Renewal Strings for Cleaning Astronomical Databases
Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert, G. Mann

TL;DR
This paper introduces renewal strings, a probabilistic method combining Hough transform, renewal processes, and hidden Markov models, to effectively identify and flag spurious records caused by artifacts in large astronomical sky survey databases.
Contribution
The paper presents a novel probabilistic technique, renewal strings, for detecting and removing artifacts in astronomical data, improving data quality for sky surveys.
Findings
Highly effective in identifying artifacts in SSS data
Provides confidence measures for spurious object detections
Applicable to future astronomical survey datasets
Abstract
Large astronomical databases obtained from sky surveys such as the SuperCOSMOS Sky Surveys (SSS) invariably suffer from a small number of spurious records coming from artefactual effects of the telescope, satellites and junk objects in orbit around earth and physical defects on the photographic plate or CCD. Though relatively small in number these spurious records present a significant problem in many situations where they can become a large proportion of the records potentially of interest to a given astronomer. In this paper we focus on the four most common causes of unwanted records in the SSS: satellite or aeroplane tracks, scratches fibres and other linear phenomena introduced to the plate, circular halos around bright stars due to internal reflections within the telescope and diffraction spikes near to bright stars. Accurate and robust techniques are needed for locating and…
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Taxonomy
TopicsImage and Object Detection Techniques · Astronomical Observations and Instrumentation · Image Processing and 3D Reconstruction
