AAS 207th Meeting, 8-12 January 2006
Session 29 Observation Processing, Calibration and Control
Poster, Monday, 9:20am-7:00pm, January 9, 2006, Exhibit Hall

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[29.01] Band-limited imaging from undersampled data

A. S. Fruchter (STScI)

Over the past decade ``Drizzle" has become a de facto standard for the combination of HST images. However, the drizzle algorithm was developed with small, faint, partially-resolved sources in mind, and is not the best possible algorithm for high signal-to-noise unresolved objects. Here, a new method for creating band-limited images from undersampled data is presented. The method uses a drizzled image as a first order approximation and then rapidly converges toward a band-limited image which fits the data given the statistical weighting provided by the drizzled image. The method largely removes both the modest blurring and small high-frequency artifacts which can be seen in the core of a drizzle PSF. It works well in the presence of geometric distortion, and can easily handle cosmic rays, bad pixels, or other missing data. It can combine images taken with random dithers, though the number of dithers required to obtain a good final image depends in part on the quality of the dither placements. The method may prove particularly useful for deriving an accurate PSF from a single undersampled image of a stellar field.

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