scholarly journals High Definition Large Screen Image Representation using 250 M-pixel-19K Ultra-High-Resolution Camera

2021 ◽  
Vol 75 (2) ◽  
pp. 305-314
Author(s):  
Katsuhisa Ogawa ◽  
Kentaro Mori
Keyword(s):  
High Resolution ◽  
Image Representation ◽  
High Definition ◽  
Screen Image ◽  
Large Screen

scholarly journals High-resolution and high-definition anorectal manometry: rediscovering anorectal function

2018 ◽  
Vol 110 ◽  
Author(s):  
Constanza Ciriza de los Ríos ◽  
Miguel Mínguez ◽  
Jose Mariaí Remes-Troche ◽  
Gl�ria Lacima
Keyword(s):  
High Resolution ◽  
Anorectal Manometry ◽  
Anorectal Function ◽  
High Definition

Is there Diagnostic Gain or Loss with High Definition Versus High Resolution Anorectal Manometry

2017 ◽  
Vol 152 (5) ◽  
pp. S316 ◽  
Author(s):  
Xuelian Xiang ◽  
Dipesh H. Vasant ◽  
Mercedes Amieva-Balmori ◽  
Rachael Parr ◽  
Amol Sharma ◽  
...  
Keyword(s):  
High Resolution ◽  
Anorectal Manometry ◽  
High Definition

scholarly journals Super High Resolution Large Screen Dis play System

1998 ◽  
Vol 52 (7) ◽  
pp. 915-918
Author(s):  
Kenji Nakazawa ◽  
Kazutake Uehira ◽  
Shigenobu Sakai
Keyword(s):  
High Resolution ◽  
Large Screen

scholarly journals The Posterior Lumbar Epidural Space: Three-Dimensional Reconstruction of High-Resolution MRI: Real and Potential Epidural Spaces and Their Content In Vivo

Pain Medicine ◽  
2019 ◽  
Vol 20 (9) ◽  
pp. 1687-1696 ◽  
Author(s):  
André P Boezaart ◽  
Alberto Prats-Galino ◽  
Olga C Nin ◽  
Anna Carrera ◽  
José Barberán ◽  
...  
Keyword(s):  
High Resolution ◽  
Epidural Space ◽  
Three Dimensional ◽  
Magnetic Resonance Images ◽  
High Definition ◽  
3D Reconstructions ◽  
Inferior Margin ◽  
Fibrous Body ◽  
Dural Sac

Abstract Objective Our aim was to study the posterior lumbar epidural space with 3D reconstructions of magnetic resonance images (MRIs) and to compare and validate the findings with targeted anatomic microdissections. Design We performed 3D reconstructions of high-resolution MRIs from seven patients and normal-resolution MRIs commonly used in clinical practice from 196 other random patients. We then dissected and photographed the lumbar spine areas of four fresh cadavers. Results From the 3D reconstructions of the MRIs, we verified that the distribution of the posterior fat pad had an irregular shape that resembled a truncated pyramid. It spanned between the superior margin of the lamina of the caudad vertebra and beyond the inferior margin to almost halfway underneath the cephalad lamina of the cranial vertebra, and it was not longitudinally or circumferentially continuous. The 3D reconstructions of the high-definition MRI also consistently revealed a prelaminar fibrous body that was not seen in most of the usually used low-definition MRI reconstructions. Targeted microdissections confirmed the 3D reconstruction findings and also showed the prelaminar tissue body to be fibrous, crossing from side to side anterior to the cephalad half of each lamina, and spanning from the dural sac to the laminae. Conclusions Three-dimensional reconstructions and targeted microdissection revealed the unique appearance of posterior fat pads and a prelaminar fibrous body. The exact consistency, presence, prevalence with age, presence in other regions, and function of this body are unknown and require further research.

Next Generation High-Definition Geomagnetic Model for Wellbore Positioning, Incorporating New Crustal Magnetic Data

2021 ◽  
Author(s):  
Manoj Nair ◽  
Arnaud Chulliat ◽  
Adam Woods ◽  
Patrick Alken ◽  
Brian Meyer ◽  
...  
Keyword(s):  
Magnetic Field ◽  
High Resolution ◽  
Error Model ◽  
Magnetic Data ◽  
Magnetic Observatory ◽  
Magnetic Survey ◽  
High Definition ◽  
The Core ◽  
Ground Magnetic ◽  
The Magnetic Field

Abstract Magnetic wellbore positioning depends on an accurate representation of the Earth's magnetic field,where the borehole azimuth is inferred by comparing the magnetic field measured-whiledrilling (MWD) with a geomagnetic reference model. Therefore, model accuracy improvements reduce the position uncertainties. An improved high-resolution model describing the core, crustal and external components of the magnetic field is presented, and it is validated with anindependent set of measurements. Additionally, we benchmark it against other high-resolution geomagnetic models. The crustal part of the improved high-definition model is based on NOAA/NCEI's latest magnetic survey compilation "EMAG2v3" which includes over 50 millionnew observations in several parts of the world, including the Gulf of Mexico and Antarctica, and does not rely on any prior information from sea-floor geology, unlike earlier versions. The core field part of the model covers years 1900 through 2020 andis inferred from polar-orbiting satellite data as well as ground magnetic observatory data. The external field part is modelled to degree and order 1 for years 2000 through 2020. The new model has internal coefficients to spherical harmonic degree and order 790, resolving magnetic anomalies to approximately 51 km wavelength at the equator. In order to quantitatively assess its accuracy, the model was compared with independent shipborne, airborne and ground magnetic measurements. We find that the newmodel has comparable or smaller errors than the other models benchmarkedagainst it over the regions of comparisons. Additionally, we compare theimproved model against magnetic datacollected from MWD; the residual error lies well within the accepted industry error model, which may lead tofuture error model improvements.

Coastal Shoreline Extraction from Very High Resolution (VHR2) Satellite SAR Imagery

2020 ◽  
Author(s):  
Daithí Maguire ◽  
Eugene Farrell
Keyword(s):  
High Resolution ◽  
Incidence Angle ◽  
Speckle Noise ◽  
High Definition ◽  
Alos Palsar ◽  
Sar Imagery ◽  
Using Data ◽  
Study Sites ◽  
Very High ◽  
Selection Of

<p>Shoreline vectors are extracted from TerraSAR-X imagery based on the identification of peak backscatter intensity levels. The vectors are being catalogued and analysed to assess the accuracy/suitability of SAR imagery for identifying coastal erosion hotspots and for monitoring coastal change as input to forecasting models. The technique is being developed, tested and refined using data collected from three study sites on the west coast of Ireland (Brandon Bay; Clew Bay; Galway Bay).</p><p>The shoreline vectors are extracted from both archived and tasked TerraSAR-X imagery. The extracted shorelines are being validated using a combination of: 1) panchromatic and multispectral satellite imagery (VHR1 & VHR2), 2) panchromatic and RGB aerial imagery (VHR1), 3) LiDAR data and 4) repeat DGPS field survey data. In addition, these shoreline vectors are also being compared with equivalent extractions from other very high-resolution X-band SAR imagery (Cosmo-SkyMed) and high-resolution C-band and L-band SAR imagery (RADARSAT-2, ALOS PALSAR). The spatial accuracy of the extracted shorelines from tasked acquisitions will be further assessed using temporarily installed corner reflectors at a selection of the study sites.</p><p>SAR acquisition parameters (orbit pass direction, incidence angle, polarisation) and a selection of speckle noise reduction filters (e.g. Boxcar, Frost, Lee) were evaluated to determine the optimum combination for coastal sites with different physical characteristics.</p><p>Results are presented in high-definition video format using a combination of GIS, Earth browser and 3D visualisation platforms.</p>

scholarly journals Targeted Grassland Monitoring at Parcel Level Using Sentinels, Street-Level Images and Field Observations

2018 ◽  
Vol 10 (8) ◽  
pp. 1300 ◽  
Author(s):  
Raphaël d’Andrimont ◽  
Guido Lemoine ◽  
Marijn van der Velde
Keyword(s):  
High Resolution ◽  
Collection Efficiency ◽  
Ground Truth ◽  
Bare Soil ◽  
Agricultural Policies ◽  
High Definition ◽  
Street Level ◽  
In Situ Data ◽  
Crop Type ◽  
Efficiency And Effectiveness

The introduction of high-resolution Sentinels combined with the use of high-quality digital agricultural parcel registration systems is driving the move towards at-parcel agricultural monitoring. The European Union’s Common Agricultural Policy (CAP) has introduced the concept of CAP monitoring to help simplify the management and control of farmers’ parcel declarations for area support measures. This study proposes a proof of concept of this monitoring approach introducing and applying the concept of ‘markers’. Using Sentinel-1- and -2-derived (S1 and S2) markers, we evaluate parcels declared as grassland in the Gelderse Vallei in the Netherlands covering more than 15,000 parcels. The satellite markers—respectively based on crop-type deep learning classification using S1 backscattering and coherence data and on detecting bare soil with S2 during the growing season—aim to identify grassland-declared parcels for which (1) the marker suggests another crop type or (2) which appear to have been ploughed during the year. Subsequently, a field-survey was carried out in October 2017 to target the parcels identified and to build a relevant ground-truth sample of the area. For the latter purpose, we used a high-definition camera mounted on the roof of a car to continuously sample geo-tagged digital imagery, as well as an app-based approach to identify the targeted fields. Depending on which satellite-based marker or combination of markers is used, the number of parcels identified ranged from 2.57% (marked by both the S1 and S2 markers) to 17.12% of the total of 11,773 parcels declared as grassland. After confirming with the ground-truth, parcels flagged by the combined S1 and S2 marker were robustly detected as non-grassland parcels (F-score = 0.9). In addition, the study demonstrated that street-level imagery collection could improve collection efficiency by a factor seven compared to field visits (1411 parcels/day vs. 217 parcels/day) while keeping an overall accuracy of about 90% compared to the ground-truth. This proposed way of collecting in situ data is suitable for the training and validating of high resolution remote sensing approaches for agricultural monitoring. Timely country-wide wall-to-wall parcel-level monitoring and targeted in-season parcel surveying will increase the efficiency and effectiveness of monitoring and implementing agricultural policies.

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