24 November 2014 Fringes' impetus to positional measurement of stars
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Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93011B (2014) https://doi.org/10.1117/12.2071483
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China
Abstract

In the modern astronomical CCD observation, fringes are annoying problems. It is critical to remove fringes in order to provide properly uniform photometry across the field. Usually a fringe map can be constructed by combining frames and taking medians at every pixel from the corresponding frames’ stack. Furthermore, the fringe map should be scaled based on a target frame in order to remove the fringes precisely. Astrometric work is another different measurement from photometry (for astrophysics), fringes’ impetus to positional determination is often overlooked.

When CCD frames are taken with a slow movement of telescope used, it’s hard to construct a fringe map from data themselves. We extracted the fringe map from other CCD frames in telescope’s different pointings, and thus practiced the approach according to Snodgrass and Carry [1] to derive a scale for a target frame.

Furthermore, the positional measurement was studied for the fringes’ impetus. In more detail, the positional measurements for stars were performed by a well-known 2-D Gaussian fit and were compared before and after de-fringing in the presentation. Our results showed that the biggest positional difference from fringes could be as big as 1 pixel for some faint stars. On average, the mean impetuses (standard deviation) were about 0.03 pixels, 0.25 pixels for bright stars, faint stars, respectively.

© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhong-jie Zheng, Qing-yu Peng, "Fringes' impetus to positional measurement of stars", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011B (24 November 2014); doi: 10.1117/12.2071483; https://doi.org/10.1117/12.2071483
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