About DrizzlePac
Overview
DrizzlePac is a software package for aligning and combining HST images, which brings an array of new features and algorithmic improvements over the prior, widely used MultiDrizzle software. Starting in July 2012, all drizzled data products obtained from MAST are produced with AstroDrizzle. An abbreviation for Astrometric Drizzle, AstroDrizzle was designed from the ground-up to substantially improve the handling of distortion in the image header World Coordinate System.
AstroDrizzle removes geometric distortion, corrects for sky background variations, flags cosmic-rays, and combines images with optional subsampling. Drizzled data products from MAST are generated for single visit associations only. To combine data from additional visits, TweakReg may be used to update the image WCS using matched source lists. Once the full set of images of a given target are properly aligned, they may be combined with AstroDrizzle.
News
February 2024: Drizzlepac’s readthedocs has been reorganized to more clearly describe its functionality and some common workflows. This change may affect links in the DrizzlePac Handbook, which will be resolved in the next version. For questions, please contact the HST Help Desk.
September 2022: Updated DrizzlePac Installation Instructions
To install Drizzlepac and related tools, please follow the instructions in the stenv Github repository, which contains the latest versions of the Space Telescope Calibration Pipeline and Analysis Tools. stenv replaces the previous AstroConda software distribution, which is no longer supported.
August 2022: "Improved Absolute Astrometry for ACS and WFC3 Data Products"
A new report (ACS ISR 2022-03; WFC3 ISR 2022-06) describes the updated WCS solutions in MAST data products and highlights two new types of "Hubble Advanced Products".
August 2021: Drizzling Multi-Epoch Datasets
Prior to combining with AstroDrizzle, multi-epoch observations with ACS/WFC, WFC3/UVIS, or ACS/SBC should be corrected for changes in the detector sensitivities ~0.1-0.2% per year. A Jupyter Notebook shows how to ‘equalize’ the count rates in WFC3/UVIS images acquired several years apart to create drizzled data products for a selected reference epoch.
February 2021: Updated DrizzlePac Handbook, now available in HDox
January 2019: DrizzlePac notebook tutorials released. See WFC3 STAN, Issue 28 for details.
About DrizzlePac
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To install Drizzlepac and related tools, please follow the instructions in the stenv Github repository, which contains the latest versions of the Space Telescope Calibration Pipeline and Analysis Tools.
This repository replaces the previous AstroConda software distribution, which is no longer supported. The DrizzlePac notebook tutorials, developed in 2019, were based on older versions of software; they will be updated in the future for full compatibility with the
stenvenvironment. While the notebooks may not run seamlessly in the new environment at present, the workflow is still relevant and may only require minor tweaks in syntax. For questions, please reach out to the DrizzlePac help desk through email or the online portal. -
New for 2019
- Initializing DrizzlePac
- Aligning observations obtained in multiple HST visits
- Aligning HST images to an absolute reference catalog (e.g. GAIA, SDSS)
- Aligning sparse fields
- Improving alignment with DS9 exclusion regions
- Masking satellite trails in DQ arrays prior to drizzling
- Optimizing the image sampling for dithered datasets
- Drizzling WFPC2 data to use a single zeropoint
- Sky matching features for HST mosaics
- Aligning HST mosaics observed with multiple detectors
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Additional Features Automated Mosaic Building Align sets of images into a large mosaic in one step Improved Sky Matching Algorithms Produce seamless mosaics using various sky matching techniques. More details can be found in an example where these techniques are compared. Mitigation of False Detections Select point-source targets for alignment based on sharpness/roundness and use of DQ masks to limit inclusion of artifacts/cosmic-rays. Aligning Different HST Cameras Specify separate source finding parameters for input and reference images to optimize source detection from images taken with different HST cameras. Aligning HST Images to Non-HST Images Allows undistorted non-HST images to be used as references for aligning and drizzling HST data. Using Exclusion Regions when Aligning Images Select specific areas of interest to use for alignment. We provide an example where these techniques are discussed. -
Archival Documentation
- DrizzlePac Handbook v1.0
- DrizzlePac Quick Start Guide
- The HST Dither Handbook v1.0
- The HST Dither Handbook v2.0
- The HST MultiDrizzle Handbook v3.0
Archival Examples
- WFC3/UVIS: Optimizing image alignment for multiple visits
- WFC3/IR: Optimizing image sampling for a single visit
- ACS/WFC: Optimizing image alignment for multiple visits
- ACS/WFC: Optimizing image sampling for a single visit
- WFC3/UVIS: Aligning images in different filters
- WFC3/UVIS: Alignment of sparse fields using headerlets
- WFPC2: Aligning and drizzling WFPC2 images
- ACS/WFC: Using SExtractor catalogs to align images
- Optimizing the image sampling
- Creating mosaics of the Eagle Nebula
- Using SExtractor Catalogs with TweakReg
- Aligning HST mosaics
- Aligning to a non-HST image
- Using DS9 regions to exclude/include sources when aligning
- Sky matching methods with AstroDrizzle
- Photometry demonstration (DRZ vs FLT)
- Creating mosaics of the Horsehead Nebula
Archival AAS Materials
- DrizzlePac Brochure: June 2012
- DrizzlePac Posters:
- AstroDrizzle: More than a New MultiDrizzle (W. Hack)
- AstroDrizzle: A Photometric Performance Study (L. Ubeda)
- AstroDrizzle: A Guide to Creating Mosaics (J. Mack)
- AstroDrizzle: Aligning Images from Multiple Instruments (R. Avila)
- AstroDrizzle: Utilizing New CALACS Products (R. Lucas)
- Using SExtractor with Tweakreg for Aligning ACS Images (R. Lucas, B. Hilbert & W. Hack)
- DrizzlePac Movie (Animation)
Questions may be addressed to the STScI Help Desk website: hsthelp.stsci.edu