Remote Non-invasive Stereoscopic Imaging of Blood Vessels: First In-vivo Results of a New Multispectral Contrast Enhancement Technology

We describe a contactless optical technique selectively enhancing superficial blood vessels below variously pigmented intact human skin by combining images in different spectral bands. Two CMOS-cameras, with apochromatic lenses and dual-band LED-arrays, simultaneously streamed Left (L) and Right (R) image data to a dual-processor PC. Both cameras captured color images within the visible range (VIS, 400–780 nm) and grey-scale images within the near infrared range (NIR, 910–920 nm) by sequentially switching between LED-array emission bands. Image-size-settings of 1280 × 1024 for VIS & 640 × 512 for NIR produced 12 cycles/s (1 cycle = 1 VIS L&R-pair + 1 NIR L&R-pair). Decreasing image-size-settings (640 × 512 for VIS and 320 × 256 for NIR) increased camera-speed to 25 cycles/s. Contrasts from below the tissue surface were algorithmically distinguished from surface shadows, reflections, etc. Thus blood vessels were selectively enhanced and back-projected into the stereoscopic VIS-color-image using either a 3D-display or conventional shutter glasses. As a first usability reconnaissance we applied this custom-built mobile stereoscopic camera for several clinical settings: • blood withdrawal; • vein inspection in dark skin; • vein detection through iodide; • varicose vein and nevi pigmentosum inspection. Our technique improves blood vessel visualization compared to the naked eye, and supports depth perception

The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops

2015 Oil Observing Tools: A Workshop Report

Since 2010, the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) have provided satellite-based pollution surveillance in United States waters to regulatory agencies such as the United States Coast Guard (USCG). These technologies provide agencies with useful information regarding possible oil discharges. Unfortunately, there has been confusion as to how to interpret the images collected by these satellites and other aerial platforms, which can generate misunderstandings during spill events. Remote sensor packages on aircraft and satellites have advantages and disadvantages vis-à-vis human observers, because they do not “see” features or surface oil the same way. In order to improve observation capabilities during oil spills, applicable technologies must be identified, and then evaluated with respect to their advantages and disadvantages for the incident. In addition, differences between sensors (e.g., visual, IR, multispectral sensors, radar) and platform packages (e.g., manned/unmanned aircraft, satellites) must be understood so that reasonable approaches can be made if applicable and then any data must be correctly interpreted for decision support. NOAA convened an Oil Observing Tools Workshop to focus on the above actions and identify training gaps for oil spill observers and remote sensing interpretation to improve future oil surveillance, observation, and mapping during spills. The Coastal Response Research Center (CRRC) assisted NOAA’s Office of Response and Restoration (ORR) with this effort. The workshop was held on October 20-22, 2015 at NOAA’s Gulf of Mexico Disaster Response Center in Mobile, AL. The expected outcome of the workshop was an improved understanding, and greater use of technology to map and assess oil slicks during actual spill events. Specific workshop objectives included: •Identify new developments in oil observing technologies useful for real-time (or near real-time) mapping of spilled oil during emergency events. •Identify merits and limitations of current technologies and their usefulness to emergency response mapping of oil and reliable prediction of oil surface transport and trajectory forecasts.Current technologies include: the traditional human aerial observer, unmanned aircraft surveillance systems, aircraft with specialized senor packages, and satellite earth observing systems. •Assess training needs for visual observation (human observers with cameras) and sensor technologies (including satellites) to build skills and enhance proper interpretation for decision support during actual events

Pulse Oxigraphy: And other new in-depth perspectives through the near infrared window

The aim of this thesis was to investigate the feasability of contactless imaging pulse oximetry (proposed term: pulse oxigraphy). The patent disclosed in chapter 2 claims that such pulse oxigraphy can be achieved with camera-derived photoplethysmographic pulse waves at three wavelengths, preferably being 660, 810 and 940nm. From the absorption curves of hemoglobin and oxyhemoglobin it can be easily derived that two of these wavelengths (660 and 940nm) contain oxygenation-related information, and they have proven to be useful for conventional pulse oximetry (in transmission- mode as well as in reflectance-mode). The additional third wavelength (810nm) lies at a so-called isobestic point where the absorption curves of hemoglobin and oxyhemoglobin intersect. Thus, images and/or plethysmographic pulse waves recorded at 810nm do not contain oxygenation-related information, which is useful for reference purposes when dealing with shadows, reflections, movement artifacts and variations in geometry. With regard to pulse oxigraphy the following results were obtained: In chapter 3 we proved that it is possible to derive photoplethysmographic pulse waves containing the heart rythm of a living person at all three required wavelengths from camera recordings collected at a distance of 72 cm. To investigate and validate the capabilities for pulse oxigraphy with this set up, direct measurements on volunteers were sub optimal, because of: Signal-to-noise issues, sequentially recorded heartbeats for oxygen saturation calculations, and lack of a method to induce prolonged stable and adjustable oxygen saturation levels

KNOWLEDGE AND DOCUMENTATION OF RENAISSANCE WORKS OF ART: THE REPLICA OF THE “ANNUNCIATION” BY BEATO ANGELICO

The Annunciation by Guido di Pietro from Mugello, known as Beato Angelico, is a wide tempera painting with some fine gold foil placed on a wooden support, today hosted at the Museum of the Basilica of Santa Maria delle Grazie, in San Giovanni Valdarno. On the occasion of the exhibition “Masaccio e Angelico. Dialogo sulla verità nella pittura”, the museum asked to the Department of Architecture at the University of Bologna to develop a digital high-resolution surrogate to favour deep investigations, to plan restoration and to simply tell the stories behind the artwork. Two tasks were accomplished: to let visitors discover the secrets in the painting and to let scholars study the artwork, to better understand the masterpiece. This paper introduces the outcomes of the research developed to digitize the Annunciation, following a dedicated pipeline developed to improve the fruition of its digital replica, originated from different input sources, and surrogating the user experience on the real object. This work presents a method for the 3D reconstruction of the surfaces based on different techniques for elements with different depth resolutions (i.e., the painting and the wooden frame) which combine photogrammetry and photometric stereo exploiting both procedures and pushing forward the boundaries of Gigapixel Imaging and photogrammetric-based 3D model representation

Seismotectonic, structural, volcanologic, and geomorphic study of New Zealand; indigenous forest assessment in New Zealand; mapping, land use, and environmental studies in New Zealand, volume 2

The author has identified the following significant results. Ship detection via LANDSAT MSS data was demonstrated. In addition, information on ship size, orientation, and movement was obtained. Band 7 was used for the initial detection followed by confirmation on other MSS bands. Under low turbidity, as experienced in open seas, the detection of ships 100 m long was verified and detection of ships down to 30 m length theorized. High turbidity and sea state inhibit ship detection by decreasing S/N ratios. The radiance effect from snow of local slope angles and orientation was also studied. Higher radiance values and even overloading in three bands were recorded for the sun-facing slope. Local hot spots from solar reflection appear at several locations along transect D-C in Six Mile Creek Basin during September 1976

Bayesian spatiotemporal modelling: An application to glacier satellite imagery

Glaciers hold 1.7% of the Earth's total water supply, but they contain 68.7% of its freshwater. Given the global warming trend, accurate and recent inventory is necessary to assess glacial changes over time. However, frequent cloud and debris cover often make it difficult to determine the glacier's exact edge. Multispectral Landsat 8 imagery along with data from the Global Land Ice Velocity Extraction (GoLIVE) project are combined to to create a Bayesian multivariate general additive model of the glaciers surrounding Mount Rainier, with Autoregressive Moving Average (ARMA) and Gaussian processes used to model the temporal and spatial autocorrelations. Using root mean square error and Watanabe-Akaike information criterion, all 42 combinations of ARMA models up to 4 total parameters and exponential, Matérn 1/2 and spherical covariance kernels were compared. The ARMA(3,1) processes with the exponential Gaussian process kernel was determined to be the best fit model. Gaussian mixture models, hierarchical clustering, hard and soft K-means clustering, and support vector machines are used to classify the posterior distribution. The hard K-means algorithm was the best classifier, and it accurately predicted 85.1% of the glaciers, compared to 68.8% from a univariate classification on the Red/SWIR band ratio