Multiscale Astronomical Image Processing Based on Nonlinear Partial Differential Equations

Astronomical applications of recent advances in the field of nonastronomical image processing are presented. These innovative methods, applied to multiscale astronomical images, increase signal-to-noise ratio, do not smear point sources or extended diffuse structures, and are thus a highly useful preliminary step for detection of different features including point sources, smoothing of clumpy data, and removal of contaminants from background maps. We show how the new methods, combined with other algorithms of image processing, unveil fine diffuse structures while at the same time enhance detection of localized objects, thus facilitating interactive morphology studies and paving the way for the automated recognition and classification of different features. We have also developed a new application framework for astronomical image processing that implements some recent advances made in computer vision and modern image processing, along with original algorithms based on nonlinear partial differential equations. The framework enables the user to easily set up and customize an image-processing pipeline interactively; it has various common and new visualization features and provides access to many astronomy data archives. Altogether, the results presented here demonstrate the first implementation of a novel synergistic approach based on integration of image processing, image visualization, and image quality assessment

Do some x-ray stars have white dwarf companions

Some Be stars which are intermittent X-ray sources may have white dwarf companions rather than neutron stars. It is not possible to prove or rule out the existence of Be + WD systems using X-ray or optical data. However, the presence of a white dwarf could be established by the detection of its EUV continuum shortward of the Be star's continuum turnover at 100 A. Either the detection or the nondetection of Be + WD systems would have implications for models of Be star variability, models of Be binary system formation and evolution, and models of wind-fed accretion

Do Some X-ray Stars Have White Dwarf Companions?

Some Be stars which are intermittent C-ray sources may have white dwarf companions rather than neutron stars. It is not possible to prove or rule out the existence of Be+WD systems using X-ray or optical data. However, the presence of a white dwarf could be established by the detection of its EUV continuum shortward of the Be star's continuum turnover at 1OOOA. Either the detection or the nondetection of Be+WD systems would have implications for models of Be star variability, models of Be binary system formation and evolution, and models of wind-fed accretion

The Data Big Bang and the Expanding Digital Universe: High-Dimensional, Complex and Massive Data Sets in an Inflationary Epoch

Recent and forthcoming advances in instrumentation, and giant new surveys, are creating astronomical data sets that are not amenable to the methods of analysis familiar to astronomers. Traditional methods are often inadequate not merely because of the size in bytes of the data sets, but also because of the complexity of modern data sets. Mathematical limitations of familiar algorithms and techniques in dealing with such data sets create a critical need for new paradigms for the representation, analysis and scientific visualization (as opposed to illustrative visualization) of heterogeneous, multiresolution data across application domains. Some of the problems presented by the new data sets have been addressed by other disciplines such as applied mathematics, statistics and machine learning and have been utilized by other sciences such as space-based geosciences. Unfortunately, valuable results pertaining to these problems are mostly to be found only in publications outside of astronomy. Here we offer brief overviews of a number of concepts, techniques and developments, some "old" and some new. These are generally unknown to most of the astronomical community, but are vital to the analysis and visualization of complex datasets and images. In order for astronomers to take advantage of the richness and complexity of the new era of data, and to be able to identify, adopt, and apply new solutions, the astronomical community needs a certain degree of awareness and understanding of the new concepts. One of the goals of this paper is to help bridge the gap between applied mathematics, artificial intelligence and computer science on the one side and astronomy on the other.Comment: 24 pages, 8 Figures, 1 Table. Accepted for publication: "Advances in Astronomy, special issue "Robotic Astronomy

High-Dimensional Data Reduction, Image Inpainting and their Astronomical Applications

Technological advances are revolutionizing multispectral astrophysics as well as the detection and study of transient sources. This new era of multitemporal and multispectral data sets demands new ways of data representation, processing and management thus making data dimension reduction instrumental in efficient data organization, retrieval, analysis and information visualization. Other astrophysical applications of data dimension reduction which require new paradigms of data analysis include knowledge discovery, cluster analysis, feature extraction and object classification, de-correlating data elements, discovering meaningful patterns and finding essential representation of correlated variables that form a manifold (e.g. the manifold of galaxies), tagging astronomical images, multiscale analysis synchronized across all available wavelengths, denoising, etc. The second part of this paper is dedicated to a new, active area of image processing: image inpainting that consists of automated methods for filling in missing or damaged regions in images. Inpainting has multiple astronomical applications including restoring images corrupted by instrument artifacts, removing undesirable objects like bright stars and their halos, sky estimating, and pre-processing for the Fourier or wavelet transforms. Applications of high-dimensional data reduction and mitigation of instrument artifacts are demonstrated on images taken by the Spitzer Space Telescope

A constraint-logic based implementation of the coarse-grained approach to data acquisition scheduling of the International Ultraviolet Explorer orbiting observatory

The International Ultraviolet Explorer (IUE) satellite observatory has been in operation continuously since 1978. It typically carries out several thousand observations per year for over a hundred different science projects. These observations, which can occur in one of four different data-taking modes, fall under several satellite-related constraints and many other constraints which derive from the science goals of the projects being undertaken. One strategy which has made the scheduling problem tractable has been that of 'coarse-graining' the time into discrete blocks of equal size (8 hours), each of which is devoted to a single science program, and each of which is sufficiently long for several observations to be carried out. We call it 'coarse-graining' because the schedule is done at a 'coarse' level which ignores fine structure; i.e., no attempt is made to plan the sequence of observations occurring within each time block. We have incorporated the IUE's coarse-grained approach in new software which examines the science needs of the observations and produces a limited set of alternative schedules which meet all of the instrument and science-related constraints. With this algorithm, the IUE can still be scheduled by a single person using a standard workstation, as it has been. We believe that this software could could be adapted to a more complex mission while retaining the IUE's high flexibility and efficiency and scientific return of future satellite missions

Models of FSA Guaranteed Loan Use Volume and Loss Claims among Arkansas Commercial Banks

The Farm Service Agency (FSA) guaranteed loan programs are an important source of credit to production agriculture. The two major guaranteed loan programs are the operating loan (OL) program and the farm ownership (FO) loan program. Guaranteed loans insure payment to the lender of up to 95% of the losses in the event of borrower default. FSA has historically been involved in lending to farm operators via direct loans, but emphasis has changed over the last two decades to making guaranteed loans the primary source of FSA associated lending to production agriculture. This study seeks to determine what characteristics of banks and the lending environment from 1990-1995 motivated Arkansas banks to use guaranteed loans and how the level of participation is related to such factors. In addition, factors are identified that indicate the likelihood of banks paying loss claims. Regression methods are used to identify these factors and the data base uses observations on individual Arkansas commercial banks for up to six years

Potato growing in Illinois

In cooperation with Illinois State Natural History Survey.Cover title