICP registration algorithm under the same coordinate system. Ten registration experiments are carried out in the same way. Error results are obtained by comparing the two sets of mark point coordinates obtained by two different methods. The results is that a minimum error is 1.34mm, the maximum error is 3.22mm,and the average error of 2.52mm; ICP registration algorithm calculates the average error of 0.89mm and a standard deviation of 0.62mm.This evaluation standards of registration accuracy is different from the average error obtained by the ICP registration algorithm. It can be intuitive to show the error caused by the operation of clinical doctors. Reference to the accuracy requirements of different operation in the Department of orthopedics, the method can be apply to the bone reduction and the anterior cruciate ligament surgery.

  14. Robust image region descriptor using local derivative ordinal binary pattern

    NASA Astrophysics Data System (ADS)

    Shang, Jun; Chen, Chuanbo; Pei, Xiaobing; Liang, Hu; Tang, He; Sarem, Mudar

    2015-05-01

    Binary image descriptors have received a lot of attention in recent years, since they provide numerous advantages, such as low memory footprint and efficient matching strategy. However, they utilize intermediate representations and are generally less discriminative than floating-point descriptors. We propose an image region descriptor, namely local derivative ordinal binary pattern, for object recognition and image categorization. In order to preserve more local contrast and edge information, we quantize the intensity differences between the central pixels and their neighbors of the detected local affine covariant regions in an adaptive way. These differences are then sorted and mapped into binary codes and histogrammed with a weight of the sum of the absolute value of the differences. Furthermore, the gray level of the central pixel is quantized to further improve the discriminative ability. Finally, we combine them to form a joint histogram to represent the features of the image. We observe that our descriptor preserves more local brightness and edge information than traditional binary descriptors. Also, our descriptor is robust to rotation, illumination variations, and other geometric transformations. We conduct extensive experiments on the standard ETHZ and Kentucky datasets for object recognition and PASCAL for image classification. The experimental results show that our descriptor outperforms existing state-of-the-art methods.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    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

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

    PubMed

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

    2014-01-01

    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.

  17. Arctic Clouds

    Atmospheric Science Data Center

    2013-04-19

    ...   View Larger Image Stratus clouds are common in the Arctic during the summer months, and are important modulators of ... from MISR's two most obliquely forward-viewing cameras. The cold, stable air causes the clouds to persist in stratified layers, and this ...

  18. Aphelion water-ice cloud mapping and property retrieval using the OMEGA imaging spectrometer onboard Mars Express

    NASA Astrophysics Data System (ADS)

    Madeleine, J.-B.; Forget, F.; Spiga, A.; Wolff, M. J.; Montmessin, F.; Vincendon, M.; Jouglet, D.; Gondet, B.; Bibring, J.-P.; Langevin, Y.; Schmitt, B.

    2012-05-01

    Mapping of the aphelion clouds over the Tharsis plateau and retrieval of their particle size and visible opacity are made possible by the OMEGA imaging spectrometer aboard Mars Express. Observations cover the period from MY26 Ls = 330° to MY29 Ls = 180° and are acquired at various local times, ranging from 8 AM to 6 PM. Cloud maps of the Tharsis region constructed using the 3.1 μm ice absorption band reveal the seasonal and diurnal evolution of aphelion clouds. Four distinct types of clouds are identified: morning hazes, topographically controlled hazes, cumulus clouds and thick hazes. The location and time of occurrence of these clouds are analyzed and their respective formation process is discussed. An inverse method for retrieving cloud particle size and opacity is then developed and can only be applied to thick hazes. The relative error of these measurements is less than 30% for cloud particle size and 20% for opacity. Two groups of particles can be distinguished. The first group is found over flat plains and is composed of relatively small particles, ranging in size from 2 to 3.5 μm. The second group is characterized by particle sizes of ˜5 μm which appear to be quite constant over Ls and local time. It is found west of Ascraeus and Pavonis Mons, and near Lunae Planum. These regions are preferentially exposed to anabatic winds, which may control the formation of these particles and explain their distinct properties. The water ice column is equal to 2.9 pr.μm on average, and can reach 5.2 pr.μm in the thickest clouds of Tharsis.

  19. Regularization methods for processing fringe-pattern images.

    PubMed

    Marroquin, J L; Rivera, M; Botello, S; Rodriguez-Vera, R; Servin, M

    1999-02-10

    A powerful technique for processing fringe-pattern images is based on Bayesian estimation theory with prior Markov random-field models. In this approach the solution of a processing problem is characterized as the minimizer of a cost function with terms that specify that the solution should be compatible with the available observations and terms that impose certain (prior) constraints on the solution. We show that, by the appropriate choice of these terms, one can use this approach in almost every processing step for accurate and robust interferogram demodulation and phase unwrapping.

  20. Discovery and imaging of a Galactic cirrus cloud with the far ultraviolet space telescope

    NASA Technical Reports Server (NTRS)

    Haikala, Lauri K.; Mattila, Kalevi; Bowyer, Stuart; Sasseen, Timothy P.; Lampton, Michael; Knude, Jens

    1995-01-01

    We present new far-ultraviolet (1400-1800 A) data concerning a Galactic cirrus cloud G251.2+73.3 near the north Galactic pole obtained with the space-borne imaging telescope FAUST (Far Ultraviolet Space Telescope). We obtain a good correlation between the far-ultraviolet (FUV) and IRAS 100 micrometers surface brightnesses, their relation being I(sub FUV) = (128 +/- 3) I(sub 100 micrometers) - (264 +/- 9), where the I(sub FUV) flux is given in units of photon/s/sq cm/A/sr and I(sub 100 micrometers) in MJy/sr. Using uvbyH-beta photometry, we get a distance of 120 pc and a visual extinction in the center of the cloud of 0.39 mag corresponding to an extinction of 1.0 mag at 1565 A. We have performed a multiple scattering calculation for the scattered light using the Monte Carlo method. These calculations provide restrictions on the FUV scattering properties of the interstellar dust.

  1. Extending the Life of Virtual Heritage: Reuse of Tls Point Clouds in Synthetic Stereoscopic Spherical Images

    NASA Astrophysics Data System (ADS)

    Garcia Fernandez, J.; Tammi, K.; Joutsiniemi, A.

    2017-02-01

    Recent advances in Terrestrial Laser Scanner (TLS), in terms of cost and flexibility, have consolidated this technology as an essential tool for the documentation and digitalization of Cultural Heritage. However, once the TLS data is used, it basically remains stored and left to waste.How can highly accurate and dense point clouds (of the built heritage) be processed for its reuse, especially to engage a broader audience? This paper aims to answer this question by a channel that minimizes the need for expert knowledge, while enhancing the interactivity with the as-built digital data: Virtual Heritage Dissemination through the production of VR content. Driven by the ProDigiOUs project's guidelines on data dissemination (EU funded), this paper advances in a production path to transform the point cloud into virtual stereoscopic spherical images, taking into account the different visual features that produce depth perception, and especially those prompting visual fatigue while experiencing the VR content. Finally, we present the results of the Hiedanranta's scans transformed into stereoscopic spherical animations.

  2. Buildup of electron cloud with different bunch pattern in thepresence of solenoid field

    SciTech Connect

    Cai, Y.; Pivi , M.; Furman , M.A.

    2003-05-01

    We have augmented the code POSINST to include solenoidfields, and used it to simulate the build up of electron cloud due toelectron multipacting in the PEP-II positron ring. We find that thedistribution of electrons is strongly affected by the resonancesassociated with the cyclotron period and bunch spacing. In addition, wediscover a threshold beyond which the electron density growsexponentially until it reaches the space charge limit. The threshold doesnot depend on the bunch spacing but does depend on the positron bunchpopulation.

  3. Segmentation of interstitial lung disease patterns in HRCT images

    NASA Astrophysics Data System (ADS)

    Dash, Jatindra K.; Madhavi, Vaddepalli; Mukhopadhyay, Sudipta; Khandelwal, Niranjan; Kumar, Prafulla

    2015-03-01

    Automated segmentation of pathological bearing region is the first step towards the development of lung CAD. Most of the work reported in the literature related to automated analysis of lung tissue aims towards classification of fixed sized block into one of the classes. This block level classification of lung tissues in the image never results in accurate or smooth boundaries between different regions. In this work, effort is taken to investigate the performance of three automated image segmentation algorithms those results in smooth boundaries among lung tissue patterns commonly encountered in HRCT images of the thorax. A public database that consists of HRCT images taken from patients affected with Interstitial Lung Diseases (ILDs) is used for the evaluation. The algorithms considered are Markov Random Field (MRF), Gaussian Mixture Model (GMM) and Mean Shift (MS). 2-fold cross validation approach is followed for the selection of the best parameter value for individual algorithm as well as to evaluate the performance of all the algorithms. Mean shift algorithm is observed as the best performer in terms of Jaccard Index, Modified Hausdorff Distance, accuracy, Dice Similarity Coefficient and execution speed.

  4. An experimental comparison of standard stereo matching algorithms applied to cloud top height estimation from satellite IR images

    NASA Astrophysics Data System (ADS)

    Anzalone, Anna; Isgrò, Francesco

    2016-10-01

    The JEM-EUSO (Japanese Experiment Module-Extreme Universe Space Observatory) telescope will measure Ultra High Energy Cosmic Ray properties by detecting the UV fluorescent light generated in the interaction between cosmic rays and the atmosphere. Cloud information is crucial for a proper interpretation of these data. The problem of recovering the cloud-top height from satellite images in infrared has struck some attention over the last few decades, as a valuable tool for the atmospheric monitoring. A number of radiative methods do exist, like C02 slicing and Split Window algorithms, using one or more infrared bands. A different way to tackle the problem is, when possible, to exploit the availability of multiple views, and recover the cloud top height through stereo imaging and triangulation. A crucial step in the 3D reconstruction is the process that attempts to match a characteristic point or features selected in one image, with one of those detected in the second image. In this article the performance of a group matching algorithms that include both area-based and global techniques, has been tested. They are applied to stereo pairs of satellite IR images with the final aim of evaluating the cloud top height. Cloudy images from SEVIRI on the geostationary Meteosat Second Generation 9 and 10 (MSG-2, MSG-3) have been selected. After having applied to the cloudy scenes the algorithms for stereo matching, the outcoming maps of disparity are transformed in depth maps according to the geometry of the reference data system. As ground truth we have used the height maps provided by the database of MODIS (Moderate Resolution Imaging Spectroradiometer) on-board Terra/Aqua polar satellites, that contains images quasi-synchronous to the imaging provided by MSG.

  5. Online self-service processing system of ZY-3 satellite: a prospective study of image cloud services

    NASA Astrophysics Data System (ADS)

    Wang, Hongyan; Wang, Huabin; Shi, Shaoyu

    2015-12-01

    The strong demands for satellite images are increasing not only in professional fields, but also in the non-professionals. But the online map services with up-to-date satellite images can serve few demands. One challenge is how to provide online processing service, which need to handle real-time online data-intensive geospatial computation and visualization. Under the background of the development of cloud computing technology, the problem can be figured out partly. The other challenge is how to implement user-customized online processing without professional background and knowledge. An online self-service processing system of ZY-3 Satellite images is designed to implement an on-demand service mode in this paper. It will work with only some simple parameters being set up for the non-professionals without having to care about the specific processing steps. And the professionals can assemble the basic processing services to a service chain, which can work out a more complex processing and a better result. This intelligent self-service online system for satellite images processing, which is called the prototype of satellite image cloud service in this paper, is accelerated under the development of cloud computing technology and researches on data-intensive computing. To realize the goal, the service mode and framework of the online self-service processing system of ZY-3 Satellite images are figured out in this paper. The details of key technologies are also discussed, including user space virtualization management, algorithm-level parallel image processing, image service chain construction, etc. And the experimental system is built up as a prospective study of image cloud services.

  6. Satellite Image Edge Detection for Population Distribution Pattern Identification using Levelset with Morphological Filtering Process

    NASA Astrophysics Data System (ADS)

    Harsiti; Munandar, T. A.; Suhendar, A.; Abdullah, A. G.; Rohendi, D.

    2017-03-01

    Population distribution pattern is directly related with economic gap of a region. Analysis of population distribution pattern is usually performed by studying statistical data on population. This study aimed to analyze population distribution pattern using image analysis concept, i.e. using satellite images. Levelset and morphological image filtering methods were used to analyze images to see distribution pattern. The research result showed that Levelset and morphological image filtering could remove a lot of noises in analysis result images and form object edge contours very clearly. The detected object contours were used as references to recognize population distribution pattern based on satellite image analysis. The pattern made based on the research result didn’t show optimal result because Levelset performed image segmentation based on the contours of the analyzed objects. Other segmentation methods should be combined with it to produce clearer population distribution pattern.

  7. Diffractive-imaging-based optical image encryption with simplified decryption from single diffraction pattern.

    PubMed

    Qin, Yi; Wang, Zhipeng; Gong, Qiong

    2014-07-01

    In this paper, we propose a novel method for image encryption by employing the diffraction imaging technique. This method is in principle suitable for most diffractive-imaging-based optical encryption schemes, and a typical diffractive imaging architecture using three random phase masks in the Fresnel domain is taken for an example to illustrate it. The encryption process is rather simple because only a single diffraction intensity pattern is needed to be recorded, and the decryption procedure is also correspondingly simplified. To achieve this goal, redundant data are digitally appended to the primary image before a standard encrypting procedure. The redundant data serve as a partial input plane support constraint in a phase retrieval algorithm, which is employed for completely retrieving the plaintext. Simulation results are presented to verify the validity of the proposed approach.

  8. Evaluating the Potential of Imaging Rover for Automatic Point Cloud Generation

    NASA Astrophysics Data System (ADS)

    Cera, V.; Campi, M.

    2017-02-01

    The paper presents a phase of an on-going interdisciplinary research concerning the medieval site of Casertavecchia (Italy). The project aims to develop a multi-technique approach for the semantic - enriched 3D modeling starting from the automatic acquisition of several data. In particular, the paper reports the results of the first stage about the Cathedral square of the medieval village. The work is focused on evaluating the potential of an imaging rover for automatic point cloud generation. Each of survey techniques has its own advantages and disadvantages so the ideal approach is an integrated methodology in order to maximize single instrument performance. The experimentation was conducted on the Cathedral square of the ancient site of Casertavecchia, in Campania, Italy.

  9. Determining ice water content from 2D crystal images in convective cloud systems

    NASA Astrophysics Data System (ADS)

    Leroy, Delphine; Coutris, Pierre; Fontaine, Emmanuel; Schwarzenboeck, Alfons; Strapp, J. Walter

    2016-04-01

    Cloud microphysical in-situ instrumentation measures bulk parameters like total water content (TWC) and/or derives particle size distributions (PSD) (utilizing optical spectrometers and optical array probes (OAP)). The goal of this work is to introduce a comprehensive methodology to compute TWC from OAP measurements, based on the dataset collected during recent HAIC (High Altitude Ice Crystals)/HIWC (High Ice Water Content) field campaigns. Indeed, the HAIC/HIWC field campaigns in Darwin (2014) and Cayenne (2015) provide a unique opportunity to explore the complex relationship between cloud particle mass and size in ice crystal environments. Numerous mesoscale convective systems (MCSs) were sampled with the French Falcon 20 research aircraft at different temperature levels from -10°C up to 50°C. The aircraft instrumentation included an IKP-2 (isokinetic probe) to get reliable measurements of TWC and the optical array probes 2D-S and PIP recording images over the entire ice crystal size range. Based on the known principle relating crystal mass and size with a power law (m=α•Dβ), Fontaine et al. (2014) performed extended 3D crystal simulations and thereby demonstrated that it is possible to estimate the value of the exponent β from OAP data, by analyzing the surface-size relationship for the 2D images as a function of time. Leroy et al. (2015) proposed an extended version of this method that produces estimates of β from the analysis of both the surface-size and perimeter-size relationships. Knowing the value of β, α then is deduced from the simultaneous IKP-2 TWC measurements for the entire HAIC/HIWC dataset. The statistical analysis of α and β values for the HAIC/HIWC dataset firstly shows that α is closely linked to β and that this link changes with temperature. From these trends, a generalized parameterization for α is proposed. Finally, the comparison with the initial IKP-2 measurements demonstrates that the method is able to predict TWC values

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

    NASA Technical Reports Server (NTRS)

    Vanzyl, Jakob J.

    1993-01-01

    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.

  11. Limb clouds and dust on Mars from VMC-Mars Express images

    NASA Astrophysics Data System (ADS)

    Sanchez-Lavega, Agustin; Chen, Hao Chen; Ordoñez-Etxeberria, Iñaki; Hueso, Ricardo; Cardesin, Alejandro; Titov, Dima; Wood, Simon

    2016-10-01

    We have used the large image database generated by the Visual Monitoring Camera (VMC) onboard Mars Express to first search and then study, the properties of projected features (dust and water clouds) on the planet limb. VMC is a small camera serving since 2007 for public education and outreach (Ormston et al., 2011). The camera consists of a CMOS sensor with a Bayer filter mosaic providing color images in the wavelength range 400-900 nm. Since the observations were performed in an opportunistic mode (nor planned on a science base) the captured events occurred in a random mode. In total 17 limb features were observed in the period spanning from April 2007 to August 2015. Their extent at limb varies from about 100 km for the smaller ones to 2,000 km for the major ones. They showed a rich morphology consisting in series of patchy elements with a uniform top layer located at altitudes ranging from 30 to 85 km. The features are mostly concentrated between latitudes 45 deg North and South covering most longitudes although a greater concentration occurs around -90 to +90 deg. from the reference meridian (i.e. longitude 0 degrees, East or West). Most events in the southern hemisphere occurred for orbital longitudes 0-90 degrees (autumnal season) and in the north for orbital longitudes 330-360 (winter season). We present a detailed study of two of these events, one corresponding to a dust storm observed also with the MARCI instrument onboard Mars Reconnaissance Orbiter, and a second one corresponding to a water cloud.

  12. Polarization of Directly Imaged Young Giant Planets as a Probe of Mass, Rotation, and Clouds

    NASA Technical Reports Server (NTRS)

    Marley, Mark Scott; Sengupta, Sujan

    2012-01-01

    Young, hot gas giant planets at large separations from their primaries have been directly imaged around several nearby stars. More such planets will likely be detected by ongoing and new imaging surveys with instruments such as the Gemini Planet Imager (GPI). Efforts continue to model the spectra of these planets in order to constrain their masses, effective temperatures, composition, and cloud structure. One potential tool for analyzing these objects, which has received relatively less attention, is polarization. Linear polarization of gas giant exoplanets can arise from the combined influences of light scattering by atmospheric dust and a rotationally distorted shape. The oblateness of gas giant planet increases of course with rotation rate and for fixed rotation also rises with decreasing gravity. Thus young, lower mass gas giant planets with youthful inflated radii could easily have oblateness greater than that of Saturn s 10%. We find that polarizations of over 1% may easily be produced in the near-infrared in such cases. This magnitude of polarization may be measurable by GPI and other instruments. Thus if detected, polarization of a young Jupiter places constraints on the combination of its gravity, rotation rate, and degree of cloudiness. We will present results of our multiple scattering analysis coupled with a self-consistent dusty atmospheric models to demonstrate the range of polarizations that might be expected from resolved exoplanets and the range of parameter space that such observations may inform.

  13. 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)

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

    2014-11-01

    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 μm) 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.

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

    PubMed

    Rosnell, Tomi; Honkavaara, Eija

    2012-01-01

    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.

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

    PubMed Central

    Rosnell, Tomi; Honkavaara, Eija

    2012-01-01

    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

  16. Characterization of image transfer patterns in a regional trauma network.

    PubMed

    Neuhaus, Philipp; Weber, Thomas; Dugas, Martin; Juhra, Christian; Breil, Bernhard

    2014-11-01

    Trauma Networks are currently founded in Germany to improve patient care of severely injured persons. To assure appropriate patient treatment in a short time, the transfer of radiological image data between the connected hospitals over the internet is an important method. This paper characterizes radiological image transfer patterns in a regional trauma network and analyzes various compression options. Within the "TraumaNetwork NorthWest" in Germany, the web-based platform "MedSix" was developed. MedSix is able to transfer DICOM-data quickly and easily between connected hospitals and can be directly connected to the local PACS. Audit data of the routine system between the 01.01.2012 and the 31.12.2012 were analyzed to identify typical characteristics of radiological image exchanges. Five different compression methods were compared by a simulation. MedSix has been used by 12 hospitals. 87 % of the transfers were uploaded within 15 min. Lossless compression is able to save about 50 % bandwidth. 82 % of the transfers have a data volume of less than 200 MB. Temporary accounts for non-regular users were used regularly. Most transfers were done from small to maximum care hospitals. It is feasible to substitute physical image exchange in a trauma network with electronic exchange of radiological images between the connected hospitals. Even large datasets are transferred within an acceptable time frame. Most transfers occur from small to large hospitals. The possibility of temporary accounts seems to be a key feature for the user acceptance.

  17. Build up of electron cloud with different bunch pattern in the presence of solenoidal field

    SciTech Connect

    Cai, Y.; Furman, M.A.; Pivi, M.

    2004-04-01

    We have augmented the code POSINST to include solenoid fields, and used it to simulate the build up of electron cloud due to electron multipacting in the PEP-II positron ring. We find that the distribution of electrons is strongly affected by the resonances associated with the cyclotron period and bunch spacing. In addition, we discover a threshold beyond which the electron density grows exponentially until it reaches the space charge limit. The threshold does not depend on the bunch spacing but does depend on the positron bunch population.

  18. Imaging Dot Patterns for Measuring Gossamer Space Structures

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

    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.

  19. Photogrammetry and photo interpretation applied to analyses of cloud cover, cloud type, and cloud motion

    NASA Technical Reports Server (NTRS)

    Larsen, P. A.

    1972-01-01

    A determination was made of the areal extent of terrain obscured by clouds and cloud shadows on a portion of an Apollo 9 photograph at the instant of exposure. This photogrammetrically determined area was then compared to the cloud coverage reported by surface weather observers at approximately the same time and location, as a check on result quality. Stereograms prepared from Apollo 9 vertical photographs, illustrating various percentages of cloud coverage, are presented to help provide a quantitative appreciation of the degradation of terrain photography by clouds and their attendant shadows. A scheme, developed for the U.S. Navy, utilizing pattern recognition techniques for determining cloud motion from sequences of satellite photographs, is summarized. Clouds, turbulence, haze, and solar altitude, four elements of our natural environment which affect aerial photographic missions, are each discussed in terms of their effects on imagery obtained by aerial photography. Data of a type useful to aerial photographic mission planners, expressing photographic ground coverage in terms of flying height above terrain and camera focal length, for a standard aerial photograph format, are provided. Two oblique orbital photographs taken during the Apollo 9 flight are shown, and photo-interpretations, discussing the cloud types imaged and certain visible geographical features, are provided.

  20. Simplified optical image encryption approach using single diffraction pattern in diffractive-imaging-based scheme.

    PubMed

    Qin, Yi; Gong, Qiong; Wang, Zhipeng

    2014-09-08

    In previous diffractive-imaging-based optical encryption schemes, it is impossible to totally retrieve the plaintext from a single diffraction pattern. In this paper, we proposed a new method to achieve this goal. The encryption procedure can be completed by proceeding only one exposure, and the single diffraction pattern is recorded as ciphertext. For recovering the plaintext, a novel median-filtering-based phase retrieval algorithm, including two iterative cycles, has been developed. This proposal not only extremely simplifies the encryption and decryption processes, but also facilitates the storage and transmission of the ciphertext, and its effectiveness and feasibility have been demonstrated by numerical simulations.

  1. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

    PubMed Central

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-01-01

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable. PMID:28042855

  2. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping.

    PubMed

    Cui, Tingting; Ji, Shunping; Shan, Jie; Gong, Jianya; Liu, Kejian

    2016-12-31

    For multi-sensor integrated systems, such as the mobile mapping system (MMS), data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

  3. Three-Dimensional Transcranial Ultrasound Imaging of Microbubble Clouds Using a Sparse Hemispherical Array

    PubMed Central

    O'Reilly, Meaghan A.; Jones, Ryan M.; Hynynen, Kullervo

    2014-01-01

    There is an increasing interest in bubble-mediated focused ultrasound (FUS) interventions in the brain. However, current technology lacks the ability to spatially monitor the interaction of the microbubbles with the applied acoustic field, something which is critical for safe clinical translation of these treatments. Passive acoustic mapping could offer a means for spatially monitoring microbubble emissions that relate to bubble activity and associated bioeffects. In this study a hemispherical receiver array was integrated within an existing transcranial therapy array to create a device capable of both delivering therapy and monitoring the process via passive imaging of bubble clouds. A 128-element receiver array was constructed and characterized for varying bubble concentrations and source spacings. Initial in vivo feasibility testing was performed. The system was found to be capable of monitoring bubble emissions down to single bubble events through an ex vivo human skull. The lateral resolution of the system was found to be between 1.25-2 mm and the axial resolution between 2-3.5 mm, comparable to the resolution of MRI-based temperature monitoring during thermal FUS treatments in the brain. The results of initial in vivo experiments show that bubble activity can be mapped starting at pressure levels below the threshold for Blood-Brain barrier disruption. This study presents a feasible solution for imaging bubble activity during cavitation-mediated FUS treatments in the brain. PMID:24658252

  4. Directional, horizontal inhomogeneities of cloud optical thickness fields retrieved from ground-based and airbornespectral imaging

    NASA Astrophysics Data System (ADS)

    Schäfer, Michael; Bierwirth, Eike; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Wendisch, Manfred

    2017-02-01

    Clouds exhibit distinct horizontal inhomogeneities of their optical and microphysical properties, which complicate their realistic representation in weather and climate models. In order to investigate the horizontal structure of cloud inhomogeneities, 2-D horizontal fields of optical thickness (τ) of subtropical cirrus and Arctic stratus are investigated with a spatial resolution of less than 10 m. The 2-D τ-fields are derived from (a) downward (transmitted) solar spectral radiance measurements from the ground beneath four subtropical cirrus and (b) upward (reflected) radiances measured from aircraft above 10 Arctic stratus. The data were collected during two field campaigns: (a) Clouds, Aerosol, Radiation, and tuRbulence in the trade wind regime over BArbados (CARRIBA) and (b) VERtical Distribution of Ice in Arctic clouds (VERDI). One-dimensional and 2-D autocorrelation functions, as well as power spectral densities, are derived from the retrieved τ-fields. The typical spatial scale of cloud inhomogeneities is quantified for each cloud case. Similarly, the scales at which 3-D radiative effects influence the radiance field are identified. In most of the investigated cloud cases considerable cloud inhomogeneities with a prevailing directional structure are found. In these cases, the cloud inhomogeneities favour a specific horizontal direction, while across this direction the cloud is of homogeneous character. The investigations reveal that it is not sufficient to quantify horizontal cloud inhomogeneities using 1-D inhomogeneity parameters; 2-D parameters are necessary.

  5. Venus Cloud Morphology and Motions from Ground-based Images at the Time of the Akatsuki Orbit Insertion

    NASA Astrophysics Data System (ADS)

    Sánchez-Lavega, A.; Peralta, J.; Gomez-Forrellad, J. M.; Hueso, R.; Pérez-Hoyos, S.; Mendikoa, I.; Rojas, J. F.; Horinouchi, T.; Lee, Y. J.; Watanabe, S.

    2016-12-01

    We report Venus image observations around the two maximum elongations of the planet at 2015 June and October. From these images we describe the global atmospheric dynamics and cloud morphology in the planet before the arrival of JAXA’s Akatsuki mission on 2015 December 7. The majority of the images were acquired at ultraviolet wavelengths (380-410 nm) using small telescopes. The Venus dayside was also observed with narrowband filters at other wavelengths (890 nm, 725-950 nm, 1.435 μm CO2 band) using the instrument PlanetCam-UPV/EHU at the 2.2 m telescope in Calar Alto Observatory. In all cases, the lucky imaging methodology was used to improve the spatial resolution of the images over the atmospheric seeing. During the April-June period, the morphology of the upper cloud showed an irregular and chaotic texture with a well-developed equatorial dark belt (afternoon hemisphere), whereas during October-December the dynamical regime was dominated by planetary-scale waves (Y-horizontal, C-reversed, and ψ-horizontal features) formed by long streaks, and banding suggesting more stable conditions. Measurements of the zonal wind velocity with cloud tracking in the latitude range from 50°N to 50°S shows agreement with retrievals from previous works. Partially based on observations obtained at Centro Astronómico Hispano Alemán, Observatorio de Calar Alto MPIA-CSIC, Almería, Spain.

  6. Evaluation of a cloud-based local-read paradigm for imaging evaluations in oncology clinical trials for lung cancer

    PubMed Central

    Kobayashi, Naomi; Bonnard, Eric; Charbonnier, Colette; Yamamichi, Junta; Mizobe, Hideaki; Kimura, Shinya

    2015-01-01

    Background Although tumor response evaluated with radiological imaging is frequently used as a primary endpoint in clinical trials, it is difficult to obtain precise results because of inter- and intra-observer differences. Purpose To evaluate usefulness of a cloud-based local-read paradigm implementing software solutions that standardize imaging evaluations among international investigator sites for clinical trials of lung cancer. Material and Methods Two studies were performed: KUMO I and KUMO I Extension. KUMO I was a pilot study aiming at demonstrating the feasibility of cloud implementation and identifying issues regarding variability of evaluations among sites. Chest CT scans at three time-points from baseline to progression, from 10 patients with lung cancer who were treated with EGFR tyrosine kinase inhibitors, were evaluated independently by two oncologists (Japan) and one radiologist (France), through a cloud-based software solution. The KUMO I Extension was performed based on the results of KUMO I. Results KUMO I showed discordance rates of 40% for target lesion selection, 70% for overall response at the first time-point, and 60% for overall response at the second time-point. Since the main reason for the discordance was differences in the selection of target lesions, KUMO I Extension added a cloud-based quality control service to achieve a consensus on the selection of target lesions, resulting in an improved rate of agreement of response evaluations. Conclusion The study shows the feasibility of imaging evaluations at investigator sites, based on cloud services for clinical studies involving multiple international sites. This system offers a step forward in standardizing evaluations of images among widely dispersed sites. PMID:26668754

  7. Pattern Recognition Of Blood Vessel Networks In Ocular Fundus Images

    NASA Astrophysics Data System (ADS)

    Akita, K.; Kuga, H.

    1982-11-01

    We propose a computer method of recognizing blood vessel networks in color ocular fundus images which are used in the mass diagnosis of adult diseases such as hypertension and diabetes. A line detection algorithm is applied to extract the blood vessels, and the skeleton patterns of them are made to analyze and describe their structures. The recognition of line segments of arteries and/or veins in the vessel networks consists of three stages. First, a few segments which satisfy a certain constraint are picked up and discriminated as arteries or veins. This is the initial labeling. Then the remaining unknown ones are labeled by utilizing the physical level knowledge. We propose two schemes for this stage : a deterministic labeling and a probabilistic relaxation labeling. Finally the label of each line segment is checked so as to minimize the total number of labeling contradictions. Some experimental results are also presented.

  8. Traumatic Rib Injury: Patterns, Imaging Pitfalls, Complications, and Treatment.

    PubMed

    Talbot, Brett S; Gange, Christopher P; Chaturvedi, Apeksha; Klionsky, Nina; Hobbs, Susan K; Chaturvedi, Abhishek

    2017-01-01

    The ribs are frequently affected by blunt or penetrating injury to the thorax. In the emergency department setting, it is vital for the interpreting radiologist to not only identify the presence of rib injuries but also alert the clinician about organ-specific injury, specific traumatic patterns, and acute rib trauma complications that require emergent attention. Rib injuries can be separated into specific morphologic fracture patterns that include stress, buckle, nondisplaced, displaced, segmental, and pathologic fractures. Specific attention is also required for flail chest and for fractures due to pediatric nonaccidental trauma. Rib fractures are associated with significant morbidity and mortality, both of which increase as the number of fractured ribs increases. Key complications associated with rib fracture include pain, hemothorax, pneumothorax, extrapleural hematoma, pulmonary contusion, pulmonary laceration, acute vascular injury, and abdominal solid-organ injury. Congenital anomalies, including supernumerary or accessory ribs, vestigial anterior ribs, bifid ribs, and synostoses, are common and should not be confused with traumatic pathologic conditions. Nontraumatic mimics of traumatic rib injury, with or without fracture, include metastatic disease, primary osseous neoplasms (osteosarcoma, chondrosarcoma, Ewing sarcoma, Langerhans cell histiocytosis, and osteochondroma), fibrous dysplasia, and Paget disease. Principles of management include supportive and procedural methods of alleviating pain, treating complications, and stabilizing posttraumatic deformity. By recognizing and accurately reporting the imaging findings, the radiologist will add value to the care of patients with thoracic trauma. Online supplemental material is available for this article. (©)RSNA, 2017.

  9. Mask image position correction for double patterning lithography

    NASA Astrophysics Data System (ADS)

    Saito, Masato; Itoh, Masamitsu; Ikenaga, Osamu; Ishigo, Kazutaka

    2008-05-01

    Application of double patterning technique has been discussed for lithography of HP 3X nm device generation. In this case, overlay budget for lithography becomes so hard that it is difficult to achieve it with only improvement of photomask's position accuracy. One of the factors of overlay error will be induced by distortion of photomask after chucking on the mask stage of exposure tool, because photomasks are bended by the force of vacuum chucking. Recently, mask flatness prediction technique was developed. This technique is simulating the surface shape of mask when it is on the mask stage by using the flatness data of free-standing state blank and the information of mask chucking stage. To use this predicted flatness data, it is possible to predict a pattern position error after exposed and it is possible to correct it on the photomask. A blank supplier developed the flatness data transfer system to mask vender. Every blanks are distinguished individually by 2D barcode mark on blank which including serial number. The flatness data of each blank is linked with this serial number, and mask vender can use this serial number as a key code to mask flatness data. We developed mask image position correction system by using 2D barcode mark linked to predicted flatness data, and position accuracy assurance system for these masks. And with these systems, we made some masks actually.

  10. Superresolution imaging with optical fluctuation using speckle patterns illumination

    PubMed Central

    Kim, MinKwan; Park, ChungHyun; Rodriguez, Christophe; Park, YongKeun; Cho, Yong-Hoon

    2015-01-01

    Superresolution fluorescence microscopy possesses an important role for the study of processes in biological cells with subdiffraction resolution. Recently, superresolution methods employing the emission properties of fluorophores have rapidly evolved due to their technical simplicity and direct applicability to existing microscopes. However, the application of these methods has been limited to samples labeled with fluorophores that can exhibit intrinsic emission properties at a restricted timescale, especially stochastic blinking. Here, we present a superresolution method that can be performed using general fluorophores, regardless of this intrinsic property. Utilizing speckle patterns illumination, temporal emission fluctuation of fluorophores is induced and controlled, from which a superresolution image can be obtained exploiting its statistical property. Using this method, we demonstrate, theoretically and experimentally, the capability to produce subdiffraction resolution images. A spatial resolution of 500 nm, 300 nm and 140 nm with 0.4, 0.5 and 1.4 NA objective lenses respectively was achieved in various samples with an enhancement factor of 1.6 compared to conventional fluorescence microscopy. PMID:26572283

  11. Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification

    NASA Astrophysics Data System (ADS)

    Gerke, Markus; Xiao, Jing

    2014-01-01

    Automatic urban object detection from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Laserscanning (ALS) data available today. This paper combines ALS data and airborne imagery to exploit both: the good geometric quality of ALS and the spectral image information to detect the four classes buildings, trees, vegetated ground and sealed ground. A new segmentation approach is introduced which also makes use of geometric and spectral data during classification entity definition. Geometric, textural, low level and mid level image features are assigned to laser points which are quantified into voxels. The segment information is transferred to the voxels and those clusters of voxels form the entity to be classified. Two classification strategies are pursued: a supervised method, using Random Trees and an unsupervised approach, embedded in a Markov Random Field framework and using graph-cuts for energy optimization. A further contribution of this paper concerns the image-based point densification for building roofs which aims to mitigate the accuracy problems related to large ALS point spacing. Results for the ISPRS benchmark test data show that to rely on color information to separate vegetation from non-vegetation areas does mostly lead to good results, but in particular in shadow areas a confusion between classes might occur. The unsupervised classification strategy is especially sensitive in this respect. As far as the point cloud densification is concerned, we observe similar sensitivity with respect to color which makes some planes to be missed out, or false detections still remain. For planes where the densification is successful we see the expected enhancement of the outline.

  12. Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning.

    PubMed

    Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

    2017-03-15

    Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

  13. Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning

    PubMed Central

    Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

    2017-01-01

    Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood. PMID:28294963

  14. Imaging patterns with 99mTc-PIPIDA in evaluating abdominal pain

    SciTech Connect

    Curtis, R.F.; Gordon, L.; Selby, J.B. Sr.

    1983-11-01

    A random retrospective review of hepatobiliary scans on 86 adult patients with abdominal pain revealed four distinct imaging patterns: normal, cystic duct obstruction, obstructive, and sick liver pattern. A normal pattern was found to exclude acute cholecystitis and was the pattern most frequently observed.

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

    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 μmol/m2/s in July and -8.8 μmol/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 μmol/m2/s respectively. With comparable higher incident radiation intensity (>1000 μmol/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 μmol/m2/s), the CO2 fluxes were higher in overcast days than in foggy days. The

  16. Characterizing growth patterns in longitudinal MRI using image contrast

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    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.

  17. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

    PubMed Central

    Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

    2017-01-01

    The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

  18. Environmental controls in the water use patterns of a tropical cloud forest tree species, Drimys brasiliensis (Winteraceae).

    PubMed

    Eller, Cleiton B; Burgess, Stephen S O; Oliveira, Rafael S

    2015-04-01

    Trees from tropical montane cloud forest (TMCF) display very dynamic patterns of water use. They are capable of downwards water transport towards the soil during leaf-wetting events, likely a consequence of foliar water uptake (FWU), as well as high rates of night-time transpiration (Enight) during drier nights. These two processes might represent important sources of water losses and gains to the plant, but little is known about the environmental factors controlling these water fluxes. We evaluated how contrasting atmospheric and soil water conditions control diurnal, nocturnal and seasonal dynamics of sap flow in Drimys brasiliensis (Miers), a common Neotropical cloud forest species. We monitored the seasonal variation of soil water content, micrometeorological conditions and sap flow of D. brasiliensis trees in the field during wet and dry seasons. We also conducted a greenhouse experiment exposing D. brasiliensis saplings under contrasting soil water conditions to deuterium-labelled fog water. We found that during the night D. brasiliensis possesses heightened stomatal sensitivity to soil drought and vapour pressure deficit, which reduces night-time water loss. Leaf-wetting events had a strong suppressive effect on tree transpiration (E). Foliar water uptake increased in magnitude with drier soil and during longer leaf-wetting events. The difference between diurnal and nocturnal stomatal behaviour in D. brasiliensis could be attributed to an optimization of carbon gain when leaves are dry, as well as minimization of nocturnal water loss. The leaf-wetting events on the other hand seem important to D. brasiliensis water balance, especially during soil droughts, both by suppressing tree transpiration (E) and as a small additional water supply through FWU. Our results suggest that decreases in leaf-wetting events in TMCF might increase D. brasiliensis water loss and decrease its water gains, which could compromise its ecophysiological performance and survival

  19. Adaptive Optics imaging of small cloud features on Neptune: zonal wind variability and detections of oscillations in longitude

    NASA Astrophysics Data System (ADS)

    Martin, S. C.; de Pater, I.; Gibbard, S. G.; Marcus, P.; Roe, H. G.; Macintosh, B. A.; Max, C. E.

    2004-11-01

    We present the results of an imaging experiment designed to track the motions of clouds in the upper atmosphere of Neptune. Images were taken in H band (1.4-1.8 microns) with a resolution of .06 arcseconds using the NIRSPEC/AO system on the W. M. Keck II telescope August 20 2001 UT. This dataset is unique in that it is densely sampled in time: 56 images were taken during 4 hours, and the time interval between images ranged from 1 to 32 minutes. The positions as a function of time were determined for 51 cloud features at southern midlatitudes (15-50 degrees South.) In this region, cloud features are visually organized into bands of clouds that almost follow lines of constant latitude. The two major findings of this analysis are: 1. The drift rates of clouds (as determined from the linear fit of longitude versus time curves) are highly variable for a given latitude band. Rotation periods range over several hours per cloud band, yielding relative velocities that are in some cases supersonic. 2. Graphs of longitude versus time are not strictly linear but rather show an oscillation in longitude. We have subtracted the linear drift rate and made empirical fits to the residuals of 12 features which have the longest time baselines of observations. Amplitudes of oscillations are 2-4 degrees of longitude, and periods are comparable to the 4 hour observation time. This is the first detection of small oscillations in the atmosphere of Neptune. Sromovsky, Limaye and Frye (1993) measured oscillations of much greater amplitudes and periods in the Great Dark Spot (GDS) and in the Second Dark Spot (DS2) of Neptune using Voyager data. This research was supported in part by the STC Program of the National Science Foundation under Agreement No. AST-9876783, and in part under the auspices of the US Department of Energy at Lawrence Livermore National Laboratory, Univ. of Calif. under contract No. W-7405-Eng-48. Data presented herein were obtained at the W.M. Keck Observatory, which is

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

    NASA Technical Reports Server (NTRS)

    Andrefeouet, Serge; Robinson, Julie

    2000-01-01

    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

  1. The airborne volcanic object imaging detector (AVOID): A new tool for airborne atmospheric remote sensing of clouds

    NASA Astrophysics Data System (ADS)

    Prata, F.; Durant, A.; Kylling, A.

    2012-04-01

    A new dual thermal imaging infrared camera system has been developed for aircraft in order to investigate water and volcanic clouds ahead. The system, AVOID, uses interference filters to discriminate clouds of water and ice from volcanic substances (silicates) by utilising the spectral features of these substances at wavelengths between 8-12 µm. Tests of the system were recently conducted in Sicily, in the vicinity of Mt Etna volcano and at Stromboli volcano, during emission of ash and SO2. The data were acquired from altitudes up to 12,000 ft, sampling from two cameras at frequencies down to 1 Hz. Corrections for the aircraft attitude were made using a very fast sampling attitude sensor, collocated with the imaging system. About 30 hours of data were acquired - over 90% of these measurements were of meteorological clouds of water droplets and ice. Using a radiative transfer model and information on the spectral refractive indices of water, ice and silicate ash, a retrieval scheme has been devised to determine the mass loading and effective particle radius of these substances and some preliminary results are presented. We have also developed a sophisticated simulation tool that allows us to model the 3D structure of clouds based on Monte Carlo radiative transfer. By utilising a narrow bandpass filter centred on 8.6 µm, AVOID can also detect SO2 gas and some illustrative examples are shown. During March 2012 the AVOID system will be mounted onto an AIRBUS A340 and flown at altitudes up to 38,000 ft. These tests will include measurements of clouds, as well as drifting volcanic ash and SO2 gas. We intend to present some of these initial results.

  2. Identifying galaxy candidates in WSRT H i imaging of ultra-compact high velocity clouds

    NASA Astrophysics Data System (ADS)

    Adams, Elizabeth A. K.; Oosterloo, Tom A.; Cannon, John M.; Giovanelli, Riccardo; Haynes, Martha P.

    2016-12-01

    Ultra-compact high velocity clouds (UCHVCs) were identified in the Arecibo Legacy Fast ALFA (ALFALFA) H i survey as potential gas-bearing dark matter halos. Here we present higher resolution neutral hydrogen (H i) observations of twelve UCHVCS with the Westerbork Synthesis Radio Telescope (WSRT). The UCHVCs were selected based on a combination of size, isolation, large recessional velocity and high column density as the best candidate dark matter halos. The WSRT data were tapered to image the UCHVCs at 210'' (comparable to the Arecibo resolution) and 105'' angular resolution. In a comparison of the single-dish to interferometer data, we find that the integrated line flux recovered in the WSRT observations is generally comparable to that from the single-dish ALFALFA data. In addition, any structure seen in the ALFALFA data is reproduced in the WSRT maps at the same angular resolution. At 210'' resolution all the sources are generally compact with a smooth H i morphology, as expected from their identification as UCHVCs. At the higher angular resolution, a majority of the sources break into small clumps contained in a diffuse envelope. These UCHVCs also have no ordered velocity motion and are most likely Galactic halo clouds. We identify two UCHVCs, AGC 198606 and AGC 249525, as excellent galaxy candidates based on maintaining a smooth H i morphology at higher angular resolution and showing ordered velocity motion consistent with rotation. A third source, AGC 249565, lies between these two populations in properties and is a possible galaxy candidate. If interpreted as gas-bearing dark matter halos, the three candidate galaxies have rotation velocities of 8-15 km s-1, H i masses of 0.6-50 × 105M⊙, H i radii of 0.3-2 kpc, and dynamical masses of 2-20 × 107M⊙ for a range of plausible distances. These are the UCHVCs with the highest column density values in the ALFALFA H i data and we suggest this is the best way to identify further candidates.

  3. Uranus' Persistent Patterns and Features from High-SNR Imaging in 2012-2014

    NASA Astrophysics Data System (ADS)

    Fry, Patrick M.; Sromovsky, Lawrence A.; de Pater, Imke; Hammel, Heidi B.; Marcus, Phillip

    2015-11-01

    Since 2012, Uranus has been the subject of an observing campaign utilizing high signal-to-noise imaging techniques at Keck Observatory (Fry et al. 2012, Astron. J. 143, 150-161). High quality observing conditions on four observing runs of consecutive nights allowed longitudinally-complete coverage of the atmosphere over a period of two years (Sromovsky et al. 2015, Icarus 258, 192-223). Global mosaic maps made from images acquired on successive nights in August 2012, November 2012, August 2013, and August 2014, show persistent patterns, and six easily distinguished long-lived cloud features, which we were able to track for long periods that ranged from 5 months to over two years. Two at similar latitudes are associated with dark spots, and move with the atmospheric zonal flow close to the location of their associated dark spot instead of following the flow at the latitude of the bright features. These features retained their morphologies and drift rates in spite of several close interactions. A second pair of features at similar latitudes also survived several close approaches. Several of the long-lived features also exhibited equatorward drifts and latitudinal oscillations. Also persistent are a remarkable near-equatorial wave feature and global zonal band structure. We will present imagery, maps, and analyses of these phenomena.PMF and LAS acknowledge support from NASA Planetary Astronomy Program; PMF and LAS acknowledge funding and technical support from W. M. Keck Observatory. We thank those of Hawaiian ancestry on whose sacred mountain we are privileged to be guests. Without their generous hospitality none of our groundbased observations would have been possible.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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.

  5. Zernike moments as a useful tool for ACE imager aerological data retrieval (stratospheric temperature and cloud product)

    NASA Astrophysics Data System (ADS)

    Dodion, Jan; Fussen, Didier; Filip, Vanhellemont; Mateshvili, Nina; Christine, Bingen; Maxime, Stapelle; Dekemper, Emmanuel; Gilbert, Kathy; Walker, Kaley; Bernath, Peter

    The Atmospheric Chemistry Experiment (ACE) was launched in August 2003 aboard the Canadian satellite SCISAT-I, and is at present fully operational. ACE circles the Earth at an altitude of 650 km with an orbital inclination of 74° . Solar occultation is the primary observation technique used by the on board instruments, which consist of a high resolution Fourier Transform spectrometer (ACE-FTS), a dual optical spectrophotometer (MAESTRO) and two filtered imagers, subject of this presentation. While the Sun is setting below or rising from behind the Earth's horizon, at every timestamp, the imagers capture a snapshot of the Sun as seen through the atmosphere. On these pictures, the apparent Sun width is about 25 km at the tangent point and the apparent Sun height varies from almost 0.7 km in the optically thick, lower troposphere where the Sun image is highly flattened by the refraction to its maximum (about 25 km at the tangent point) where refractive effects are negligible. Used in image processing, image moments are certain particular weighted averages (moments) of the image pixel's intensities, or functions of those moments, usually chosen to have some attractive property on interpretation. Zernike moments were first introduced by Teague (1980) based on the complex, orthogonal functions called Zernike polynomials. Though computationally very complex compared to geometric and Legendre moments, Zernike moments have proved to be superior in terms of their feature representation capability and low noise sensitivity. Also, the construction of different moment invariants makes them well suited for our research. A detailed image analysis of ACE imager data using Zernike moments provides us the necessary information for the retrieval of temperature profiles from a series of distorted images of an object of known shape such as the Sun. These temperature profiles are validated with ACE-FTS data. Besides, a preliminary cloud product could be derived and, in addition, a

  6. Moderate Resolution Spectroscopy of Directly Imaged Exoplanets: Formation, Chemistry, and Clouds

    NASA Astrophysics Data System (ADS)

    Konopacky, Quinn

    resolution data, capable of resolving atomic and molecular lines. Depending upon the mode of planet formation, the differentiation of solids and gas in a protoplanetary disk may lead to elemental abundances that differ substantially from that of the host star. Subsequent migration or planetesimal accretion after formation can also lead to variation in the abundance of species such as carbon and oxygen. Our program will yield measurements of abundances and abundance ratios precise enough to study the early accretion history for a variety of giant planets. We will provide a library of J, H, and K near-IR spectra for all observable directly imaged planets at these spectral resolutions. We will use these spectra to measure abundance ratios and search for higher atomic number species such as sodium and iron. Grids of models will be generated to test possible values of carbon, oxygen, and other metal abundances, in addition to properties such as non-equilibrium chemistry and cloud coverage. In order to assure that these models are not systematically yielding certain abundance values, we will test their predictions on a set of well-studied brown dwarfs with precisely measured masses, temperatures, and gravities. The research proposed here is highly relevant to the NASA Exoplanets Research program. By probing the spectra of gas giant planets in unmatched detail, we seek to provide a fundamental understanding of the physical processes at work during the early stages of planet formation and the subsequent atmospheric evolution as a function of mass and age. The proposed research will complement current NASA exoplanet missions by investigating the relatively unexplored population of widely separated planets. We will also provide a framework for measuring atmospheric properties that will be applicable to planets discovered with upcoming NASA missions such as WFIRST-AFTA and JWST.

  7. Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

    NASA Astrophysics Data System (ADS)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high

  8. Cloud Computing for radiologists.

    PubMed

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

    2012-07-01

    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.

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

    ERIC Educational Resources Information Center

    Evans, John M. , Ed.; And Others

    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…

  10. Increasing accuracy and precision of digital image correlation through pattern optimization

    NASA Astrophysics Data System (ADS)

    Bomarito, G. F.; Hochhalter, J. D.; Ruggles, T. J.; Cannon, A. H.

    2017-04-01

    The accuracy and precision of digital image correlation (DIC) is based on three primary components: image acquisition, image analysis, and the subject of the image. Focus on the third component, the image subject, has been relatively limited and primarily concerned with comparing pseudo-random surface patterns. In the current work, a strategy is proposed for the creation of optimal DIC patterns. In this strategy, a pattern quality metric is developed as a combination of quality metrics from the literature rather than optimization based on any single one of them. In this way, optimization produces a pattern which balances the benefits of multiple quality metrics. Specifically, sum of square of subset intensity gradients (SSSIG) was found to be the metric most strongly correlated to DIC accuracy and thus is the main component of the newly proposed pattern quality metric. A term related to the secondary auto-correlation peak height is also part of the proposed quality metric which effectively acts as a constraint upon SSSIG ensuring that a regular (e.g., checkerboard-type) pattern is not achieved. The combined pattern quality metric is used to generate a pattern that was on average 11.6% more accurate than a randomly generated pattern in a suite of numerical experiments. Furthermore, physical experiments were performed which confirm that there is indeed improvement of a similar magnitude in DIC measurements for the optimized pattern compared to a random pattern.

  11. Imaging polychromator for density measurements of polystyrene pellet cloud on the Large Helical Device.

    PubMed

    Sharov, I A; Sergeev, V Yu; Miroshnikov, I V; Tamura, N; Kuteev, B V; Sudo, S

    2015-04-01

    Experimental data on spatial distributions of a pellet cloud electron density are necessary for the development of many applications of pellet injection, namely, plasma fuelling, discharge control, and plasma diagnostics. An improved approach of electron density measurements inside the cloud of a polystyrene pellet ablating in hot plasma of the large helical device is described. Density values of (1-30) × 10(16) cm(-3) depending on the background plasma parameters and distance from the solid pellet were measured.

  12. A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

    NASA Astrophysics Data System (ADS)

    Hsu, Kuo-Hsien

    2012-11-01

    Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

  13. Multi-Focus Raw Bayer Pattern Image Fusion for Single-Chip Camera

    NASA Astrophysics Data System (ADS)

    Yang, Bin; Chen, Jibin

    2015-12-01

    In this paper, an efficient patch-based image fusion approach for raw images of single-chip imaging devices incorporated with the Bayer CFA pattern is presented. The multi-source raw Bayer pattern images are firstly parted into half overlapped patches. Then, the patches with maximum clarity measurement defined for raw Bayer pattern image are selected as the fused patches. Next, all the fused local patches are merged with weighted average method in order to reduce the blockness effect of fused raw Bayer pattern image. Finally, the real color fused image is obtained by gradient based demosaicing technology. The multi-source raw Bayer pattern data is fused before demosaicing, so that the multi-sensor system will be more efficient and the artifacts introduced in demosaicing processing do not accumulate in image fusion processing. For comparison, the raw images are also interpolated firstly, and then various image fusion methods are used to get the fused color images. Experimental results show that the proposed algorithm is valid and very effective.

  14. Cloud Front

    NASA Technical Reports Server (NTRS)

    2006-01-01

    [figure removed for brevity, see original site] Context image for PIA02171 Cloud Front

    These clouds formed in the south polar region. The faintness of the cloud system likely indicates that these are mainly ice clouds, with relatively little dust content.

    Image information: VIS instrument. Latitude -86.7N, Longitude 212.3E. 17 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

  15. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    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.

  16. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Vazquez Rueda, Martin G.; Hahn, Federico

    1999-03-01

    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.

  18. Near-Resonant Imaging of Trapped Cold Atomic Samples

    PubMed Central

    You, L.; Lewenstein, Maciej

    1996-01-01

    We study the formation of diffraction patterns in the near-resonant imaging of trapped cold atomic samples. We show that the spatial imaging can provide detailed information on the trapped atomic clouds. PMID:27805110

  19. Basic research planning in mathematical pattern recognition and image analysis

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

    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.

  20. Data management in pattern recognition and image processing systems

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

    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.

  1. Evidence for island effects and diurnal signals in satellite images of clouds over the tropical western pacific

    SciTech Connect

    Barr-Kumarakulasinghe, S.A.; Reynolds, R.M.; Minnett, P.J.

    1996-04-01

    Instruments to measure atmospheric radiation and ancillary meteorological variables will be set up on Manus Island as the first site of the tropical western pacific (TWP) locale of the Atmospheric Radiation Measurements (ARM) program. Manus is in the {open_quotes}warm pool{close_quotes} region of the TWP. This region is critical in establishing global atmospheric circulation patterns and is a primary energy source for the Hadley and Walker cells. The myriad islands and enclosed seas in the immediate vicinity of Manus have been referred to as the {open_quotes}maritime continent{close_quotes}, which has the deepest convective activity in the world. Manus is in a region having a global impact on climate and where island effects on clouds are likely to be important. In this preliminary analysis we have sought evidence of island effects in the cloud fields around Manus and have studied the variability of the diurnal cycles of cloud cover over Manus and over other islands and areas of open sea in the region.

  2. Thin Clouds

    Atmospheric Science Data Center

    2013-04-18

    ... one of a new generation of instruments flying aboard the NASA Earth Observing System's Terra satellite, views Earth with nine cameras ... of thin cirrus minutes after MISR imaged the cloud from space. At the same time, another NASA high-altitude jet, the WB-57, flew right ...

  3. The embedded young stars in the Taurus-Auriga molecular cloud. II - Models for scattered light images

    NASA Technical Reports Server (NTRS)

    Kenyon, Scott J.; Whitney, Barbara A.; Gomez, Mercedes; Hartmann, Lee

    1993-01-01

    We describe NIR imaging observations of embedded young stars in the Taurus-Auriga molecular cloud. We find a large range in J-K and H-K colors for these class I sources. The bluest objects have colors similar to the reddest T Tauri stars in the cloud; redder objects lie slightly above the reddening line for standard ISM dust and have apparent K extinctions of up to 5 mag. Most of these sources also show extended NIR emission on scales of 10-20 arcsec which corresponds to linear sizes of 1500-3000 AU. The NIR colors and nebular morphologies for this sample and the magnitude of linear polarization in several sources suggest scattered light produces most of the NIR emission in these objects. We present modeling results that suggest mass infall rates that agree with predictions for cold clouds and are generally consistent with rates estimated from radiative equilibrium models. For reasonable dust grain parameters, the range of colors and extinctions require flattened density distributions with polar cavities evacuated by bipolar outflows. These results support the idea that infall and outflow occur simultaneously in deeply embedded bipolar outflow sources. The data also indicate fairly large centrifugal radii and large inclinations to the rotational axis for a typical source.

  4. Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection.

    PubMed

    Gottschlich, Carsten

    2016-01-01

    We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification.

  5. Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

    PubMed Central

    Gottschlich, Carsten

    2016-01-01

    We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

  6. Imaging polychromator for density measurements of polystyrene pellet cloud on the Large Helical Device

    SciTech Connect

    Sharov, I. A. Sergeev, V. Yu.; Miroshnikov, I. V.; Tamura, N.; Sudo, S.; Kuteev, B. V.

    2015-04-15

    Experimental data on spatial distributions of a pellet cloud electron density are necessary for the development of many applications of pellet injection, namely, plasma fuelling, discharge control, and plasma diagnostics. An improved approach of electron density measurements inside the cloud of a polystyrene pellet ablating in hot plasma of the large helical device is described. Density values of (1-30) × 10{sup 16} cm{sup −3} depending on the background plasma parameters and distance from the solid pellet were measured.

  7. Southern Clouds

    NASA Technical Reports Server (NTRS)

    2005-01-01

    [figure removed for brevity, see original site] Context image for PIA03026 Southern Clouds

    This image shows a system of clouds just off the margin of the South Polar cap. Taken during the summer season, these clouds contain both water-ice and dust.

    Image information: VIS instrument. Latitude 80.2S, Longitude 57.6E. 17 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

  8. Linear Clouds

    NASA Technical Reports Server (NTRS)

    2006-01-01

    [figure removed for brevity, see original site] Context image for PIA03667 Linear Clouds

    These clouds are located near the edge of the south polar region. The cloud tops are the puffy white features in the bottom half of the image.

    Image information: VIS instrument. Latitude -80.1N, Longitude 52.1E. 17 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

  9. TiLIA: a software package for image analysis of firefly flash patterns.

    PubMed

    Konno, Junsuke; Hatta-Ohashi, Yoko; Akiyoshi, Ryutaro; Thancharoen, Anchana; Silalom, Somyot; Sakchoowong, Watana; Yiu, Vor; Ohba, Nobuyoshi; Suzuki, Hirobumi

    2016-05-01

    As flash signaling patterns of fireflies are species specific, signal-pattern analysis is important for understanding this system of communication. Here, we present time-lapse image analysis (TiLIA), a free open-source software package for signal and flight pattern analyses of fireflies that uses video-recorded image data. TiLIA enables flight path tracing of individual fireflies and provides frame-by-frame coordinates and light intensity data. As an example of TiLIA capabilities, we demonstrate flash pattern analysis of the fireflies Luciola cruciata and L. lateralis during courtship behavior.

  10. Content based image retrieval using local binary pattern operator and data mining techniques.

    PubMed

    Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

    2015-01-01

    Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

  11. The study on cloud masking of GOCI optical images by using adaptive threshold and BRDF-based NDVI profiles for the land application

    NASA Astrophysics Data System (ADS)

    Kim, H. W.; Yeom, J. M.; Woo, S. H.; Kim, Y. S.; Chae, T. B.

    2015-12-01

    Geostationary Ocean Color Imager (GOCI) which was launched on 27 June 2010, developed to detect, monitor, and predict the ocean phenomena around Korea. Although GOCI was developed to observe the ocean environment, GOCI has also enormous scientific data for land surface. However, it is extremely important to extract the cloud pixels over the land surface to utilize its data for the land application. Over the land surface, the reflectance variation is higher and the characteristic of surface is more various than those over the ocean. Furthermore, the infra-red (IR) channel is not included in 8 GOCI bands, which is useful to detect the thin cloud and the water vapor with cloud top temperature. Nevertheless, GOCI has potential to detect the cloud using the temporal variation due to the characteristics of geostationary satellite observation. The purpose of this study is to estimate the cloud masking maps over the Korean Peninsula. For cloud masking with GOCI, following methods are used; simple threshold with reflectance and ratio of bands, adaptive threshold with multi-temporal images, and stable multi-temporal vegetation image. In the case of adaptive threshold, high variable cloudy when comparing with surface reflectance is used by comparing the surface reflectance by temporal based analysis. In this study, the multi-temporal NDVI data processed by the bi-directional reflectance distribution function (BRDF) modeling also used to reflect the relative solar-target-sensor geometry during the daytime. This result will have a substantial role for the land application using GOCI data.

  12. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    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.

  13. Compressive spectral polarization imaging by a pixelized polarizer and colored patterned detector.

    PubMed

    Fu, Chen; Arguello, Henry; Sadler, Brian M; Arce, Gonzalo R

    2015-11-01

    A compressive spectral and polarization imager based on a pixelized polarizer and colored patterned detector is presented. The proposed imager captures several dispersed compressive projections with spectral and polarization coding. Stokes parameter images at several wavelengths are reconstructed directly from 2D projections. Employing a pixelized polarizer and colored patterned detector enables compressive sensing over spatial, spectral, and polarization domains, reducing the total number of measurements. Compressive sensing codes are specially designed to enhance the peak signal-to-noise ratio in the reconstructed images. Experiments validate the architecture and reconstruction algorithms.

  14. Sahara Dust Cloud

    NASA Technical Reports Server (NTRS)

    2005-01-01

    [figure removed for brevity, see original site] Dust Particles Click on the image for Quicktime movie from 7/15-7/24

    A continent-sized cloud of hot air and dust originating from the Sahara Desert crossed the Atlantic Ocean and headed towards Florida and the Caribbean. A Saharan Air Layer, or SAL, forms when dry air and dust rise from Africa's west coast and ride the trade winds above the Atlantic Ocean.

    These dust clouds are not uncommon, especially during the months of July and August. They start when weather patterns called tropical waves pick up dust from the desert in North Africa, carry it a couple of miles into the atmosphere and drift westward.

    In a sequence of images created by data acquired by the Earth-orbiting Atmospheric Infrared Sounder ranging from July 15 through July 24, we see the distribution of the cloud in the atmosphere as it swirls off of Africa and heads across the ocean to the west. Using the unique silicate spectral signatures of dust in the thermal infrared, AIRS can detect the presence of dust in the atmosphere day or night. This detection works best if there are no clouds present on top of the dust; when clouds are present, they can interfere with the signal, making it much harder to detect dust as in the case of July 24, 2005.

    In the Quicktime movie, the scale at the bottom of the images shows +1 for dust definitely detected, and ranges down to -1 for no dust detected. The plots are averaged over a number of AIRS observations falling within grid boxes, and so it is possible to obtain fractional numbers. [figure removed for brevity, see original site] Total Water Vapor in the Atmosphere Around the Dust Cloud Click on the image for Quicktime movie

    The dust cloud is contained within a dry adiabatic layer which originates over the Sahara Desert. This Saharan Air Layer (SAL) advances Westward over the Atlantic Ocean, overriding the cool, moist air nearer the surface. This burst of very dry air is visible in the

  15. HOLOGondel: A novel in-situ cloud measurement platform on a cable car with a digital holographic imager

    NASA Astrophysics Data System (ADS)

    Beck, Alexander; Henneberger, Jan; Kanji, Zamin; Lohmann, Ulrike

    2015-04-01

    Cloud particle properties observed in-situ are commonly conducted from airborne or ground-based measurements. When compared to airborne measurements, the advantages of ground-based measurements are a higher spatial resolution and much less costly to perform. However, ground-based observations allow only single-point measurements within a cloud. To overcome this disadvantage, a novel measurement platform with a digital holographic imager has been developed to allow in-situ cloud observations on the roof of a cable car cabin. With a traveling velocity of a cable car of a few m/s, such a measurement platform yields a spatial resolution comparable to those of ground-based measurements. In addition, it is possible to obtain vertical profiles of the microphysical properties within the cloud, because of the vertical distance covered by the cable car of approximately 800m. The major technical challenges for such a measurement platform are the lack of an external power supply and the additional weight constrain on a cable car cabin. To allow continuous operation for eight hours with a battery and to stay within the weight limit of 25kg at the same time, a compact design with carefully chosen material and components with a low power consumption was necessary. The new measurement platform HOLOGondel is equipped with a HOLographic Imager for Microscopic Objects (HOLIMO 3G). Digital in-line holography offers the advantages of measuring simultaneously an ensemble of cloud particles within a well-defined detection volume over a large range of particle size. The image captured, a hologram, yields information about the three-dimensional position, size and a shadow-graph of each particle within the detection volume. The HOLIMO 3G instrument is equipped with a 30MP camera and a 1.8 times magnifying, both-sided telecentric lens system. At a frame rate of six pictures per second a sample volume rate of about 100 cm3s-1 at a maximum resolution of 7 µm is achieved. This configuration

  16. Investigation of mesoscale cloud features viewed by LANDSAT

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

    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.

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

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr.

    1983-01-01

    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.

  18. Coupling sky images with three-dimensional radiative transfer models: a new method to estimate cloud optical depth

    NASA Astrophysics Data System (ADS)

    Mejia, F. A.; Kurtz, B.; Murray, K.; Hinkelman, L. M.; Sengupta, M.; Xie, Y.; Kleissl, J.

    2015-10-01

    A method for retrieving cloud optical depth (τc) using a ground-based sky imager (USI) is presented. The Radiance Red-Blue Ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a 3-D Radiative Transfer Model (3DRTM). From these images the basic parameters affecting the radiance and RBR of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλ(τc, θ0, ϑs, ϑz) and the red-blue ratio, RBR(τc, θ0, ϑs, ϑz) are retrieved from the 3DRTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeas(ϑs, ϑz), in addition to RBRmeas(ϑs, ϑz) to obtain a unique solution for τc. The RRBR method is applied to images taken by a USI at the Oklahoma Atmospheric Radiation Measurement program (ARM) site over the course of 220 days and validated against measurements from a microwave radiometer (MWR); output from the Min method for overcast skies, and τc retrieved by Beer's law from direct normal irradiance (DNI) measurements. A τc RMSE of 5.6 between the Min method and the USI are observed. The MWR and USI have an RMSE of 2.3 which is well within the uncertainty of the MWR. An RMSE of 0.95 between the USI and DNI retrieved τc is observed. The procedure developed here provides a foundation to test and develop other cloud detection algorithms.

  19. Cloud-based application for rice moisture content measurement using image processing technique and perceptron neural network

    NASA Astrophysics Data System (ADS)

    Cruz, Febus Reidj G.; Padilla, Dionis A.; Hortinela, Carlos C.; Bucog, Krissel C.; Sarto, Mildred C.; Sia, Nirlu Sebastian A.; Chung, Wen-Yaw

    2017-02-01

    This study is about the determination of moisture content of milled rice using image processing technique and perceptron neural network algorithm. The algorithm involves several inputs that produces an output which is the moisture content of the milled rice. Several types of milled rice are used in this study, namely: Jasmine, Kokuyu, 5-Star, Ifugao, Malagkit, and NFA rice. The captured images are processed using MATLAB R2013a software. There is a USB dongle connected to the router which provided internet connection for online web access. The GizDuino IOT-644 is used for handling the temperature and humidity sensor, and for sending and receiving of data from computer to the cloud storage. The result is compared to the actual moisture content range using a moisture tester for milled rice. Based on results, this study provided accurate data in determining the moisture content of the milled rice.

  20. INFRARED AND OPTICAL IMAGINGS OF THE COMET 2P/ENCKE DUST CLOUD IN THE 2003 RETURN

    SciTech Connect

    Sarugaku, Yuki; Ueno, Munetaka; Ishiguro, Masateru; Usui, Fumihiko; Reach, William T.

    2015-05-10

    We report contemporaneous imaging observations of the short-period comet 2P/Encke in infrared and optical wavelengths during the 2003 return. Both images show the same unique morphology consisting of a spiky dust cloud near the nucleus and a dust trail extending along the orbit. We conducted a dynamical simulation of dust particles to characterize the morphology and found that dust particles were ejected intensively for a short duration (≲10 days) a few days after perihelion passage. The maximum particle size is at least on the order of 1 cm in radius following a differential power-law size distribution with an index of −3.2 to −3.6. The total mass ejected in the 2003 return is at least 1.5 × 10{sup 9}–1.2 × 10{sup 10} kg, which corresponds to 0.003%–0.03% of the nucleus mass. We derived the albedo of the dust cloud as 0.01–0.04 at a solar phase angle of 26.°2, which is consistent with or possibly greater than that of the nucleus. We suppose that impulsive activity such as an outburst is a key to understanding the peculiar appearance of 2P/Encke.

  1. Ammonia Clouds on Jupiter

    NASA Technical Reports Server (NTRS)

    2007-01-01

    [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.

  2. Semantic Concept Co-Occurrence Patterns for Image Annotation and Retrieval.

    PubMed

    Feng, Linan; Bhanu, Bir

    2016-04-01

    Describing visual image contents by semantic concepts is an effective and straightforward way to facilitate various high level applications. Inferring semantic concepts from low-level pictorial feature analysis is challenging due to the semantic gap problem, while manually labeling concepts is unwise because of a large number of images in both online and offline collections. In this paper, we present a novel approach to automatically generate intermediate image descriptors by exploiting concept co-occurrence patterns in the pre-labeled training set that renders it possible to depict complex scene images semantically. Our work is motivated by the fact that multiple concepts that frequently co-occur across images form patterns which could provide contextual cues for individual concept inference. We discover the co-occurrence patterns as hierarchical communities by graph modularity maximization in a network with nodes and edges representing concepts and co-occurrence relationships separately. A random walk process working on the inferred concept probabilities with the discovered co-occurrence patterns is applied to acquire the refined concept signature representation. Through experiments in automatic image annotation and semantic image retrieval on several challenging datasets, we demonstrate the effectiveness of the proposed concept co-occurrence patterns as well as the concept signature representation in comparison with state-of-the-art approaches.

  3. Artificial neural network for bubbles pattern recognition on the images

    NASA Astrophysics Data System (ADS)

    Poletaev, I. E.; Pervunin, K. S.; Tokarev, M. P.

    2016-10-01

    Two-phase bubble flows have been used in many technological and energy processes as processing oil, chemical and nuclear reactors. This explains large interest to experimental and numerical studies of such flows last several decades. Exploiting of optical diagnostics for analysis of the bubble flows allows researchers obtaining of instantaneous velocity fields and gaseous phase distribution with the high spatial resolution non-intrusively. Behavior of light rays exhibits an intricate manner when they cross interphase boundaries of gaseous bubbles hence the identification of the bubbles images is a complicated problem. This work presents a method of bubbles images identification based on a modern technology of deep learning called convolutional neural networks (CNN). Neural networks are able to determine overlapping, blurred, and non-spherical bubble images. They can increase accuracy of the bubble image recognition, reduce the number of outliers, lower data processing time, and significantly decrease the number of settings for the identification in comparison with standard recognition methods developed before. In addition, usage of GPUs speeds up the learning process of CNN owning to the modern adaptive subgradient optimization techniques.

  4. Imaging in laser spectroscopy by a single-pixel camera based on speckle patterns

    NASA Astrophysics Data System (ADS)

    Žídek, K.; Václavík, J.

    2016-11-01

    Compressed sensing (CS) is a branch of computational optics able to reconstruct an image (or any other information) from a reduced number of measurements - thus significantly saving measurement time. It relies on encoding the detected information by a random pattern and consequent mathematical reconstruction. CS can be the enabling step to carry out imaging in many time-consuming measurements. The critical step in CS experiments is the method to invoke encoding by a random mask. Complex devices and relay optics are commonly used for the purpose. We present a new approach of creating the random mask by using laser speckles from coherent laser light passing through a diffusor. This concept is especially powerful in laser spectroscopy, where it does not require any complicated modification of the current techniques. The main advantage consist in the unmatched simplicity of the random pattern generation and a versatility of the pattern resolution. Unlike in the case of commonly used random masks, here the pattern fineness can be adjusted by changing the laser spot size being diffused. We demonstrate the pattern tuning together with the connected changes in the pattern statistics. In particular, the issue of patterns orthogonality, which is important for the CS applications, is discussed. Finally, we demonstrate on a set of 200 acquired speckle patterns that the concept can be successfully employed for single-pixel camera imaging. We discuss requirements on detector noise for the image reconstruction.

  5. Digital image pattern recognition system using normalized Fourier transform and normalized analytical Fourier-Mellin transform

    NASA Astrophysics Data System (ADS)

    Vélez-Rábago, Rodrigo; Solorza-Calderón, Selene; Jordan-Aramburo, Adina

    2016-12-01

    This work presents an image pattern recognition system invariant to translation, scale and rotation. The system uses the Fourier transform to achieve the invariance to translation and the analytical Forier-Mellin transform for the invariance to scale and rotation. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  6. Cloud Interactions

    NASA Technical Reports Server (NTRS)

    2004-01-01

    [figure removed for brevity, see original site]

    Released 1 July 2004 The atmosphere of Mars is a dynamic system. Water-ice clouds, fog, and hazes can make imaging the surface from space difficult. Dust storms can grow from local disturbances to global sizes, through which imaging is impossible. Seasonal temperature changes are the usual drivers in cloud and dust storm development and growth.

    Eons of atmospheric dust storm activity has left its mark on the surface of Mars. Dust carried aloft by the wind has settled out on every available surface; sand dunes have been created and moved by centuries of wind; and the effect of continual sand-blasting has modified many regions of Mars, creating yardangs and other unusual surface forms.

    This image was acquired during mid-spring near the North Pole. The linear water-ice clouds are now regional in extent and often interact with neighboring cloud system, as seen in this image. The bottom of the image shows how the interaction can destroy the linear nature. While the surface is still visible through most of the clouds, there is evidence that dust is also starting to enter the atmosphere.

    Image information: VIS instrument. Latitude 68.4, Longitude 258.8 East (101.2 West). 38 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration

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

    ERIC Educational Resources Information Center

    Stejic, Zoran; Takama, Yasufumi; Hirota, Kaoru

    2003-01-01

    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)

  8. An Empirical Study of Tropical Cloud cluters Using Special Sensor Microwave Imager Data.

    DTIC Science & Technology

    1993-08-01

    hail ) scatter microwave radiation much more effectively than do "soft" snowflakes of the same dimension, so that the algorithm shows a bias in...26 Chapter 4. ALGORITHMS FOR RETRIEVAL OF ATMOSPHERIC PARAMETERS ............................................................ 39 4.1 Column Integrated...processes at various levels within a cloud. Most of the copious research on microwave radiometry in recent years has been devoted to developing algorithms

  9. Statistical Image Recovery From Laser Speckle Patterns With Polarization Diversity

    DTIC Science & Technology

    2010-09-01

    polarization diversity. iv For my Lord, my wife and my three children . v Acknowledgements I would like to thank Dr Steve Cain for all of his help in this...reasonable if the image and pupil plane data are collected at angular or range offsets. With a slight change in angle, the random phase contributions from the...pulse that produce this effect. These pulse- to-pulse geometry changes may include target jitter due to movement, target surface deformation due to

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    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.

  11. Imaging outside the box: Resolution enhancement in X-ray coherent diffraction imaging by extrapolation of diffraction patterns

    SciTech Connect

    Latychevskaia, Tatiana Fink, Hans-Werner; Chushkin, Yuriy; Zontone, Federico

    2015-11-02

    Coherent diffraction imaging is a high-resolution imaging technique whose potential can be greatly enhanced by applying the extrapolation method presented here. We demonstrate the enhancement in resolution of a non-periodical object reconstructed from an experimental X-ray diffraction record which contains about 10% missing information, including the pixels in the center of the diffraction pattern. A diffraction pattern is extrapolated beyond the detector area and as a result, the object is reconstructed at an enhanced resolution and better agreement with experimental amplitudes is achieved. The optimal parameters for the iterative routine and the limits of the extrapolation procedure are discussed.

  12. Patterns of Hepatosplenic Brucella Abscesses on Cross-Sectional Imaging: A Review of Clinical and Imaging Features

    PubMed Central

    Heller, Tom; Bélard, Sabine; Wallrauch, Claudia; Carretto, Edoardo; Lissandrin, Raffaella; Filice, Carlo; Brunetti, Enrico

    2015-01-01

    While diffuse involvement of liver and spleen is frequently seen in brucellosis, suppurative abscesses caused by Brucella are less common but well described. With the increased availability of cross-sectional imaging techniques, reports have become more frequent. Four patients with hepatosplenic abscesses caused by Brucella spp. are described and included in a review of 115 previously published cases. Clinical characteristics and patterns on ultrasound (US) and computed tomography imaging were analyzed. Furthermore, the proportion of patients with brucellosis affected by suppurative hepatosplenic lesions was estimated. Hepatosplenic abscesses were seen in 1.2% of patients with brucellosis and were mostly caused by Brucella melitensis. Imaging analysis revealed two main distinct patterns. Solitary abscesses involving liver more frequently than spleen, and showing characteristic central calcifications, characterize the first pattern. Multiple smaller abscesses, frequent spleen involvement, and absence of calcifications characterize the second pattern. Blood and aspirate cultures were frequently negative, however, the positivity rate increased over the past years. Indirect Coombs test was positive in 96%. Half of the patients were cured by antibiotic treatment; case fatality in this series was 1.9%. Hepatosplenic abscesses due to Brucella infections have characteristic imaging findings. Clinicians should be aware of these and the proactive use of cross-sectional imaging, particularly US, should be encouraged in endemic regions. PMID:26283749

  13. Patterns of Hepatosplenic Brucella Abscesses on Cross-Sectional Imaging: A Review of Clinical and Imaging Features.

    PubMed

    Heller, Tom; Bélard, Sabine; Wallrauch, Claudia; Carretto, Edoardo; Lissandrin, Raffaella; Filice, Carlo; Brunetti, Enrico

    2015-10-01

    While diffuse involvement of liver and spleen is frequently seen in brucellosis, suppurative abscesses caused by Brucella are less common but well described. With the increased availability of cross-sectional imaging techniques, reports have become more frequent. Four patients with hepatosplenic abscesses caused by Brucella spp. are described and included in a review of 115 previously published cases. Clinical characteristics and patterns on ultrasound (US) and computed tomography imaging were analyzed. Furthermore, the proportion of patients with brucellosis affected by suppurative hepatosplenic lesions was estimated. Hepatosplenic abscesses were seen in 1.2% of patients with brucellosis and were mostly caused by Brucella melitensis. Imaging analysis revealed two main distinct patterns. Solitary abscesses involving liver more frequently than spleen, and showing characteristic central calcifications, characterize the first pattern. Multiple smaller abscesses, frequent spleen involvement, and absence of calcifications characterize the second pattern. Blood and aspirate cultures were frequently negative, however, the positivity rate increased over the past years. Indirect Coombs test was positive in 96%. Half of the patients were cured by antibiotic treatment; case fatality in this series was 1.9%. Hepatosplenic abscesses due to Brucella infections have characteristic imaging findings. Clinicians should be aware of these and the proactive use of cross-sectional imaging, particularly US, should be encouraged in endemic regions.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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

  15. Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

    NASA Astrophysics Data System (ADS)

    Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

    2016-07-01

    To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

  16. Lensless coherent imaging by phase retrieval with an illumination pattern constraint.

    PubMed

    Fienup, James R

    2006-01-23

    It is often possible to reduce the requirements on an imaging system by placing greater demands either on an illumination system or on post-detection processing of the data collected by the system. An extreme example of this is a system with no receiver optics whatsoever. By illuminating an object or scene with coherent light having a shaped illumination pattern, the receiver can be a simple detector array with no imaging optics, detecting the speckle intensity pattern reflected from the object; an image of the object can be reconstructed by a phase retrieval algorithm.

  17. Extraction of Urban Trees from Integrated Airborne Based Digital Image and LIDAR Point Cloud Datasets - Initial Results

    NASA Astrophysics Data System (ADS)

    Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

    2016-10-01

    Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.

  18. HERschel Inventory of The Agents of Galaxy Evolution (HERITAGE) in the Magellanic Clouds: SPIRE and PACS images of a Large Magellanic Cloud Strip

    NASA Astrophysics Data System (ADS)

    Meixner, Margaret

    As part of the science demonstration program for HERITAGE, we mapped a central strip across the entire Large Magellanic Cloud's (LMC's) HI disk in the parallel mode of SPIRE, with bands of 250, 350 and 500 microns, and PACS, with bands of 100 and 160 microns. The emission in these bands is dominated by the dust emission from the interstellar medium. The SPIRE bands in particular provide the first view into the coldest possible dust in the interstellar medium of the LMC. This paper shows the observations of the entire LMC strip in all 5 bands and the comparison of the Herschel band emissions with notable tracers of ISM gas: HI 21 cm, CO J=1-0, and H-alpha. We present a dust temperature, opacity and dust mass map for these regions and their global comparison to the gas tracers. We then compare how the dust relates to the major stellar components in the galaxy especially the massive stars at all stages from formation to their explosive death. This paper will briefly describe how the SDP-strip provides a confirmation that HERITAGE will achieve its over-arching science goals when the surveys are complete. Herschel images will provide key insights into the life cycle of galaxies because the far-infrared and submm emission from dust grains is an effective tracer of the cold-est ISM dust, the most deeply embedded young stellar objects (YSOs), and the dust ejected over the lifetime of massive stars. The ISM dust map will directly measure dust on a scale size of individual regions ( 10pc, 5-20 K) with column densities ¿0.85x1021 and > 6x1021 H - atomscm-2 f ortheLM CandSM C, respectively.Dustemissionperbeamwillbedetectedf orregionswith > 0.1M sunat 25K, > 5M sunof 10K.HERIT AGEwillcomplete1)thecensusof massiveY SOsdownto > 4M sunClass0sourcesand2)theinventoryof dustinjectedintotheISM bymassiveevolvedstarsandsupernova

  19. 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)

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

    2004-01-01

    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.

  20. Cloud Arcs in the Western Pacific

    NASA Technical Reports Server (NTRS)

    2002-01-01

    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

  1. Staining Pattern Classification of Antinuclear Autoantibodies Based on Block Segmentation in Indirect Immunofluorescence Images

    PubMed Central

    Li, Jiaqian; Tseng, Kuo-Kun; Hsieh, Zu Yi; Yang, Ching Wen; Huang, Huang-Nan

    2014-01-01

    Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image) with a total accuracy of about 94.62%. PMID:25474260

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

    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.

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

    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 are 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.

  4. Artificial cloud test confirms volcanic ash detection using infrared spectral imaging

    PubMed Central

    Prata, A. J.; Dezitter, F.; Davies, I.; Weber, K.; Birnfeld, M.; Moriano, D.; Bernardo, C.; Vogel, A.; Prata, G. S.; Mather, T. A.; Thomas, H. E.; Cammas, J.; Weber, M.

    2016-01-01

    Airborne volcanic ash particles are a known hazard to aviation. Currently, there are no means available to detect ash in flight as the particles are too fine (radii < 30 μm) for on-board radar detection and, even in good visibility, ash clouds are difficult or impossible to detect by eye. The economic cost and societal impact of the April/May 2010 Icelandic eruption of Eyjafjallajökull generated renewed interest in finding ways to identify airborne volcanic ash in order to keep airspace open and avoid aircraft groundings. We have designed and built a bi-spectral, fast-sampling, uncooled infrared camera device (AVOID) to examine its ability to detect volcanic ash from commercial jet aircraft at distances of more than 50 km ahead. Here we report results of an experiment conducted over the Atlantic Ocean, off the coast of France, confirming the ability of the device to detect and quantify volcanic ash in an artificial ash cloud created by dispersal of volcanic ash from a second aircraft. A third aircraft was used to measure the ash in situ using optical particle counters. The cloud was composed of very fine ash (mean radii ~10 μm) collected from Iceland immediately after the Eyjafjallajökull eruption and had a vertical thickness of ~200 m, a width of ~2 km and length of between 2 and 12 km. Concentrations of ~200 μg m−3 were identified by AVOID at distances from ~20 km to ~70 km. For the first time, airborne remote detection of volcanic ash has been successfully demonstrated from a long-range flight test aircraft. PMID:27156701

  5. Artificial cloud test confirms volcanic ash detection using infrared spectral imaging.

    PubMed

    Prata, A J; Dezitter, F; Davies, I; Weber, K; Birnfeld, M; Moriano, D; Bernardo, C; Vogel, A; Prata, G S; Mather, T A; Thomas, H E; Cammas, J; Weber, M

    2016-05-09

    Airborne volcanic ash particles are a known hazard to aviation. Currently, there are no means available to detect ash in flight as the particles are too fine (radii < 30 μm) for on-board radar detection and, even in good visibility, ash clouds are difficult or impossible to detect by eye. The economic cost and societal impact of the April/May 2010 Icelandic eruption of Eyjafjallajökull generated renewed interest in finding ways to identify airborne volcanic ash in order to keep airspace open and avoid aircraft groundings. We have designed and built a bi-spectral, fast-sampling, uncooled infrared camera device (AVOID) to examine its ability to detect volcanic ash from commercial jet aircraft at distances of more than 50 km ahead. Here we report results of an experiment conducted over the Atlantic Ocean, off the coast of France, confirming the ability of the device to detect and quantify volcanic ash in an artificial ash cloud created by dispersal of volcanic ash from a second aircraft. A third aircraft was used to measure the ash in situ using optical particle counters. The cloud was composed of very fine ash (mean radii ~10 μm) collected from Iceland immediately after the Eyjafjallajökull eruption and had a vertical thickness of ~200 m, a width of ~2 km and length of between 2 and 12 km. Concentrations of ~200 μg m(-3) were identified by AVOID at distances from ~20 km to ~70 km. For the first time, airborne remote detection of volcanic ash has been successfully demonstrated from a long-range flight test aircraft.

  6. Artificial cloud test confirms volcanic ash detection using infrared spectral imaging

    NASA Astrophysics Data System (ADS)

    Prata, A. J.; Dezitter, F.; Davies, I.; Weber, K.; Birnfeld, M.; Moriano, D.; Bernardo, C.; Vogel, A.; Prata, G. S.; Mather, T. A.; Thomas, H. E.; Cammas, J.; Weber, M.

    2016-05-01

    Airborne volcanic ash particles are a known hazard to aviation. Currently, there are no means available to detect ash in flight as the particles are too fine (radii < 30 μm) for on-board radar detection and, even in good visibility, ash clouds are difficult or impossible to detect by eye. The economic cost and societal impact of the April/May 2010 Icelandic eruption of Eyjafjallajökull generated renewed interest in finding ways to identify airborne volcanic ash in order to keep airspace open and avoid aircraft groundings. We have designed and built a bi-spectral, fast-sampling, uncooled infrared camera device (AVOID) to examine its ability to detect volcanic ash from commercial jet aircraft at distances of more than 50 km ahead. Here we report results of an experiment conducted over the Atlantic Ocean, off the coast of France, confirming the ability of the device to detect and quantify volcanic ash in an artificial ash cloud created by dispersal of volcanic ash from a second aircraft. A third aircraft was used to measure the ash in situ using optical particle counters. The cloud was composed of very fine ash (mean radii ~10 μm) collected from Iceland immediately after the Eyjafjallajökull eruption and had a vertical thickness of ~200 m, a width of ~2 km and length of between 2 and 12 km. Concentrations of ~200 μg m‑3 were identified by AVOID at distances from ~20 km to ~70 km. For the first time, airborne remote detection of volcanic ash has been successfully demonstrated from a long-range flight test aircraft.

  7. Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

    PubMed

    Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

    2016-12-16

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

  8. Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

    PubMed Central

    Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

    2016-01-01

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

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

    PubMed

    Pham, Tuan D

    2014-01-01

    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.

  10. Spatial Uncertainty Modeling of Fuzzy Information in Images for Pattern Classification

    PubMed Central

    Pham, Tuan D.

    2014-01-01

    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

  11. A Novel Strategy for Quantum Image Steganography Based on Moiré Pattern

    NASA Astrophysics Data System (ADS)

    Jiang, Nan; Wang, Luo

    2015-03-01

    Image steganography technique is widely used to realize the secrecy transmission. Although its strategies on classical computers have been extensively researched, there are few studies on such strategies on quantum computers. Therefore, in this paper, a novel, secure and keyless steganography approach for images on quantum computers is proposed based on Moiré pattern. Algorithms based on the Moiré pattern are proposed for binary image embedding and extraction. Based on the novel enhanced quantum representation of digital images (NEQR), recursive and progressively layered quantum circuits for embedding and extraction operations are designed. In the end, experiments are done to verify the validity and robustness of proposed methods, which confirms that the approach in this paper is effective in quantum image steganography strategy.

  12. Bayer patterned high dynamic range image reconstruction using adaptive weighting function

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    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.

  13. Crater Clouds

    NASA Technical Reports Server (NTRS)

    2006-01-01

    [figure removed for brevity, see original site] Context image for PIA06085 Crater Clouds

    The crater on the right side of this image is affecting the local wind regime. Note the bright line of clouds streaming off the north rim of the crater.

    Image information: VIS instrument. Latitude -78.8N, Longitude 320.0E. 17 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

  14. Reliable Averages and Risky Extremes - Analysis of spatio-temporal variability in solar irradiance and persistent cloud cover patterns over Switzerland

    NASA Astrophysics Data System (ADS)

    Kahl, Annelen; Nguyen, Viet-Anh; Sarrasin, Karine; Lehning, Michael

    2016-04-01

    With the perspective of Switzerland's phase-out from nuclear energy, solar energy potential may take a leading role for the country's future in renewable energy. Unlike nuclear power stations, photovoltaic (PV) production is prone to intermittency as it depends on the immediate solar irradiance, which fluctuates in space and time. If a large percentage of Switzerland's electricity was to be derived from solar radiation, stochastic fluctuations pose a risk to the robust supply and healthy function of the electricity network. For most efficient PV planning and siting, it is hence imperative to understand and quantify this variability in solar radiation, in order to anticipate average production as well as worst-case scenarios. Based on 12 years of satellite derived, spatially distributed data of daily average surface incoming shortwave radiation (SIS) this work analyses standard statistics, spatial correlation patterns and extreme conditions of cloud cover over Switzerland. Having compared different irradiance products, we decided to use the SIS product captured on the Meteosat Second Generation satellites, because it provides the most reliable snow/cloud discrimination, which is essential for spatial analysis over alpine terrain. Particularly in regions with high elevation differences, correlation between cloud cover and elevation undergo an annual cycle. In winter more clouds are found in the valleys, while in summer convective clouds dominate at higher elevations. The highest average irradiance values occur in the southern parts of the country, and make the cantons of Vallais, Tessin and Grison ideal candidate locations for PV installations. Simultaneously the Tessin shows a higher risk of periods with long lasting cloud cover, which would discourage from relying too much on solar power in that area. However looking at the question of suitability by studying spatial and temporal correlations of extremes, we see that the Tessin appears to be comparably decoupled

  15. Martian Clouds

    NASA Technical Reports Server (NTRS)

    2004-01-01

    [figure removed for brevity, see original site]

    Released 28 June 2004 The atmosphere of Mars is a dynamic system. Water-ice clouds, fog, and hazes can make imaging the surface from space difficult. Dust storms can grow from local disturbances to global sizes, through which imaging is impossible. Seasonal temperature changes are the usual drivers in cloud and dust storm development and growth.

    Eons of atmospheric dust storm activity has left its mark on the surface of Mars. Dust carried aloft by the wind has settled out on every available surface; sand dunes have been created and moved by centuries of wind; and the effect of continual sand-blasting has modified many regions of Mars, creating yardangs and other unusual surface forms.

    This image was acquired during early spring near the North Pole. The linear 'ripples' are transparent water-ice clouds. This linear form is typical for polar clouds. The black regions on the margins of this image are areas of saturation caused by the build up of scattered light from the bright polar material during the long image exposure.

    Image information: VIS instrument. Latitude 68.1, Longitude 147.9 East (212.1 West). 38 meter/pixel resolution.

    Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

    NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS

  16. Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

    PubMed

    Liu, Dong; Wang, Shengsheng; Huang, Dezhi; Deng, Gang; Zeng, Fantao; Chen, Huiling

    2016-05-01

    Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches.

  17. Integration of Point Clouds from Terrestrial Laser Scanning and Image-Based Matching for Generating High-Resolution Orthoimages

    NASA Astrophysics Data System (ADS)

    Salach, A.; Markiewicza, J. S.; Zawieska, D.

    2016-06-01

    An orthoimage is one of the basic photogrammetric products used for architectural documentation of historical objects; recently, it has become a standard in such work. Considering the increasing popularity of photogrammetric techniques applied in the cultural heritage domain, this research examines the two most popular measuring technologies: terrestrial laser scanning, and automatic processing of digital photographs. The basic objective of the performed works presented in this paper was to optimize the quality of generated high-resolution orthoimages using integration of data acquired by a Z+F 5006 terrestrial laser scanner and a Canon EOS 5D Mark II digital camera. The subject was one of the walls of the "Blue Chamber" of the Museum of King Jan III's Palace at Wilanów (Warsaw, Poland). The high-resolution images resulting from integration of the point clouds acquired by the different methods were analysed in detail with respect to geometric and radiometric correctness.

  18. Quantitative analysis of breast echotexture patterns in automated breast ultrasound images

    SciTech Connect

    Chang, Ruey-Feng; Hou, Yu-Ling; Lo, Chung-Ming; Huang, Chiun-Sheng; Chen, Jeon-Hor; Kim, Won Hwa; Chang, Jung Min; Bae, Min Sun; Moon, Woo Kyung

    2015-08-15

    Purpose: Breast tissue composition is considered to be associated with breast cancer risk. This study aimed to develop a computer-aided classification (CAC) system to automatically classify echotexture patterns as heterogeneous or homogeneous using automated breast ultrasound (ABUS) images. Methods: A CAC system was proposed that can recognize breast echotexture patterns in ABUS images. For each case, the echotexture pattern was assessed by two expert radiologists and classified as heterogeneous or homogeneous. After neutrosophic image transformation and fuzzy c-mean clusterings, the lower and upper boundaries of the fibroglandular tissues were defined. Then, the number of hypoechoic regions and histogram features were extracted from the fibroglandular tissues, and the support vector machine model with the leave-one-out cross-validation method was utilized as the classifier. The authors’ database included a total of 208 ABUS images of the breasts of 104 females. Results: The accuracies of the proposed system for the classification of heterogeneous and homogeneous echotexture patterns were 93.48% (43/46) and 92.59% (150/162), respectively, with an overall Az (area under the receiver operating characteristic curve) of 0.9786. The agreement between the radiologists and the proposed system was almost perfect, with a kappa value of 0.814. Conclusions: The use of ABUS and the proposed method can provide quantitative information on the echotexture patterns of the breast and can be used to evaluate whether breast echotexture patterns are associated with breast cancer risk in the future.

  19. Temporal pattern of acoustic imaging noise asymmetrically modulates activation in the auditory cortex.

    PubMed

    Ranaweera, Ruwan D; Kwon, Minseok; Hu, Shuowen; Tamer, Gregory G; Luh, Wen-Ming; Talavage, Thomas M

    2016-01-01

    This study investigated the hemisphere-specific effects of the temporal pattern of imaging related acoustic noise on auditory cortex activation. Hemodynamic responses (HDRs) to five temporal patterns of imaging noise corresponding to noise generated by unique combinations of imaging volume and effective repetition time (TR), were obtained using a stroboscopic event-related paradigm with extra-long (≥27.5 s) TR to minimize inter-acquisition effects. In addition to confirmation that fMRI responses in auditory cortex do not behave in a linear manner, temporal patterns of imaging noise were found to modulate both the shape and spatial extent of hemodynamic responses, with classically non-auditory areas exhibiting responses to longer duration noise conditions. Hemispheric analysis revealed the right primary auditory cortex to be more sensitive than the left to the presence of imaging related acoustic noise. Right primary auditory cortex responses were significantly larger during all the conditions. This asymmetry of response to imaging related acoustic noise could lead to different baseline activation levels during acquisition schemes using short TR, inducing an observed asymmetry in the responses to an intended acoustic stimulus through limitations of dynamic range, rather than due to differences in neuronal processing of the stimulus. These results emphasize the importance of accounting for the temporal pattern of the acoustic noise when comparing findings across different fMRI studies, especially those involving acoustic stimulation.

  20. Temporal pattern of acoustic imaging noise asymmetrically modulates activation in the auditory cortex

    PubMed Central

    Ranaweera, Ruwan D.; Kwon, Minseok; Hu, Shuowen; Tamer, Gregory G.; Luh, Wen-Ming; Talavage, Thomas M.

    2015-01-01

    This study investigated the hemisphere-specific effects of the temporal pattern of imaging related acoustic noise on auditory cortex activation. Hemodynamic responses (HDRs) to five temporal patterns of imaging noise corresponding to noise generated by unique combinations of imaging volume and effective repetition time (TR), were obtained using a stroboscopic event-related paradigm with extra-long (≥27.5s) TR to minimize inter-acquisition effects. In addition to confirmation that fMRI responses in auditory cortex do not behave in a linear manner, temporal patterns of imaging noise were found to modulate both the shape and spatial extent of hemodynamic responses, with classically non-auditory areas exhibiting responses to longer duration noise conditions. Hemispheric analysis revealed the right primary auditory cortex to be more sensitive than the left to the presence of imaging related acoustic noise. Right primary auditory cortex responses were significantly larger during all the conditions. This asymmetry of response to imaging related acoustic noise could lead to different baseline activation levels during acquisition schemes using short TR, inducing an observed asymmetry in the responses to an intended acoustic stimulus through limitations of dynamic range, rather than due to differences in neuronal processing of the stimulus. These results emphasize the importance of accounting for the temporal pattern of the acoustic noise when comparing findings across different fMRI studies, especially those involving acoustic stimulation. PMID:26519093

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

    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.

  2. Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

    NASA Technical Reports Server (NTRS)

    Bomarito, G. F.; Hochhalter, J. D.; Cannon, A. H.

    2016-01-01

    The accuracy and precision of digital image correlation (DIC) is a function of three primary ingredients: image acquisition, image analysis, and the subject of the image. Development of the first two (i.e. image acquisition techniques and image correlation algorithms) has led to widespread use of DIC; however, fewer developments have been focused on the third ingredient. Typically, subjects of DIC images are mechanical specimens with either a natural surface pattern or a pattern applied to the surface. Research in the area of DIC patterns has primarily been aimed at identifying which surface patterns are best suited for DIC, by comparing patterns to each other. Because the easiest and most widespread methods of applying patterns have a high degree of randomness associated with them (e.g., airbrush, spray paint, particle decoration, etc.), less effort has been spent on exact construction of ideal patterns. With the development of patterning techniques such as microstamping and lithography, patterns can be applied to a specimen pixel by pixel from a patterned image. In these cases, especially because the patterns are reused many times, an optimal pattern is sought such that error introduced into DIC from the pattern is minimized. DIC consists of tracking the motion of an array of nodes from a reference image to a deformed image. Every pixel in the images has an associated intensity (grayscale) value, with discretization depending on the bit depth of the image. Because individual pixel matching by intensity value yields a non-unique scale-dependent problem, subsets around each node are used for identification. A correlation criteria is used to find the best match of a particular subset of a reference image within a deformed image. The reader is referred to references for enumerations of typical correlation criteria. As illustrated by Schreier and Sutton and Lu and Cary systematic errors can be introduced by representing the underlying deformation with under

  3. Search Cloud

    MedlinePlus

    ... this page: https://medlineplus.gov/cloud.html Search Cloud To use the sharing features on this page, ... chest pa and lateral Share the MedlinePlus search cloud with your users by embedding our search cloud ...

  4. 3D scene reconstruction based on 3D laser point cloud combining UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Huiyun; Yan, Yangyang; Zhang, Xitong; Wu, Zhenzhen

    2016-03-01

    It is a big challenge capturing and modeling 3D information of the built environment. A number of techniques and technologies are now in use. These include GPS, and photogrammetric application and also remote sensing applications. The experiment uses multi-source data fusion technology for 3D scene reconstruction based on the principle of 3D laser scanning technology, which uses the laser point cloud data as the basis and Digital Ortho-photo Map as an auxiliary, uses 3DsMAX software as a basic tool for building three-dimensional scene reconstruction. The article includes data acquisition, data preprocessing, 3D scene construction. The results show that the 3D scene has better truthfulness, and the accuracy of the scene meet the need of 3D scene construction.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  6. A Local Index of Cloud Immersion in Tropical Forests Using Time-Lapse Photography

    NASA Astrophysics Data System (ADS)

    Bassiouni, M.; Scholl, M. A.

    2015-12-01

    Data on the frequency, duration and elevation of cloud immersion is essential to improve estimates of cloud water deposition in water budgets in cloud forests. Here, we present a methodology to detect local cloud immersion in remote tropical forests using time-lapse photography. A simple approach is developed to detect cloudy conditions in photographs within the canopy where image depth during clear conditions may be less than 10 meters and moving leaves and branches and changes in lighting are unpredictable. A primary innovation of this study is that cloudiness is determined from images without using a reference clear image and without minimal threshold value determination or human judgment for calibration. Five sites ranging from 600 to 1000 meters elevation along a ridge in the Luquillo Critical Zone Observatory, Puerto Rico were each equipped with a trail camera programmed to take an image every 30 minutes since March 2014. Images were classified using four selected cloud-sensitive image characteristics (SCICs) computed for small image regions: contrast, the coefficient of variation and the entropy of the luminance of each image pixel, and image colorfulness. K-means clustering provided reasonable results to discriminate cloudy from clear conditions. Preliminary results indicate that 79-94% (daytime) and 85-93% (nighttime) of validation images were classified accurately at one open and two closed canopy sites. The euclidian distances between SCICs vectors of images during cloudy conditions and the SCICs vector of the centroid of the cluster of clear images show potential to quantify cloud density in addition to immersion. The classification method will be applied to determine spatial and temporal patterns of cloud immersion in the study area. The presented approach offers promising applications to increase observations of low-lying clouds at remote mountain sites where standard instruments to measure visibility and cloud base may not be practical.

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

    PubMed

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

    2015-01-01

    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.

  8. Rotation, scale and translation invariant pattern recognition system for color images

    NASA Astrophysics Data System (ADS)

    Barajas-García, Carolina; Solorza-Calderón, Selene; Álvarez-Borrego, Josué

    2016-12-01

    This work presents a color image pattern recognition system invariant to rotation, scale and translation. The system works with three 1D signatures, one for each RGB color channel. The signatures are constructed based on Fourier transform, analytic Fourier-Mellin transform and Hilbert binary rings mask. According with the statistical theory of box-plots, the pattern recognition system has a confidence level at least of 95.4%.

  9. Free-form surface design method for nonaxial-symmetrical reflectors producing arbitrary image patterns

    NASA Astrophysics Data System (ADS)

    Tsai, Chung-Yu

    2016-07-01

    A free-form (FF) surface design method is proposed for a nonaxial-symmetrical projector system comprising an FF reflector and a light source. The profile of the reflector is designed using a nonaxial-symmetrical FF (NFF) surface construction method such that each incident ray is directed in such a way as to form a user-specified image pattern on the target region of the image plane. The light ray paths within the projection system are analyzed using an exact analytical model and a skew-ray tracing approach. The validity of the proposed NFF design method is demonstrated by means of ZEMAX simulations. It is shown that the image pattern formed on the target region of the image plane is in good agreement with that specified by the user. The NFF method is mathematically straightforward and easily implemented in computer code. As such, it provides a useful tool for the design and analysis stages of optical systems design.

  10. A new sparse Bayesian learning method for inverse synthetic aperture radar imaging via exploiting cluster patterns

    NASA Astrophysics Data System (ADS)

    Fang, Jun; Zhang, Lizao; Duan, Huiping; Huang, Lei; Li, Hongbin

    2016-05-01

    The application of sparse representation to SAR/ISAR imaging has attracted much attention over the past few years. This new class of sparse representation based imaging methods present a number of unique advantages over conventional range-Doppler methods, the basic idea behind these works is to formulate SAR/ISAR imaging as a sparse signal recovery problem. In this paper, we propose a new two-dimensional pattern-coupled sparse Bayesian learning(SBL) method to capture the underlying cluster patterns of the ISAR target images. Based on this model, an expectation-maximization (EM) algorithm is developed to infer the maximum a posterior (MAP) estimate of the hyperparameters, along with the posterior distribution of the sparse signal. Experimental results demonstrate that the proposed method is able to achieve a substantial performance improvement over existing algorithms, including the conventional SBL method.

  11. Speckle pattern of the images of objects exposed to monochromatic coherent terahertz radiation

    SciTech Connect

    Vinokurov, Nikolai A; Knyazev, Boris A; Kulipanov, Gennadii N; Dem'yanenko, M A; Esaev, D G; Chashchina, O I; Cherkasskii, Valerii S

    2009-05-31

    By using a free electron laser and a microbolometer array, real-time images are recorded for the first time in the terahertz range at the rate of up to 90 frames per second. In the case of diffusive illumination of objects by coherent monochromatic radiation, the images consist of speckles. The study of the statistical properties of speckle patterns shows that they are quite accurately described by the theory developed for speckles in the visible range. By averaging a set of images with the help of a rotating scatterer during the exposure time of a frame (20 ms) and by summing statistically independent speckle patterns of many frames, images of the acceptable quality are obtained. The possibilities of terahertz speckle photography and speckle interferometry are discussed. (terahertz radiation)

  12. Using a multiscale image processing method to characterize the periodic growth patterns on scallop shells.

    PubMed

    Xing, Qiang; Wei, Tengda; Chen, Zhihui; Wang, Yangfan; Lu, Yuan; Wang, Shi; Zhang, Lingling; Bao, Zhenmin

    2017-03-01

    The fine periodic growth patterns on shell surfaces have been widely used for studies in the ecology and evolution of scallops. Modern X-ray CT scanners and digital cameras can provide high-resolution image data that contain abundant information such as the shell formation rate, ontogenetic age, and life span of shellfish organisms. We introduced a novel multiscale image processing method based on matched filters with Gaussian kernels and partial differential equation (PDE) multiscale hierarchical decomposition to segment the small tubular and periodic structures in scallop shell images. The periodic patterns of structures (consisting of bifurcation points, crossover points of the rings and ribs, and the connected lines) could be found by our Space-based Depth-First Search (SDFS) algorithm. We created a MATLAB package to implement our method of periodic pattern extraction and pattern matching on the CT and digital scallop images available in this study. The results confirmed the hypothesis that the shell cyclic structure patterns encompass genetically specific information that can be used as an effective invariable biomarker for biological individual recognition. The package is available with a quick-start guide and includes three examples: http://mgb.ouc.edu.cn/novegene/html/code.php.

  13. Image reversal for direct electron beam patterning of protein coated surfaces.

    PubMed

    Pesen, Devrim; Erlandsson, Anna; Ulfendahl, Mats; Haviland, David B

    2007-11-01

    Electron beam lithography (EBL) is used to create surfaces with protein patterns, which are characterized by immunofluorescence and atomic force microscopies. Both negative and positive image processes are realized by electron beam irradiation of proteins absorbed on a silicon surface, where image reversal is achieved by selectively binding a second species of protein to the electron beam exposed areas on the first protein layer. Biofunctionality at the cellular level was established by culturing cortical cells on patterned lines of fibronectin adsorbed on a bovine serum albumin background for 7 days in culture.

  14. Using aberration test patterns to optimize the performance of EUV aerial imaging microscopes

    SciTech Connect

    Mochi, Iacopo; Goldberg, Kenneth A.; Miyakawa, Ryan; Naulleau, Patrick; Han, Hak-Seung; Huh, Sungmin

    2009-06-16

    The SEMATECH Berkeley Actinic Inspection Tool (AIT) is a prototype EUV-wavelength zoneplate microscope that provides high quality aerial image measurements of EUV reticles. To simplify and improve the alignment procedure we have created and tested arrays of aberration-sensitive patterns on EUV reticles and we have compared their images collected with the AIT to the expected shapes obtained by simulating the theoretical wavefront of the system. We obtained a consistent measure of coma and astigmatism in the center of the field of view using two different patterns, revealing a misalignment condition in the optics.

  15. Jupiter's High-Altitude Clouds

    NASA Technical Reports Server (NTRS)

    2007-01-01

    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

  16. Searching for patterns in remote sensing image databases using neural networks

    NASA Technical Reports Server (NTRS)

    Paola, Justin D.; Schowengerdt, Robert A.

    1995-01-01

    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.

  17. Waves on White: Ice or Clouds?

    NASA Technical Reports Server (NTRS)

    2005-01-01

    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

  18. Imaging spectroscopy diagnosis of internal electron temperature and density distributions of plasma cloud surrounding hydrogen pellet in the Large Helical Device

    SciTech Connect

    Motojima, G.; Sakamoto, R.; Goto, M.; Matsuyama, A.; Yamada, H.; Mishra, J. S.

    2012-09-15

    To investigate the behavior of hydrogen pellet ablation, a novel method of high-speed imaging spectroscopy has been used in the Large Helical Device (LHD) for identifying the internal distribution of the electron density and temperature of the plasma cloud surrounding the pellet. This spectroscopic system consists of a five-branch fiberscope and a fast camera, with each objective lens having a different narrow-band optical filter for the hydrogen Balmer lines and the background continuum radiation. The electron density and temperature in the plasma cloud are obtained, with a spatial resolution of about 6 mm and a temporal resolution of 5 Multiplication-Sign 10{sup -5} s, from the intensity ratio measured through these filters. To verify the imaging, the average electron density and temperature also have been measured from the total emission by using a photodiode, showing that both density and temperature increase with time during the pellet ablation. The electron density distribution ranging from 10{sup 22} to 10{sup 24} m{sup -3} and the temperature distribution around 1 eV have been observed via imaging. The electron density and temperature of a 0.1 m plasma cloud are distributed along the magnetic field lines and a significant electron pressure forms in the plasma cloud for typical experimental conditions of the LHD.

  19. Imaging spectroscopy diagnosis of internal electron temperature and density distributions of plasma cloud surrounding hydrogen pellet in the Large Helical Device.

    PubMed

    Motojima, G; Sakamoto, R; Goto, M; Matsuyama, A; Mishra, J S; Yamada, H

    2012-09-01

    To investigate the behavior of hydrogen pellet ablation, a novel method of high-speed imaging spectroscopy has been used in the Large Helical Device (LHD) for identifying the internal distribution of the electron density and temperature of the plasma cloud surrounding the pellet. This spectroscopic system consists of a five-branch fiberscope and a fast camera, with each objective lens having a different narrow-band optical filter for the hydrogen Balmer lines and the background continuum radiation. The electron density and temperature in the plasma cloud are obtained, with a spatial resolution of about 6 mm and a temporal resolution of 5 × 10(-5) s, from the intensity ratio measured through these filters. To verify the imaging, the average electron density and temperature also have been measured from the total emission by using a photodiode, showing that both density and temperature increase with time during the pellet ablation. The electron density distribution ranging from 10(22) to 10(24) m(-3) and the temperature distribution around 1 eV have been observed via imaging. The electron density and temperature of a 0.1 m plasma cloud are distributed along the magnetic field lines and a significant electron pressure forms in the plasma cloud for typical experimental conditions of the LHD.

  20. A CERES-like Cloud Property Climatology Using AVHRR Data

    NASA Astrophysics Data System (ADS)

    Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

    2015-12-01

    Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

  1. Computed Tomography Image Origin Identification based on Original Sensor Pattern Noise and 3D Image Reconstruction Algorithm Footprints.

    PubMed

    Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

    2016-06-08

    In this paper, we focus on the "blind" identification of the Computed Tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-Scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT-Scanner based on an Original Sensor Pattern Noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its 3D image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train an SVM based classifier so as to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-Scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than Sensor Pattern Noise (SPN) based strategy proposed for general public camera devices.

  2. Speckle imaging of Titan at 2 microns: surface albedo, haze optical depth, and tropospheric clouds 1996-1998

    NASA Astrophysics Data System (ADS)

    Gibbard, S. G.; Macintosh, B.; Gavel, D.; Max, C. E.; de Pater, I.; Roe, H. G.; Ghez, A. M.; Young, E. F.; McKay, C. P.

    2004-06-01

    We present results from 14 nights of observations of Titan in 1996-1998 using near-infrared (centered at 2.1 microns) speckle imaging at the 10-meter W.M. Keck Telescope. The observations have a spatial resolution of 0.06 arcseconds. We detect bright clouds on three days in October 1998, with a brightness about 0.5% of the brightness of Titan. Using a 16-stream radiative transfer model (DISORT) to model the central equatorial longitude of each image, we construct a suite of surface albedo models parameterized by the optical depth of Titan's hydrocarbon haze layer. From this we conclude that Titan's equatorial surface albedo has plausible values in the range of 0-0.20. Titan's minimum haze optical depth cannot be constrained from this modeling, but an upper limit of 0.3 at this wavelength range is found. More accurate determination of Titan's surface albedo and haze optical depth, especially at higher latitudes, will require a model that fully considers the 3-dimensional nature of Titan's atmosphere.

  3. Imaging of four planetary nebulae in the Magellanic Clouds using the Hubble Space Telescope Faint Object Camera

    NASA Technical Reports Server (NTRS)

    Blades, J. C.; Barlow, M. J.; Albrecht, R.; Barbieri, C.; Boksenberg, A.; Crane, P.; Deharveng, J. M.; Disney, M. J.; Jakobsen, P.; Kamperman, T. M.

    1992-01-01

    Using the Faint Object Camera on-board the Hubble Space Telescope, we have obtained images of four planetary nebulae (PNe) in the Magellanic Clouds, namely N2 and N5 in the SMC and N66 and N201 in the LMC. Each nebula was imaged through two narrow-band filters isolating forbidden O III 5007 and H-beta, for a nominal exposure time of 1000 s in each filter. In forbidden O III, SMC N5 shows a circular ring structure, with a peak-to-peak diameter of 0.26 arcsec and a FWHM of 0.35 arcsec while SMC N2 shows an elliptical ring structure with a peak-to-peak diameter of 0.26 x 0.21. The expansion ages corresponding to the observed structures in SMC N2 and N5 are of the order of 3000 yr. LMC N201 is very compact, with a FWHM of 0.2 arcsec in H-beta. The Type I PN LMC N66 is a multipolar nebula, with the brightest part having an extent of about 2 arcsec and with fainter structures extending over 4 arcsec.

  4. Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

    PubMed Central

    Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M.; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V.; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L.; Bilello, Michel; O'Rourke, Donald M.; Davatzikos, Christos

    2016-01-01

    Background MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). Methods One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Results Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. Conclusions By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood–brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. PMID:26188015

  5. Fabrication and optimization of micro-scale speckle patterns for digital image correlation

    NASA Astrophysics Data System (ADS)

    Zhu, Jianguo; Yan, Gaoshen; He, Guanglong; Chen, Lei

    2016-01-01

    Experimental investigations are performed on the fabrication and optimization of micro-scale speckle patterns formed by spinning an epoxy resin and powder for digital image correlation measurements. New factors influencing the fabrication process, including the ambient temperature, centrifugal velocity, and solidifying time, are carefully analyzed and are evaluated in terms of the average gray gradient and particle agglomeration, and the optimal micro-scale speckle pattern is obtained with the proposed parameters in the fabrication process. Additionally, the micro-scale speckle pattern is experimentally verified by performing prescribed rigid-body translation tests, and the relative errors are approximately 1.5%. Finally, the micro-scale speckle patterns are transferred to tensile specimens of aluminum and a polymer material with a V notch. The measurement results are consistent with the theoretical predictions, and this agreement demonstrates the feasibility and accuracy of the micro-scale speckle patterns.

  6. Constraining mass-diameter relations from hydrometeor images and cloud radar reflectivities in tropical continental and oceanic convective anvils

    NASA Astrophysics Data System (ADS)

    Fontaine, E.; Schwarzenboeck, A.; Delanoë, J.; Wobrock, W.; Leroy, D.; Dupuy, R.; Protat, A.

    2014-01-01

    In this study the density of hydrometeors in tropical clouds is derived from a combined analysis of particle images from 2-D-array probes and associated reflectivities measured with a Doppler cloud radar on the same research aircraft. The mass-diameter m(D) relationship is expressed as a power law with two unknown coefficients (pre-factor, exponent) that need to be constrained from complementary information on hydrometeors, where absolute ice density measurement methods do not apply. Here, at first an extended theoretical study of numerous hydrometeor shapes simulated in 3-D and arbitrarily projected on a 2-D plane allowed to constrain the temporal evolution of the exponent of the mass-diameter relationship with that of the exponent of the surface-diameter relationship that is measured by the 2-D-array probes. The pre-factor is then constrained from theoretical simulations of the radar reflectivities matching the measured reflectivities along the aircraft trajectory. The study has been performed as part of the Megha-Tropiques satellite project, where two types of mesoscale convective systems (MCS) have been investigated: (i) above the African Continent and (ii) above the Indian Ocean. In general, both mass-diameter coefficients (pre-factor and exponent) decrease with decreasing temperature, the decrease is more pronounced for oceanic MCS. The condensed water contents (CWC) calculated from particle size distributions (PSD) and m(D) also decrease with altitude while the concentrations of the hydrometeors increase with altitude. The calculated values of CWC are largest for continental MCS.

  7. Photoacoustic image patterns of breast carcinoma and comparisons with Magnetic Resonance Imaging and vascular stained histopathology

    NASA Astrophysics Data System (ADS)

    Heijblom, M.; Piras, D.; Brinkhuis, M.; van Hespen, J. C. G.; van den Engh, F. M.; van der Schaaf, M.; Klaase, J. M.; van Leeuwen, T. G.; Steenbergen, W.; Manohar, S.

    2015-07-01

    Photoacoustic (optoacoustic) imaging can visualize vasculature deep in tissue using the high contrast of hemoglobin to light, with the high-resolution possible with ultrasound detection. Since angiogenesis, one of the hallmarks of cancer, leads to increased vascularity, photoacoustics holds promise in imaging breast cancer as shown in proof-of-principle studies. Here for the first time, we investigate if there are specific photoacoustic appearances of breast malignancies which can be related to the tumor vascularity, using an upgraded research imaging system, the Twente Photoacoustic Mammoscope. In addition to comparisons with x-ray and ultrasound images, in subsets of cases the photoacoustic images were compared with MR images, and with vascular staining in histopathology. We were able to identify lesions in suspect breasts at the expected locations in 28 of 29 cases. We discovered generally three types of photoacoustic appearances reminiscent of contrast enhancement types reported in MR imaging of breast malignancies, and first insights were gained into the relationship with tumor vascularity.

  8. Photoacoustic image patterns of breast carcinoma and comparisons with Magnetic Resonance Imaging and vascular stained histopathology.

    PubMed

    Heijblom, M; Piras, D; Brinkhuis, M; van Hespen, J C G; van den Engh, F M; van der Schaaf, M; Klaase, J M; van Leeuwen, T G; Steenbergen, W; Manohar, S

    2015-07-10

    Photoacoustic (optoacoustic) imaging can visualize vasculature deep in tissue using the high contrast of hemoglobin to light, with the high-resolution possible with ultrasound detection. Since angiogenesis, one of the hallmarks of cancer, leads to increased vascularity, photoacoustics holds promise in imaging breast cancer as shown in proof-of-principle studies. Here for the first time, we investigate if there are specific photoacoustic appearances of breast malignancies which can be related to the tumor vascularity, using an upgraded research imaging system, the Twente Photoacoustic Mammoscope. In addition to comparisons with x-ray and ultrasound images, in subsets of cases the photoacoustic images were compared with MR images, and with vascular staining in histopathology. We were able to identify lesions in suspect breasts at the expected locations in 28 of 29 cases. We discovered generally three types of photoacoustic appearances reminiscent of contrast enhancement types reported in MR imaging of breast malignancies, and first insights were gained into the relationship with tumor vascularity.

  9. Photoacoustic image patterns of breast carcinoma and comparisons with Magnetic Resonance Imaging and vascular stained histopathology

    PubMed Central

    Heijblom, M.; Piras, D.; Brinkhuis, M.; van Hespen, J. C. G.; van den Engh, F. M.; van der Schaaf, M.; Klaase, J. M.; van Leeuwen, T. G.; Steenbergen, W.; Manohar, S.

    2015-01-01

    Photoacoustic (optoacoustic) imaging can visualize vasculature deep in tissue using the high contrast of hemoglobin to light, with the high-resolution possible with ultrasound detection. Since angiogenesis, one of the hallmarks of cancer, leads to increased vascularity, photoacoustics holds promise in imaging breast cancer as shown in proof-of-principle studies. Here for the first time, we investigate if there are specific photoacoustic appearances of breast malignancies which can be related to the tumor vascularity, using an upgraded research imaging system, the Twente Photoacoustic Mammoscope. In addition to comparisons with x-ray and ultrasound images, in subsets of cases the photoacoustic images were compared with MR images, and with vascular staining in histopathology. We were able to identify lesions in suspect breasts at the expected locations in 28 of 29 cases. We discovered generally three types of photoacoustic appearances reminiscent of contrast enhancement types reported in MR imaging of breast malignancies, and first insights were gained into the relationship with tumor vascularity. PMID:26159440

  10. Image Data Mining for Pattern Classification and Visualization of Morphological Changes in Brain MR Images.

    PubMed

    Murakawa, Saki; Ikuta, Rie; Uchiyama, Yoshikazu; Shiraishi, Junji

    2016-02-01

    Hospital information systems (HISs) and picture archiving and communication systems (PACSs) are archiving large amounts of data (i.e., "big data") that are not being used. Therefore, many research projects in progress are trying to use "big data" for the development of early diagnosis, prediction of disease onset, and personalized therapies. In this study, we propose a new method for image data mining to identify regularities and abnormalities in the large image data sets. We used 70 archived magnetic resonance (MR) images that were acquired using three-dimensional magnetization-prepared rapid acquisition with gradient echo (3D MP-RAGE). These images were obtained from the Alzheimer's disease neuroimaging initiative (ADNI) database. For anatomical standardization of the data, we used the statistical parametric mapping (SPM) software. Using a similarity matrix based on cross-correlation coefficients (CCs) calculated from an anatomical region and a hierarchical clustering technique, we classified all the abnormal cases into five groups. The Z score map identified the difference between a standard normal brain and each of those from the Alzheimer's groups. In addition, the scatter plot obtained from two similarity matrixes visualized the regularities and abnormalities in the image data sets. Image features identified using our method could be useful for understanding of image findings associated with Alzheimer's disease.

  11. Classification of skin cancer images using local binary pattern and SVM classifier

    NASA Astrophysics Data System (ADS)

    Adjed, Faouzi; Faye, Ibrahima; Ababsa, Fakhreddine; Gardezi, Syed Jamal; Dass, Sarat Chandra

    2016-11-01

    In this paper, a classification method for melanoma and non-melanoma skin cancer images has been presented using the local binary patterns (LBP). The LBP computes the local texture information from the skin cancer images, which is later used to compute some statistical features that have capability to discriminate the melanoma and non-melanoma skin tissues. Support vector machine (SVM) is applied on the feature matrix for classification into two skin image classes (malignant and benign). The method achieves good classification accuracy of 76.1% with sensitivity of 75.6% and specificity of 76.7%.

  12. Uv Imaging of Intermediate-Age Magellanic Cloud Clusters: Hot Stellar Populations in Composite Stellar Systems

    NASA Astrophysics Data System (ADS)

    Freedman, Wendy

    1994-01-01

    Hot stars were first recognized to be an important component of galactic spheroids with early vacuum ultraviolet observations of ellipticals and spiral bulges that were made with OAO. Now, 20 years later, we still do not have a full understanding of the VUV evolution of intermediate and old age stellar populations. Using the WFPC2, we therefore propose to undertake an ultraviolet survey of a sample of star clusters spanning a range in age in the Large Magellanic Cloud. The objective of this investigation is to determine the nature of the hot stellar components in rich, intermediate-to-old age LMC clusters. Ground-based optical/IR studies suggest the presence of short-lived hot horizontal branch and post-asymptotic giant branch stars in these clusters but detailed characterizations of the stars require the ultraviolet capability of HST. In this effort we will be aided by the absence of red leaks in the WFPC2 Woods filter and very high angular resolution of the HST. Although old star clusters in the Galaxy and M31 are, and will be, the subjects of intense investigation by HST, OUR SURVEY WILL BE THE FIRST OF ITS KIND FOR POPULATIONS OF INTERMEDIATE AGE. Such systems are critical for interpreting the spectra and colors of high redshift galaxies, and will provide important support to these studies.

  13. ALFALFA and WSRT Imaging of Extended H I Features in the Leo Cloud of Galaxies

    NASA Astrophysics Data System (ADS)

    Leisman, Lukas; Haynes, Martha P.; Giovanelli, Riccardo; Józsa, Gyula; Adams, Elizabeth A. K.; Hess, Kelley M.

    2016-12-01

    We present Arecibo Legacy Fast ALFA (ALFALFA) H I observations of a well-studied region of the Leo Cloud, which includes the NGC 3227 group and the NGC 3190 group. We detect optically dark H I tails and plumes with extents potentially exceeding 600 kpc, well beyond the field of view of previous observations. These H I features contain ˜40 per cent of the total H I mass in the NGC 3227 group and ˜10 per cent of the NGC 3190 group. We also present Westerbork Synthesis Radio Telescope (WSRT) maps which show the complex morphology of the extended emission in the NGC 3227 group. We comment on previously proposed models of the interactions in these groups and the implications for the scale of group processing through interactions. Motivated by the extent of the H I plumes, we place the H I observations in the context of the larger loose group, demonstrating the need for future sensitive, wide field H I surveys to understand the role of group processing in galaxy evolution.

  14. A practical approach to optimizing the preparation of speckle patterns for digital-image correlation

    NASA Astrophysics Data System (ADS)

    Lionello, Giacomo; Cristofolini, Luca

    2014-10-01

    The quality of strain measurements by digital image correlation (DIC) strongly depends on the quality of the pattern on the specimen’s surface. An ideal pattern should be highly contrasted, stochastic, and isotropic. In addition, the speckle pattern should have an average size that exceeds the image pixel size by a factor of 3-5. (Smaller speckles cause poor contrast, and larger speckles cause poor spatial resolution.) Finally, the ideal pattern should have a limited scatter in terms of speckle sizes. The aims of this study were: (i) to define the ideal speckle size in relation to the specimen size and acquisition system; (ii) provide practical guidelines to identify the optimal settings of an airbrush gun, in order to produce a pattern that is as close as possible to the desired one while minimizing the scatter of speckle sizes. Patterns of different sizes were produced using two different airbrush guns with different settings of the four most influential factors (dilution, airflow setting, spraying distance, and air pressure). A full-factorial DOE strategy was implemented to explore the four factors at two levels each: 36 specimens were analyzed for each of the 16 combinations. The images were acquired using the digital cameras of a DIC system. The distribution of speckle sizes was analyzed to calculate the average speckle size and the standard deviation of the corresponding truncated Gaussian distribution. A mathematical model was built to enable prediction of the average speckle size in relation to the airbrush gun settings. We showed that it is possible to obtain a pattern with a highly controlled average and a limited scatter of speckle sizes, so as to match the ideal distribution of speckle sizes for DIC. Although the settings identified here apply only to the specific equipment being used, this method can be adapted to any airbrush to produce a desired speckle pattern.

  15. Spatiotemporal Mining of Time-Series Remote Sensing Images Based on Sequential Pattern Mining

    NASA Astrophysics Data System (ADS)

    Liu, H. C.; He, G. J.; Zhang, X. M.; Jiang, W.; Ling, S. G.

    2015-07-01

    With the continuous development of satellite techniques, it is now possible to acquire a regular series of images concerning a given geographical zone with both high accuracy and low cost. Research on how best to effectively process huge volumes of observational data obtained on different dates for a specific geographical zone, and to exploit the valuable information regarding land cover contained in these images has received increasing interest from the remote sensing community. In contrast to traditional land cover change measures using pair-wise comparisons that emphasize the compositional or configurational changes between dates, this research focuses on the analysis of the temporal sequence of land cover dynamics, which refers to the succession of land cover types for a given area over more than two observational periods. Using a time series of classified Landsat images, ranging from 2006 to 2011, a sequential pattern mining method was extended to this spatiotemporal context to extract sets of connected pixels sharing similar temporal evolutions. The resultant sequential patterns could be selected (or not) based on the range of support values. These selected patterns were used to explore the spatial compositions and temporal evolutions of land cover change within the study region. Experimental results showed that continuous patterns that represent consistent land cover over time appeared as quite homogeneous zones, which agreed with our domain knowledge. Discontinuous patterns that represent land cover change trajectories were dominated by the transition from vegetation to bare land, especially during 2009-2010. This approach quantified land cover changes in terms of the percentage area affected and mapped the spatial distribution of these changes. Sequential pattern mining has been used for string mining or itemset mining in transactions analysis. The expected novel significance of this study is the generalization of the application of the sequential pattern

  16. Imaging of subatomic electron cloud interactions: Effect of higher harmonics processing in noncontact atomic force microscopy

    NASA Astrophysics Data System (ADS)

    Alan Wright, C.; Solares, Santiago D.

    2012-04-01

    In a previous study of higher harmonics atomic force microscopy imaging of graphite using a tungsten tip [Hembacher et al., Science 305, 380 (2004)], the authors interpreted the observed subatomic features as the signature of tip apex electron bonding lobes. We explore here their higher harmonics processing and filtering methods. We do not find any imaging artifacts inherent to the filtering process, but we find that the harmonics averaging approach used is not appropriate due to non-uniform harmonics ratios across the surface. A promising alternative may be the individual mapping of the first two harmonics.

  17. Landsat 7 - First Cloud-free Image of Yellowstone National Park

    NASA Technical Reports Server (NTRS)

    2002-01-01

    This image of Yellowstone Lake, in the center of Yellowstone National Park, was taken by Landsat 7 on July 13, 1999. Bands 5 (1.65um),4 (.825um), and 2 (.565um) were used for red, green, and blue, respectively. Water appears blue/black, snow light blue, mature forest red/green, young forest pink, and grass and fields appear light green. Southwest of the lake is young forest that is growing in the wake of the widespread fires of 1988. For more information, see: Landsat 7 Fact Sheet Landsat 7 in Mission Control Image by Rich Irish, NASA GSFC

  18. Object-based algorithms and methods for quantifying urban growth pattern using sequential satellite images

    NASA Astrophysics Data System (ADS)

    Yu, Bailang; Liu, Hongxing; Gao, Yige; Wu, Jianping

    2008-08-01

    Previously, urban growth pattern is described and measured by the pixel-by-pixel comparison of satellite images. The geographic extent, patterns and types of urban growth are derived from satellite images separated in time. However, the pixel-by-pixel comparison approach suffers from several drawbacks. Firstly, slight error in image geo-reference can cause false detection of changes. Secondly, it's difficult to recognize and correct artifact changes induced by data noise and data processing errors. Thirdly, only limited information can be derived. In this paper, we present a new objectbased method to describe and quantify urban growth patterns. The different types of land cover are classified from sequential satellite images as urban objects. The geometric and shape attributes of objects and the spatial relationship between them are employed to identify the different types of urban growth pattern. The algorithms involved in the object-based method are implemented by using C++ programming language and the software user interface is developed by using ArcObjects and VB.Net. A simulated example is given to demonstrate the utility and effectiveness of this new method.

  19. Two-phase flow patterns characteristics analysis based on image and conductance sensors

    NASA Astrophysics Data System (ADS)

    Wang, Zhenya; Jin, Ningde; Wang, Chun; Wang, Jinxiang

    2008-10-01

    In order to study the temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern, the two-phase flow monitoring system composed of high-speed dynamic camera and Vertical Multi-Electrode Array conductance sensor (VMEA) was utilized to shoot dynamic images and acquire the conductance fluctuating signals of 5 typical vertical gas-liquid two-phase flow patterns in a 125mm i.d. upward pipe. Gray level co-occurrence matrix (GLCM) was used to extract four time-varying characteristic parameter indices which represented different flow image texture structures and also Lempel-Ziv complexity of them were calculated. Then the transition of flow structure and flow property we