148 research outputs found
The 2014 American State Litter Scorecard FINAL: USA's Dirtiest & Cleanest States Includes Statistics and Charts
A NEW State Litter "Scorecard" is released for the 2014 American Society for Public Administration (ASPA) Conference. Every three years, the Scorecard approximates each state's overall public spaces environmental quality through tried-and-true, hard-to-publicly obtain objective and subjective measures, resulting in a total overall jurisdictional score. Readers gain a realistic "picture" of "what's going on" within one or all of the 50 states. Illegal littering and dumping, found frequently on or near transportation paths, creates danger to public safety and health, with 800+ Americans dying each year by vehicle collisions with unmoved roadway debris. Because policy makers, public administrators and citizens are ever more involved in effectuating "green" outcomes, satisfactory public spaces waste removals are vital. Since 2008, major publications (the Boston Globe; TRAVEL+LEISURE; National Cooperative Highway Research Program's "Reducing Litter on Roadsides" Journal) have referred to the Scorecard, an ever valuable, trusted standard for improving debris/litter abatement in states and localities
On the computation of directional scale-discretized wavelet transforms on the sphere
We review scale-discretized wavelets on the sphere, which are directional and
allow one to probe oriented structure in data defined on the sphere.
Furthermore, scale-discretized wavelets allow in practice the exact synthesis
of a signal from its wavelet coefficients. We present exact and efficient
algorithms to compute the scale-discretized wavelet transform of band-limited
signals on the sphere. These algorithms are implemented in the publicly
available S2DW code. We release a new version of S2DW that is parallelized and
contains additional code optimizations. Note that scale-discretized wavelets
can be viewed as a directional generalization of needlets. Finally, we outline
future improvements to the algorithms presented, which can be achieved by
exploiting a new sampling theorem on the sphere developed recently by some of
the authors.Comment: 13 pages, 3 figures, Proceedings of Wavelets and Sparsity XV, SPIE
Optics and Photonics 2013, Code is publicly available at http://www.s2dw.org
S2LET: A code to perform fast wavelet analysis on the sphere
We describe S2LET, a fast and robust implementation of the scale-discretised
wavelet transform on the sphere. Wavelets are constructed through a tiling of
the harmonic line and can be used to probe spatially localised, scale-depended
features of signals on the sphere. The scale-discretised wavelet transform was
developed previously and reduces to the needlet transform in the axisymmetric
case. The reconstruction of a signal from its wavelets coefficients is made
exact here through the use of a sampling theorem on the sphere. Moreover, a
multiresolution algorithm is presented to capture all information of each
wavelet scale in the minimal number of samples on the sphere. In addition S2LET
supports the HEALPix pixelisation scheme, in which case the transform is not
exact but nevertheless achieves good numerical accuracy. The core routines of
S2LET are written in C and have interfaces in Matlab, IDL and Java. Real
signals can be written to and read from FITS files and plotted as Mollweide
projections. The S2LET code is made publicly available, is extensively
documented, and ships with several examples in the four languages supported. At
present the code is restricted to axisymmetric wavelets but will be extended to
directional, steerable wavelets in a future release.Comment: 8 pages, 6 figures, version accepted for publication in A&A. Code is
publicly available from http://www.s2let.or
Implications for compressed sensing of a new sampling theorem on the sphere
A sampling theorem on the sphere has been developed recently, requiring half
as many samples as alternative equiangular sampling theorems on the sphere. A
reduction by a factor of two in the number of samples required to represent a
band-limited signal on the sphere exactly has important implications for
compressed sensing, both in terms of the dimensionality and sparsity of
signals. We illustrate the impact of this property with an inpainting problem
on the sphere, where we show the superior reconstruction performance when
adopting the new sampling theorem compared to the alternative.Comment: 1 page, 2 figures, Signal Processing with Adaptive Sparse Structured
Representations (SPARS) 201
Continuous Wavelet Transform on the Hyperboloid
In this paper we build a Continuous Wavelet Transform (CWT) on the upper sheet of the 2-hyperboloid H_+^2. First, we define a class of suitable dilations on the hyperboloid through conic ptojection. Then, incorporating hyperbolic motions belonging to SO_0(1,2), we define a family of hyperbolic wavelets. The continuous wavelet transform W_f(a,x) is obtained by convolution of the scaled wavelets with the signal. The wavelet transform is proved to be invertible whenever wavelets satisfy a particular admissibility condition, which turns out to be a zero-mean condition. We then provide some basic examples and discuss the limit at null curvature
Sparse image reconstruction on the sphere: implications of a new sampling theorem
We study the impact of sampling theorems on the fidelity of sparse image
reconstruction on the sphere. We discuss how a reduction in the number of
samples required to represent all information content of a band-limited signal
acts to improve the fidelity of sparse image reconstruction, through both the
dimensionality and sparsity of signals. To demonstrate this result we consider
a simple inpainting problem on the sphere and consider images sparse in the
magnitude of their gradient. We develop a framework for total variation (TV)
inpainting on the sphere, including fast methods to render the inpainting
problem computationally feasible at high-resolution. Recently a new sampling
theorem on the sphere was developed, reducing the required number of samples by
a factor of two for equiangular sampling schemes. Through numerical simulations
we verify the enhanced fidelity of sparse image reconstruction due to the more
efficient sampling of the sphere provided by the new sampling theorem.Comment: 11 pages, 5 figure
Probing dark energy with steerable wavelets through correlation of WMAP and NVSS local morphological measures
Using local morphological measures on the sphere defined through a steerable
wavelet analysis, we examine the three-year WMAP and the NVSS data for
correlation induced by the integrated Sachs-Wolfe (ISW) effect. The steerable
wavelet constructed from the second derivative of a Gaussian allows one to
define three local morphological measures, namely the signed-intensity,
orientation and elongation of local features. Detections of correlation between
the WMAP and NVSS data are made with each of these morphological measures. The
most significant detection is obtained in the correlation of the
signed-intensity of local features at a significance of 99.9%. By inspecting
signed-intensity sky maps, it is possible for the first time to see the
correlation between the WMAP and NVSS data by eye. Foreground contamination and
instrumental systematics in the WMAP data are ruled out as the source of all
significant detections of correlation. Our results provide new insight on the
ISW effect by probing the morphological nature of the correlation induced
between the cosmic microwave background and large scale structure of the
Universe. Given the current constraints on the flatness of the Universe, our
detection of the ISW effect again provides direct and independent evidence for
dark energy. Moreover, this new morphological analysis may be used in future to
help us to better understand the nature of dark energy.Comment: 12 pages, 10 figures, replaced to match version accepted by MNRA
Processor Enhancements for Media Streaming Applications
The development of more processing demanding applications on the Internet (video broadcasting) on one hand and the popularity of recent devices at the user level (digital cameras, wireless videophones, ...) on the other hand introduce challenges at several levels. Today, such devices present processing capabilities and bandwidth settings that are inefficient to manage scalable QoS requirements in a typical media delivery framework. In this paper, we present an impact study of such a scalable data representation optimized for QoS (Matching Pursuit 3D algorithms) on processor architectures to achieve the best performance and power efficiency. A review of state of the art techniques for processor architecture enhancement let us expect promising opportunities from the latest developments in the reconfigurable computing research field. We present here the first design steps of an efficient reconfigurable coprocessor especially designed to cope with future video delivery and multimedia processing requirements. Architecture perspectives are proposed with respect to low development cost constraints, backward compatibilty and easy coprocessor usage using an original strategy based on a hardware/software codesign methodolog
Exact reconstruction with directional wavelets on the sphere
A new formalism is derived for the analysis and exact reconstruction of band-limited signals on the sphere with directional wavelets. It represents an evolution of a previously developed wavelet formalism developed by Antoine & Vandergheynst and Wiaux et al. The translations of the wavelets at any point on the sphere and their proper rotations are still defined through the continuous three-dimensional rotations. The dilations of the wavelets are directly defined in harmonic space through a new kernel dilation, which is a modification of an existing harmonic dilation. A family of factorized steerable functions with compact harmonic support which are suitable for this kernel dilation are first identified. A scale-discretized wavelet formalism is then derived, relying on this dilation. The discrete nature of the analysis scales allows the exact reconstruction of band-limited signals. A corresponding exact multi-resolution algorithm is finally described and an implementation is tested. The formalism is of interest notably for the denoising or the deconvolution of signals on the sphere with a sparse expansion in wavelets. In astrophysics, it finds a particular application for the identification of localized directional features in the cosmic microwave background data, such as the imprint of topological defects, in particular, cosmic strings, and for their reconstruction after separation from the other signal component
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