Image Co-Addition with Temporally Varying Kernels

Homrighausen, Darren; Genovese, Christopher R.; Connolly, A. J.; Becker, A. C.; Owen, R.

doi:10.1086/662075

Cited by 4 publications

(10 citation statements)

References 10 publications

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“…There are several methods of tackling the image coaddition problem. Apart from such approaches as Lucky Imaging or Fourier-based methods for combining stacks of images (Homrighausen et al 2011), the pixelwise statistics techniques stand out among the commonly found approach of PSF homogenization (see Zackay & Ofek 2017 for a recent review of these techniques). To a first approximation, we disregard image convolution to the worst seeing before coadding because it alters the information contained in the image, degrades the PSF of almost the whole input image set, amplifies the background noise at high frequencies, creates correlated artefacts.…”

Section: Image Coadditionmentioning

confidence: 99%

The OTELO survey. I. Description, data reduction, and multi-wavelength catalogue

Bongiovanni,

Ramón-Pérez,

García

et al. 2020

Preprint

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Context. The evolution of galaxies through cosmic time is studied observationally by means of extragalactic surveys. The usefulness of these surveys is greatly improved by increasing the cosmological volume, in either depth or area, and by observing the same targets in different wavelength ranges. A multi-wavelength approach using different observational techniques can compensate for observational biases. Aims. The OTELO survey aims to provide the deepest narrow-band survey to date in terms of minimum detectable flux and emission line equivalent width in order to detect the faintest extragalactic emission line systems. In this way, OTELO data will complements other broad-band, narrow-band, and spectroscopic surveys. Methods. The red tunable filter of the OSIRIS instrument on the 10.4 m Gran Telescopio Canarias (GTC) is used to scan a spectral window centred at 9175 Å, which is free from strong sky emission lines, with a sampling interval of 6 Å and a bandwidth of 12 Å in the most deeply explored EGS region. Careful data reduction using improved techniques for sky ring subtraction, accurate astrometry, photometric calibration, and source extraction enables us to compile the OTELO catalogue. This catalogue is complemented with ancillary data ranging from deep X-ray to far-infrared, including high resolution HST images, which allow us to segregate the different types of targets, derive precise photometric redshifts, and obtain the morphological classification of the extragalactic objects detected.Results. The OTELO multi-wavelength catalogue contains 11 237 entries and is 50% complete at AB magnitude 26.38. Of these sources, 6600 have photometric redshifts with an uncertainty δ z phot better than 0.2 (1+z phot ). A total of 4336 of these sources correspond to preliminary emission line candidates, which are complemented by 81 candidate stars and 483 sources that qualify as absorption line systems. The OTELO survey data products were released to the public on 2019.

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Section: Image Coadditionmentioning

confidence: 99%

The OTELO survey. I. Description, data reduction, and multi-wavelength catalogue

Bongiovanni,

Ramón-Pérez,

García

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

Section: Image Coadditionmentioning

confidence: 99%

The OTELO survey

Bongiovanni

Ramón-Pérez

García

et al. 2019

A&A

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Context. The evolution of galaxies through cosmic time is studied observationally by means of extragalactic surveys. The usefulness of these surveys is greatly improved by increasing the cosmological volume, in either depth or area, and by observing the same targets in different wavelength ranges. A multi-wavelength approach using different observational techniques can compensate for observational biases. Aims. The OTELO survey aims to provide the deepest narrow-band survey to date in terms of minimum detectable flux and emission line equivalent width in order to detect the faintest extragalactic emission line systems. In this way, OTELO data will complements other broad-band, narrow-band, and spectroscopic surveys. Methods. The red tunable filter of the OSIRIS instrument on the 10.4 m Gran Telescopio Canarias (GTC) is used to scan a spectral window centred at 9175 Å, which is free from strong sky emission lines, with a sampling interval of 6 Å and a bandwidth of 12 Å in the most deeply explored EGS region. Careful data reduction using improved techniques for sky ring subtraction, accurate astrometry, photometric calibration, and source extraction enables us to compile the OTELO catalogue. This catalogue is complemented with ancillary data ranging from deep X-ray to far-infrared, including high resolution HST images, which allow us to segregate the different types of targets, derive precise photometric redshifts, and obtain the morphological classification of the extragalactic objects detected. Results. The OTELO multi-wavelength catalogue contains 11 237 entries and is 50% complete at AB magnitude 26.38. Of these sources, 6600 have photometric redshifts with an uncertainty δ zphot better than 0.2 (1+zphot). A total of 4336 of these sources correspond to preliminary emission line candidates, which are complemented by 81 candidate stars and 483 sources that qualify as absorption line systems. The OTELO survey results will be released to the public on the second half of 2019.

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“…There are multiple ways to solve for the PSF, Harmeling et al [10] proposes using the LBFGS-B Algorithm [6], Homrighausen proposes a "Fourier deconvolution" method [12] and Fish et al [9] proposes simply using the same update formula for the estimation of the PSF as for updating the model image. The latter is possible since the convolution, f * x, is commutative, meaning that if we can use an update formula to solve for the model, we must also be able to rewrite it for the PSF.…”

Section: Deconvolution As Likelihood Optimizationmentioning

confidence: 99%

“…Most of these techniques rely on a variation of an iterative deconvolution using a known point spread function (PSF). The main difficulty with such methods is preventing numerical degeneracies caused by the presence of noise and poorly constrained parameters [12]. Even more challenging is when the PSF is unknown.…”

Section: Introductionmentioning

confidence: 99%

Robust statistics for image deconvolution

Lee

Budavàri

White

et al. 2017

Astronomy and Computing

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We present a blind multiframe image-deconvolution method based on robust statistics. The usual shortcomings of iterative optimization of the likelihood function are alleviated by minimizing the M -scale of the residuals, which achieves more uniform convergence across the image. We focus on the deconvolution of astronomical images, which are among the most challenging due to their huge dynamic ranges and the frequent presence of large noise-dominated regions in the images. We show that high-quality image reconstruction is possible even in super-resolution and without the use of traditional regularization terms. Using a robust ρ-function is straightforward to implement in a streaming setting and, hence our method is applicable to the large volumes of astronomy images. The power of our method is demonstrated on observations from the Sloan Digital Sky Survey (Stripe 82) and we briefly discuss the feasibility of a pipeline based on Graphical Processing Units for the next generation of telescope surveys.

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Image Co-Addition with Temporally Varying Kernels

Cited by 4 publications

References 10 publications

The OTELO survey. I. Description, data reduction, and multi-wavelength catalogue

The OTELO survey. I. Description, data reduction, and multi-wavelength catalogue

The OTELO survey

Robust statistics for image deconvolution

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