A number of popular software tools in the public domain are used by astronomers, professional and amateur
alike, but some of the tools that have similar purposes cannot be easily interchanged, owing to the lack of a
common standard. For the case of image distortion, SCAMP and SExtractor, available from Astromatic.net,
perform astrometric calibration and source-object extraction on image data, and image-data geometric distortion
is computed in celestial coordinates with polynomial coefficients stored in the FITS header with the PV i_j
keywords. Another widely-used astrometric-calibration service, Astrometry.net, solves for distortion in pixel
coordinates using the SIP convention that was introduced by the Spitzer Science Center. Up until now, due to
the complexity of these distortion representations, it was very difficult to use the output of one of these packages
as input to the other. New Python software, along with faster-computing C-language translations, have been
developed at the Infrared Processing and Analysis Center (IPAC) to convert FITS-image headers from PV to
SIP and vice versa. It is now possible to straightforwardly use Astrometry.net for astrometric calibration and
then SExtractor for source-object extraction. The new software also enables astrometric calibration by SCAMP
followed by image visualization with tools that support SIP distortion, but not PV . The software has been
incorporated into the image-processing pipelines of the Palomar Transient Factory (PTF), which generate FITS
images with headers containing both distortion representations. The software permits the conversion of archived
images, such as from the Spitzer Heritage Archive and NASA/IPAC Infrared Science Archive, from SIP to PV
or vice versa. This new capability renders unnecessary any new representation, such as the proposed TPV
The Palomar Transient Factory (PTF) is a new fully-automated, wide-field survey conducting a systematic exploration
of the optical transient sky. The transient survey is performed using a new 8.1 square degree, 101 megapixel camera
installed on the 48-inch Samuel Oschin Telescope at Palomar Observatory. The PTF Camera achieved first light at the
end of 2008, completed commissioning in July 2009, and is now in routine science operations. The camera is based on
the CFH12K camera, and was extensively modified for use on the 48-inch telescope. A field-flattening curved window
was installed, the cooling system was re-engineered and upgraded to closed-cycle, custom shutter and filter exchanger
mechanisms were added, new custom control software was written, and many other modifications were made. We here
describe the performance of these new systems during the first year of Palomar Transient Factory operations, including
a detailed and long term on-sky performance characterization. We also describe lessons learned during the construction
and commissioning of the upgraded camera, the photometric and astrometric precision currently achieved with the PTF
camera, and briefly summarize the first supernova results from the PTF survey.
LSST will have a Science Data Quality Assessment (SDQA) subsystem for the assessment of the data products that will
be produced during the course of a 10 yr survey. The LSST will produce unprecedented volumes of astronomical data as
it surveys the accessible sky every few nights. The SDQA subsystem will enable comparisons of the science data with
expectations from prior experience and models, and with established requirements for the survey. While analogous
systems have been built for previous large astronomical surveys, SDQA for LSST must meet a unique combination of
challenges. Chief among them will be the extraordinary data rate and volume, which restricts the bulk of the quality
computations to the automated processing stages, as revisiting the pixels for a post-facto evaluation is prohibitively
expensive. The identification of appropriate scientific metrics is driven by the breadth of the expected science, the scope
of the time-domain survey, the need to tap the widest possible pool of scientific expertise, and the historical tendency of
new quality metrics to be crafted and refined as experience grows. Prior experience suggests that contemplative, off-line
quality analyses are essential to distilling new automated quality metrics, so the SDQA architecture must support
integrability with a variety of custom and community-based tools, and be flexible to embrace evolving QA demands.
Finally, the time-domain nature of LSST means every exposure may be useful for some scientific purpose, so the model
of quality thresholds must be sufficiently rich to reflect the quality demands of diverse science aims.
Data Quality Analysis (DQA) for astronomical infrared maps and spectra acquired by NASA's Spitzer Space Telescope is one of the important functions performed in routine science operations at the Spitzer Science Center of the California Institute of Technology. A DQA software system has been implemented to display, analyze and grade Spitzer science data. This supports the project requirement that the science data be verified after calibration and before archiving and subsequent release to the astronomical community. The software has an interface for browsing the mission data and for visualizing images and spectra. It accesses supporting data in the operations database and updates the database with DQA grading information. The system has worked very well since the beginning of the Spitzer observatory's routine phase of operations, and can be regarded as a model for DQA operations in future space science missions.
A graphical user interface (GUI) for bandmerging is presented. The purpose of the Bandmerge GUI is to provide an integrated graphical user interface for running the bandmerge module and its support modules to provide astronomers with an interactive tool for bandmerging. The bandmerge module identifies multi-band detections of an individual point source and merges the information in the different bands into a single record of the source. The developed Java Application provides an interface to downlink software, which is normally invoked on the command line. With the Bandmerge GUI, a <i>SPITZER</i> general user can select the data to be processed, specify processing parameters, and invoke the Bandmerge pipelines.
A new nonlinear diffusion filtering scheme based on a nonlinear diffusion equation with a variable scale parameter is developed to preserve faint point sources while smoothing images for segmentation purposes. Application of the proposed approach to simulated, as well as to real images obtained by the <i>Spitzer Space Telescope</i> and by the <i>Chandra</i> X-ray Observatory reduced the Gaussian and Poisson noise successfully, while preserving both point sources and diffuse structures.