918 resultados para Astronomical photography.


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Sparse representation of astronomical images is discussed. It is shown that a significant gain in sparsity is achieved when particular mixed dictionaries are used for approximating these types of images with greedy selection strategies. Experiments are conducted to confirm (i) the effectiveness at producing sparse representations and (ii) competitiveness, with respect to the time required to process large images. The latter is a consequence of the suitability of the proposed dictionaries for approximating images in partitions of small blocks. This feature makes it possible to apply the effective greedy selection technique called orthogonal matching pursuit, up to some block size. For blocks exceeding that size, a refinement of the original matching pursuit approach is considered. The resulting method is termed "self-projected matching pursuit," because it is shown to be effective for implementing, via matching pursuit itself, the optional backprojection intermediate steps in that approach. © 2013 Optical Society of America.

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What is discussed in this chapter is work-in-progress, an opportunity for reflection upon elements of an on-going research project examining the lives of street children in Accra, Ghana. Street children have received much research in recent years but our project is, we believe, distinctive in two respects. The first of these is that access to reliable data on the growing presence of children on the streets of African cities is often problematic. Available research is often diffuse and hard to access, it is more often than not driven by the short-term requirements of specific programmes and interventions and as a consequence can be lacking in depth, rigour and innovation. Without the means to provide a sufficiently self-conscious and critical engagement with accepted understandings of the lives of street children, consideration of the experience of street children in Africa continues to rely heavily on the more capacious and better disseminated research from the Americas (e.g., Mickelson, 2000). At the very least, Africa's specific experience of large population displacements, diversity of family forms, rapid urbanisation, vigorous structural adjustment and internal conflict raise important questions about the appropriateness of such ready generalisations. Judith Ennew (2003, p. 4) is clear that caution is needed in an uncritical endorsement of the “globalisation of the street child based on Latin American work”. She is equally mindful, however, that as far as Africa is concerned the absence of reliable evidence continues to hinder debate.

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Purpose: To assess the inter and intra observer variability of subjective grading of the retinal arterio-venous ratio (AVR) using a visual grading and to compare the subjectively derived grades to an objective method using a semi-automated computer program. Methods: Following intraocular pressure and blood pressure measurements all subjects underwent dilated fundus photography. 86 monochromatic retinal images with the optic nerve head centred (52 healthy volunteers) were obtained using a Zeiss FF450+ fundus camera. Arterio-venous ratios (AVR), central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) were calculated on three separate occasions by one single observer semi-automatically using the software VesselMap (ImedosSystems, Jena, Germany). Following the automated grading, three examiners graded the AVR visually on three separate occasions in order to assess their agreement. Results: Reproducibility of the semi-automatic parameters was excellent (ICCs: 0.97 (CRAE); 0.985 (CRVE) and 0.952 (AVR)). However, visual grading of AVR showed inter grader differences as well as discrepancies between subjectively derived and objectively calculated AVR (all p < 0.000001). Conclusion: Grader education and experience leads to inter-grader differences but more importantly, subjective grading is not capable to pick up subtle differences across healthy individuals and does not represent true AVR when compared with an objective assessment method. Technology advancements mean we no longer rely on opthalmoscopic evaluation but can capture and store fundus images with retinal cameras, enabling us to measure vessel calibre more accurately compared to visual estimation; hence it should be integrated in optometric practise for improved accuracy and reliability of clinical assessments of retinal vessel calibres. © 2014 Spanish General Council of Optometry.

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ACM Computing Classification System (1998): J.2.

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ACM Computing Classification System (1998): J.2.

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ACM Computing Classification System (1998): J.2.

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ACM Computing Classification System (1998): J.2.

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ACM Computing Classification System (1998): H.5.2, H.2.8, J.2, H.5.3.

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ACM Computing Classification System (1998): I.2.8, I.2.10, I.5.1, J.2.

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ACM Computing Classification System (1998): I.7, I.7.5.

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Established as a National Park in 1980, Biscayne National Park (BISC) comprises an area of nearly 700 km2 , of which most is under water. The terrestrial portions of BISC include a coastal strip on the south Florida mainland and a set of Key Largo limestone barrier islands which parallel the mainland several kilometers offshore and define the eastern rim of Biscayne Bay. The upland vegetation component of BISC is embedded within an extensive coastal wetland network, including an archipelago of 42 mangrove-dominated islands with extensive areas of tropical hardwood forests or hammocks. Several databases and vegetation maps describe these terrestrial communities. However, these sources are, for the most part, outdated, incomplete, incompatible, or/and inaccurate. For example, the current, Welch et al. (1999), vegetation map of BISC is nearly 10 years old and represents the conditions of Biscayne National Park shortly after Hurricane Andrew (August 24, 1992). As a result, a new terrestrial vegetation map was commissioned by The National Park Service Inventory and Monitoring Program South Florida / Caribbean Network.

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Mapping of vegetation patterns over large extents using remote sensing methods requires field sample collections for two different purposes: (1) the establishment of plant association classification systems from samples of relative abundance estimates; and (2) training for supervised image classification and accuracy assessment of satellite data derived maps. One challenge for both procedures is the establishment of confidence in results and the analysis across multiple spatial scales. Continuous data sets that enable cross-scale studies are very time consuming and expensive to acquire and such extensive field sampling can be invasive. The use of high resolution aerial photography (hrAP) offers an alternative to extensive, invasive, field sampling and can provide large volume, spatially continuous, reference information that can meet the challenges of confidence building and multi-scale analysis.