Space Telescope Science Institute
DrizzlePac 2012 Handbook
Table of Contents Previous Next Index Print

The DrizzlePac Handbook > Chapter 4: DrizzlePac Package > 4.1 DrizzlePac: An Overview

DrizzlePac is a package of tasks used primarily for post-pipeline drizzling of images. astrodrizzle is its flagship task, and the rest of DrizzlePac’s tasks support more complex drizzling operations.
AstroDrizzle replaces MultiDrizzle in the pipeline and for post-pipeline image drizzling. It uses the same algorithmic base as MultiDrizzle with a modified set of core routines that have been recoded in C and Python.
AstroDrizzle also introduces a conceptual change in how drizzling is handled, from moving pixels according to shifts to moving them according to the astrometry encoded in the WCS. This chapter provides a description of the software interface to AstroDrizzle and the other tasks in the DrizzlePac package.
In a nutshell, AstroDrizzle processes a set of pipeline flat-field calibrated files (flt.fits) as follows:
Using this astrometric information, and the distortion information in the header, the images are separately drizzled onto undistorted output images in a common reference frame.
By comparing each flt.fits image with its blotted counterpart median image, the software locates bad pixels in each of the original flt.fits frames and creates bad pixel masks. These bad pixels are typically cosmic rays or faulty pixels in the detector.
In the final step, all images are drizzled, using the mask files, onto a single output image. This produces an image that’s corrected for geometric distortion and largely free of cosmic rays and detector artifacts.
In the pipeline, AstroDrizzle task parameters are given default values selected to cover a wide range of data. These parameter values are stored in a reference file named by the MDRIZTAB image header keyword. However, these values may not be well suited for some images. In such cases, users may elect to reprocess the images to obtain better quality results.
In this section, as well as Chapters 6 and 7, information will be provided to help users select the best possible task parameter values suited for reprocessing their data. This includes combining images spread over several visits at different roll angles–this type of data is almost always taken using different guide stars, and due to positional uncertainties in the Guide Star Catalog, the coordinate frames of each visit could be significantly misaligned as much as 0.5 arcseconds. A DrizzlePac task called tweakreg will serve as a useful tool, in most imaging cases, for aligning all multi-visit images to a common WCS. There are also tools for converting pixel positions to sky coordinates, and vice versa, as well as translating pixel positions for an image before and after geometric distortion corrections.
Software Requirements
DrizzlePac has been designed and implemented as a package in Python. AstroDrizzle and other DrizzlePac tasks maintain their own command-line interface in the Python environment. Tasks in DrizzlePac can also be run using the TEAL GUI, an interface that resembles the “epar” GUI in PyRAF. TEAL is part of another Python-based package called, and is invoked by typing epar followed by the taskname in PyRAF. These packages have been designed to work together without requiring any manual settings of the environment by the user.
DrizzlePac requires at least Python 2.6, PyFITS v3.0 and Numpy v1.6 to be installed for operation with the Python interfaces. In addition, PyRAF v1.10 or greater is required for use of the GUI interface. Additional information is available at the STScI Python webpage and the DrizzlePac webpage.

Table of Contents Previous Next Index Print