The Impact of Shadows on Partitioning of Radiometric Temperature to Canopy and Soil Temperature Based on the Contextual Two-Source Energy Balance Model (TSEB-2T)

Tests of the most recent version of the two-source energy balance model have demonstrated that canopy and soil temperatures can be retrieved from high-resolution thermal imagery captured by an unmanned aerial vehicle (UAV). This work has assumed a linear relationship between vegetation indices (VIs) and radiometric temperature in a square grid (i.e., 3.6 m x 3.6 m) that is coarser than the resolution of the imagery acquired by the UAV. In this method, with visible, near infrared (VNIR), and thermal bands available at the same high-resolution, a linear fit can be obtained over the pixels located in a grid, where the x-axis is a vegetation index (VI) and the y-axis is radiometric temperature. Next, with an accurate VI threshold that separates soil and vegetation pixels from one another, the corresponding soil and vegetation temperatures can be extracted from the linear equation. Although this method is simpler than other approaches, such as TSEB with Priestly-Taylor (TSEB-PT), it could be sensitive to VIs and the parameters that affect VIs, such as shadows. Recent studies have revealed that, on average, the values of VIs, such as normalized difference vegetation index (NDVI) and leaf area index (LAI), that are located in sunlit areas are greater than those in shaded areas. This means that involving or compensating for shadows will affect the linear relationship parameters (slope and bias) between radiometric temperature and VI, as well as thresholds that separate soil and vegetation pixels. This study evaluates the impact of shadows on the retrieval of canopy and soil temperature data from four UAV images before and after applying shadow compensation techniques. The retrieved temperatures, using the TSEB-2T approach, both before and after shadow correction, are compared to the average temperature values for both soil and canopy in each grid. The imagery was acquired by the Utah State University AggieAir UAV system over a commercial vineyard located in California as part of the USDA Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program during 2014 to 2016. The results of this study show when it is necessary to employ shadow compensation methods to retrieve vegetation and soil temperature directly

Morphometric analysis of infraorbital foramen in Indian dry skulls

We analyzed the variability in position, shape, size and incidence of the infraorbital foramen in Indian dry skulls as little literature is available on this foramen in Indians to prevent clinical complications during maxillofacial surgery and regional block anesthesia. Fifty-five Indian skulls from the Department of Anatomy CSM Medical University were examined. The 110 sides (left and right) of the skulls were analyzed by measuring the infraorbital foramina distances from infraorbital margin and the piriform aperture on both sides. The vertical and horizontal dimensions were also measured. All measurements were taken with a compass transferred to calipers and analyzed statistically. The mean distances between the infraorbital foramen and the infraorbital margin on the right and left side were 6.12 mm and 6.19 mm, respectively. The mean distances between the infraorbital foramen and the piriform aperture were 15.31 mm and 15.80 mm on the right and left sides, respectively. The mean vertical dimensions on the right and left side were 3.39 mm and 3.75 mm, respectively. The mean horizontal dimensions on the two sides were 3.19 mm and 3.52 mm. These results provide detailed knowledge of the anatomical characteristics and clinical importance of the infraorbital foramina which are of paramount importance for surgeons when performing maxillofacial surgery and regional block anesthesia

HFCVD of diamond at low substrate and low filament temperatures

It has been discovered that the addition of a small amount of oxygen to the CH{sub 4} and H{sub 2} feed gas permits HFCVD of diamond at significantly lower filament and substrate temperatures. The effective O/C ratio here is much lower than that used in most studies of the oxygen effect. Careful control of the O/C and C/H ratios were found to be crucial to success. The effects of substrate and filament temperatures on growth rate and film quality were studied. Optimum conditions were found that gave reasonable growth rates ( {approximately}0.5 {mu}m/h ) with high film quality at filament temperatures below 1750{degrees}C and substrate temperatures below 600C. As a result, low temperature deposition has been realized. Power consumption can be reduced 50%, and the filament lifetime is extended indefinitely

Magnetic separation for soil decontamination

High gradient magnetic separation (HGMS) is a physical separation process that is used to extract magnetic particles from mixtures. The technology is used on a large scale in the kaolin clay industry to whiten or brighten kaolin clay and increase its value. Because all uranium and plutonium compounds are slightly magnetic, HGMS can be used to separate these contaminants from non-magnetic soils. A Cooperative Research and Development Agreement (CRADA) was signed in 1992 between Los Alamos National Laboratory (LANL) and Lockheed Environmental Systems and Technologies Company (LESAT) to develop HGMS for soil decontamination. This paper reports progress and describes the HGMS technology

Using Fuzzy Logic to Enhance Stereo Matching in Multiresolution Images

Stereo matching is an open problem in Computer Vision, for which local features are extracted to identify corresponding points in pairs of images. The results are heavily dependent on the initial steps. We apply image decomposition in multiresolution levels, for reducing the search space, computational time, and errors. We propose a solution to the problem of how deep (coarse) should the stereo measures start, trading between error minimization and time consumption, by starting stereo calculation at varying resolution levels, for each pixel, according to fuzzy decisions. Our heuristic enhances the overall execution time since it only employs deeper resolution levels when strictly necessary. It also reduces errors because it measures similarity between windows with enough details. We also compare our algorithm with a very fast multi-resolution approach, and one based on fuzzy logic. Our algorithm performs faster and/or better than all those approaches, becoming, thus, a good candidate for robotic vision applications. We also discuss the system architecture that efficiently implements our solution

Fuzzy-similarity-based noise cancellation for real-time image processing

We introduce a new algorithm for image noise cancellation based on fuzzy similarity and homogeneity. The proposed method allows simple tuning of fuzzy filter properties and it is very convenient for high-speed real-time image processing. A detailed analysis of the filter properties is presented to support tuning its parameters for a particular application. Test examples and comparisons with other image noise cancellation techniques show the advantages of the method.</p

Signal processing for imaging and mapping ladar

The new generation laser-based FLASH 3D imaging sensors enable data collection at video rate. This opens up for realtime data analysis but also set demands on the signal processing. In this paper the possibilities and challenges with this new data type are discussed. The commonly used focal plane array based detectors produce range estimates that vary with the target's surface reflectance and target range, and our experience is that the built-in signal processing may not compensate fully for that. We propose a simple adjustment that can be used even if some sensor parameters are not known. The cost for the instantaneous image collection is, compared to scanning laser radar systems, lower range accuracy. By gathering range information from several frames the geometrical information of the target can be obtained. We also present an approach of how range data can be used to remove foreground clutter in front of a target. Further, we illustrate how range data enables target classification in near real-time and that the results can be improved if several frames are co-registered. Examples using data from forest and maritime scenes are shown.</p