TL;DR: This paper considers the requirements and implementation constraints on a framework that simultaneously enables an efficient discretization with associated hierarchical indexation and fast analysis/synthesis of functions defined on the sphere and demonstrates how these are explicitly satisfied by HEALPix.
Abstract: HEALPix the Hierarchical Equal Area isoLatitude Pixelization is a versatile structure for the pixelization of data on the sphere. An associated library of computational algorithms and visualization software supports fast scientific applications executable directly on discretized spherical maps generated from very large volumes of astronomical data. Originally developed to address the data processing and analysis needs of the present generation of cosmic microwave background experiments (e.g., BOOMERANG, WMAP), HEALPix can be expanded to meet many of the profound challenges that will arise in confrontation with the observational output of future missions and experiments, including, e.g., Planck, Herschel, SAFIR, and the Beyond Einstein inflation probe. In this paper we consider the requirements and implementation constraints on a framework that simultaneously enables an efficient discretization with associated hierarchical indexation and fast analysis/synthesis of functions defined on the sphere. We demonstrate how these are explicitly satisfied by HEALPix.
TL;DR: This research attacked the mode confusion problem by developing a parallel version of the “ Hubble Space Telescope” (“Hubble”) based on a model developed by accident at the Jet Propulsion Laboratory.
Abstract: 1 San Diego Supercomputer Center, University of California, San Diego, USA 2 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA 3 Max-Planck-Institute for Astrophysics, Garching, Germany 4 Institut d’Astrophysique de Paris, CNRS/Sorbonne Universite, Paris, France 5 Laboratoire Astroparticules et Cosmologie, CNRS/Université Paris Diderot, Paris, France 6 Goddard Space Flight Center, NASA, Greenbelt, Maryland, USA
TL;DR: The standard differential privacy notion is extended to image data, which protects individuals, objects, or their features, and is shown to effectively reduce the success rate of re-identification attacks.
Abstract: Ubiquitous surveillance cameras and personal devices have given rise to the vast generation of image data. While sharing the image data can benefit various applications, including intelligent transportation systems and social science research, those images may capture sensitive individual information, such as license plates, identities, etc. Existing image privacy preservation techniques adopt deterministic obfuscation, e.g., pixelization, which can lead to re-identification with well-trained neural networks. In this study, we propose sharing pixelized images with rigorous privacy guarantees. We extend the standard differential privacy notion to image data, which protects individuals, objects, or their features. Empirical evaluation with real-world datasets demonstrates the utility and efficiency of our method; despite its simplicity, our method is shown to effectively reduce the success rate of re-identification attacks.
TL;DR: The CdTe gamma-ray camera IBIS/ISGRI, on board the INTEGRAL satellite launched in October 2002, is currently the largest spectro-imager of this type in the world as discussed by the authors.
Abstract: The CdTe gamma-ray camera IBIS/ISGRI, on board the INTEGRAL satellite launched in October 2002, is currently the largest spectro-imager of this type in the world. The development of this detector, for research in the field of astrophysics, has provided the opportunity to demonstrate the feasibility of massive integration of CdTe nuclear detectors, taking advantage of the CdTe good spectral performances and high modularity. Many other groups in the world work also to further develop detectors using this material in view of improving its spectral performances (crystal quality, electrode geometry and type, electronics and filtering, etc.), the spatial resolution (pixelization of monolithic crystals) and the detection efficiency at high energy (thickness). In this review, I will detail the main directions in which to strive in order to explore these fields in the upcoming years through examples of techniques or applications.
TL;DR: In this article, a system and method for correction and reconstruction of digital color images make use of one or more of a set of algorithms for color calibration and correction, and reconstruction, which can be used to match the response curve of the scanner to that of the scanned media, thereby improving signal-to-noise ratio and decreasing artifacts such as pixelization.
Abstract: A system and method for correction and reconstruction of digital color images make use of one or more of a set of algorithms for color calibration and correction, and reconstruction. An algorithm for optimized bit depth reduction also can be used to match the response curve of the scanner to that of the scanned media, thereby improving signal-to-noise ratio and decreasing artifacts such as pixelization, which can result from sampling the tone curve too coarsely. In a photographic film application, in particular, a color calibration and correction algorithm enables correction of the image for variations in hue from film type to film type, over-exposure or under-exposure, exposure-induced hue shifts, hue shifts caused by lighting effects, processing related hue shifts, and other variables in film processing, while preserving overall hue of the subject matter in the originally photographed image. An image reconstruction algorithm allows creation of look-up tables (LUTs) that create a visually pleasing version of the image when applied to the original data.