Detection and removal of artifacts in astronomical images
@article{Desai2016DetectionAR, title={Detection and removal of artifacts in astronomical images}, author={Shantanu Desai and Joseph J. Mohr and Emmanuel Bertin and Martin Kuemmel and Markus Wetzstein}, journal={Astron. Comput.}, year={2016}, volume={16}, pages={67-78} }
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References
SHOWING 1-10 OF 39 REFERENCES
Implementation of Robust Image Artifact Removal in SWarp through Clipped Mean Stacking
- Physics, Geology
- 2014
An algorithm for detecting and removing artifacts from astronomical images by means of outlier rejection during stacking that has superior noise properties, allowing a significant reduction in exposure time compared to median stacking.
Simultaneous Multicolor Detection of Faint Galaxies in the Hubble Deep Field
- Environmental Science
- 1999
We present a novel way to detect objects when multiband images are available. Typically, object detection is performed in one of the available bands or on a somewhat arbitrarily co-added image. Our…
Cosmic‐Ray Rejection by Linear Filtering of Single Images
- Physics
- 2000
It is demonstrated that the false alarm probability for a pixel containing object flux will never exceed the corresponding probability for an blank-sky pixel, provided the convolution kernel appropriately, which allows confident rejection of cosmic rays superposed on real objects.
Evaluation of Cosmic Ray Rejection Algorithms on Single-Shot Exposures
- PhysicsPublications of the Astronomical Society of Australia
- 2005
Abstract To maximise data output from single-shot astronomical images, the rejection of cosmic rays is important. We present the results of a benchmark trial comparing various cosmic ray rejection…
Drizzle: A Method for the Linear Reconstruction of Undersampled Images
- Computer Science
- 1998
The photometric and astrometric accuracy and image fidelity of the algorithm as well as the noise characteristics of output images are discussed and the use of drizzling to combine dithered images in the presence of cosmic rays is described.
The Dark Energy Survey data processing and calibration system
- Computer ScienceOther Conferences
- 2012
The Dark Energy Survey (DES) is a 5000 deg2 grizY survey reaching characteristic photometric depths of 24th magnitude (10 sigma) and enabling accurate photometry and morphology of objects ten times…
THE BLANCO COSMOLOGY SURVEY: DATA ACQUISITION, PROCESSING, CALIBRATION, QUALITY DIAGNOSTICS, AND DATA RELEASE
- Physics
- 2012
The Blanco Cosmology Survey (BCS) is a 60 night imaging survey of ∼80 deg2 of the southern sky located in two fields: (α, δ) = (5 hr, −55°) and (23 hr, −55°). The survey was carried out between 2005…
The Two Micron All Sky Survey (2MASS)
- Physics
- 2006
Between 1997 June and 2001 February the Two Micron All Sky Survey (2MASS) collected 25.4 Tbytes of raw imaging data covering 99.998% of the celestial sphere in the near-infrared J (1.25 μm), H (1.65…
CosmoDM and its application to Pan-STARRS data
- Physics
- 2015
Processed Pan-STARRS data from CosmoDM has been used to optically confirm and measure photometric redshifts of Planck-based Sunyaev-Zeldovich effect selected cluster candidates.