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2020PASP..132g5001H - Publ. Astron. Soc. Pac., 132, part no 7, 5001-75001 (2020/July-0)

Robust automated photometry pipeline for blurred images.

HUANG W., XIE Z., ZHONG W., MEI Y., DENG H., LIU Y. and WANG F.

Abstract (from CDS):

The primary task of the 1.26 m telescope jointly operated by the National Astronomical Observatory and Guangzhou University is photometric observations of the g, r, and i bands. A data processing pipeline system was set up with mature software packages, such as IRAF, SExtractor, and SCAMP, to process approximately 5 GB of observational data automatically every day. However, the success ratio was significantly reduced when processing blurred images owing to telescope tracking error; this, in turn, significantly constrained the output of the telescope. We propose a robust automated photometric pipeline (RAPP) software that can correctly process blurred images. Two key techniques are presented in detail: blurred star enhancement and robust image matching. A series of tests proved that RAPP not only achieves a photometric success ratio and precision comparable to those of IRAF but also significantly reduces the data processing load and improves the efficiency.

Abstract Copyright: © 2020. The Astronomical Society of the Pacific. All rights reserved.

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