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Photometry of moving sources typically suffers from reduced signal-to-noise (SNR) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps, and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSF) and trailed point-spread functions (TSF) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with a accuracy of 10 millimags for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve signal-to-noise of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all SNR.
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The Montage image mosaic engine has found wide applicability in astronomy research, integration into processing environments, and is an examplar application for the development of advanced cyber-infrastructure. It is written in C to provide performance and portability. Linking C/C++ libraries to the Python kernel at run time as binary extensions allows them to run under Python at compiled speeds and enables users to take advantage of all the functionality in Python. We have built Python binary extensions of the 59 ANSI-C modules that make up version 5 of the Montage toolkit. This has involved a turning the code into a C library, with driver code fully separated to reproduce the calling sequence of the command-line tools; and then adding Python and C linkage code with the Cython library, which acts as a bridge between general C libraries and the Python interface. We will demonstrate how to use these Python binary extensions to perform image processing, including reprojecting and resampling images, rectifying background emission to a common level, creation of image mosaics that preserve the calibration and astrometric fidelity of the input images, creating visualizations with an adaptive stretch algorithm, processing HEALPix images, and analyzing and managing image metadata.
We present an algorithm implemented in the astroalign Python module for image registration in astronomy. Our module does not rely on WCS information and instead matches 3-point asterisms (triangles) on the images to find the most accurate linear transformation between the two. It is especially useful in the context of aligning images prior to stacking or performing difference image analysis. Astroalign can match images of different point-spread functions, seeing, and atmospheric conditions.
scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.
Asteroid detections in astronomical images may appear as trails due to a combination of their apparent rate of motion and exposure duration. Nearby asteroids in particular typically have high apparent rates of motion and acceleration. Their recovery, especially on their discovery apparition, depends upon obtaining good astrometry from the trailed detections. We present an analytic function describing a trailed detection under the assumption of a Gaussian point spread function (PSF) and constant rate of motion. We have fit the function to both synthetic and real trailed asteroid detections from the Pan-STARRS1 survey telescope to obtain accurate astrometry and photometry. For short trails our trailing function yields the same astrometric and photometry accuracy as a functionally simpler 2-d Gaussian but the latter underestimates the length of the trail - a parameter that can be important for measuring the objects rate of motion and assessing its cometary activity. For trails longer than about 10 pixels (> 3xPSF) our trail fitting provides 3-times better astrometric accuracy and up to 2 magnitudes improvement in the photometry. The trail fitting algorithm can be implemented at the source detection level for all detections to provide trail length and position angle that can be used to reduce the false tracklet rate.
Ground-based exoplanet surveys such as SuperWASP, HATNet and KELT have discovered close to two hundred transiting extrasolar planets in the past several years. The strategy of these surveys is to look at a large field of view and measure the brightnesses of its bright stars to around half a percent per point precision, which is adequate for detecting hot Jupiters. Typically, these surveys use CCD detectors to achieve high precision photometry. These CCDs, however, are expensive relative to other consumer-grade optical imaging devices, such as digital single-lens reflex cameras (DSLRs). We look at the possibility of using a digital single-lens reflex camera for precision photometry. Specifically, we used a Canon EOS 60D camera that records light in 3 colors simultaneously. The DSLR was integrated into the HATNet survey and collected observations for a month, after which photometry was extracted for 6600 stars in a selected stellar field. We found that the DSLR achieves a best-case median absolute deviation (MAD) of 4.6 mmag per 180 s exposure when the DSLR color channels are combined, and 1000 stars are measured to better than 10 mmag (1%). Also, we achieve 10,mmag or better photometry in the individual colors. This is good enough to detect transiting hot Jupiters. We performed a candidate search on all stars and found four candidates, one of which is KELT-3b, the only known transiting hot Jupiter in our selected field. We conclude that the Canon 60D is a cheap, lightweight device capable of useful photometry in multiple colors.
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