The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Shapelets -- I. A method for image analysis
Open accessAbstract
We present a new method for the analysis of images, a fundamental task in observational astronomy. It is based on the linear decomposition of each object in the image into a series of localized basis functions of different shapes, which we call ‘shapelets’. A particularly useful set of complete and orthonormal shapelets is that consisting of weighted Hermite polynomials, which correspond to perturbations around a circular Gaussian. They are also the eigenstates of the two dimensional quantum harmonic oscillator, and thus allow us to use the powerful formalism developed for this problem. One of their special properties is their invariance under Fourier transforms (up to a rescaling), leading to an analytic form for convolutions. The generator of linear transformations such as translations, rotations, shears and dilatations can be written as simple combinations of raising and lowering operators. We derive analytic expressions for practical quantities, such as the centroid (astrometry), flux (photometry) and radius of the object, in terms of its shapelet coefficients. We also construct polar basis functions which are eigenstates of the angular momentum operator, and thus have simple properties under rotations. As an example, we apply the method to Hubble Space Telescope images, and show that the small number of shapelet coefficients required to represent galaxy images lead to compression factors of about 40 to 90. We discuss applications of shapelets for the archival of large photometric surveys, for weak and strong gravitational lensing and for image deprojection.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Method for Optimal Image Subtraction
Alard, C., & Lupton, R. H. (1998) · The Astrophysical Journal · doi:10.1086/305984 · Cited by 1,387
The Hubble Deep Field: Observations, Data Reduction, and Galaxy Photometry
Williams, R. E., Blacker, B., Dickinson, M., Dixon, W. V. D., Ferguson, H. C., Fruchter, A. S., Giavalisco, M., Gilliland, R. L., Heyer, I., Katsanis, R., et al. (1996) · The Astronomical Journal · doi:10.1086/118105 · Cited by 1,076
Birkinshaw, M. (1999) · Physics Reports · doi:10.1016/s0370-1573(98)00080-5 · Cited by 851
A Method for Weak Lensing Observations
Kaiser, N., Squires, G., & Broadhurst, T. (1995) · The Astrophysical Journal · doi:10.1086/176071 · Cited by 789
Probing the Universe with Weak Lensing
Mellier, Y. (1999) · Annual Review of Astronomy and Astrophysics · doi:10.1146/annurev.astro.37.1.127 · Cited by 490
Gerhard, O. E. (1993) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/265.1.213 · Cited by 464
Detection of Weak Lensing by a Cluster of Galaxies at z= 0.83
Luppino, G. A., & Kaiser, N. (1997) · The Astrophysical Journal · doi:10.1086/303508 · Cited by 336
FOCAS - Faint Object Classification and Analysis System
Jarvis, J. F., & Tyson, J. A. (1981) · The Astronomical Journal · doi:10.1086/112907 · Cited by 194
A New Shear Estimator for Weak‐Lensing Observations
Kaiser, N. (2000) · The Astrophysical Journal · doi:10.1086/309041 · Cited by 174
Weak Lensing Measurements: A Revisited Method and Application to Hubble Space Telescope Images
Rhodes, J., Refregier, A., & Groth, E. J. (2000) · The Astrophysical Journal · doi:10.1086/308902 · Cited by 166
Self-citation
Cited by
KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing
Hildebrandt, H., Viola, M., Heymans, C., Joudaki, S., Kuijken, K., Blake, C., Erben, T., Joachimi, B., Klaes, D., Miller, L., et al. (2017) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stw2805 · Cited by 1,021
Cosmology with cosmic shear observations: a review
Kilbinger, M. (2015) · Reports on Progress in Physics · doi:10.1088/0034-4885/78/8/086901 · Cited by 604
The Shear Testing Programme – I. Weak lensing analysis of simulated ground-based observations
Heymans, C., Van Waerbeke, L., Bacon, D., Berge, J., Bernstein, G., Bertin, E., Bridle, S., Brown, M. L., Clowe, D., Dahle, H., et al. (2006) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2006.10198.x · Cited by 508
Self-citationBirrer, S., Treu, T., Rusu, C. E., Bonvin, V, Fassnacht, C. D., Chan, J. H. H., Agnello, A., Shajib, A. J., Chen, G. C.-F., Auger, M., et al. (2019) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stz200 · Cited by 365
lenstronomy: Multi-purpose gravitational lens modelling software package
Birrer, S., & Amara, A. (2018) · Physics of the Dark Universe · doi:10.1016/j.dark.2018.11.002 · Cited by 324
Metadata
- Authors
- Refregier, A.
- Venue
- Monthly Notices of the Royal Astronomical Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-01-01
- Volume
- 338
- Issue
- 1
- Pages
- 35-47
- ISSN
- 0035-8711 (ISSN-L)
- 1365-2966
- OpenAlex
- W2103986031
- Cited by
- 339
- References
- 11
- FWCI
- 9.67
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Shapelets -- I. A method for image analysis. https://app.cochat.ai/papers/10.1046/j.1365-8711.2003.05901.x
- The paper
- Refregier, A. (2003). Shapelets -- I. A method for image analysis. Monthly Notices of the Royal Astronomical Society. https://doi.org/10.1046/j.1365-8711.2003.05901.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.