Drizzle (image processing)

Lore & Background

Drizzle was originally developed to combine the dithered images of the Hubble Deep Field North and has since been widely used for the combination of dithered images from both HST's cameras and those on other telescopes. The method has the versatility of shift-and-add, yet largely maintains the resolution and independent noise statistics of interlacing. It can handle images with essentially arbitrary shifts, rotations, and geometric distortion, and when given input images with proper associated weight maps, creates an optimal statistically summed image. Drizzle also naturally handles images with missing data due to corruption by cosmic rays or detector defects.

Camera optics generally introduce geometric distortion of images. Undersampled images are common in astronomy because instrument designers are frequently forced to choose between properly sampling a small field of view and undersampling a larger field. This is a particular problem for the Hubble Space Telescope, where corrected optics may provide superb resolution, but detectors are only able to take full advantage of the full resolving power over a limited field of view. Drizzle was developed as a collaboration between the Space Telescope Science Institute and the Space Telescope European Coordinating Facility.

In addition to Drizzle, a number of ancillary tasks that assist in the combination of Hubble Space Telescope imaging data are available as part of the Drizzlepac package. Detailed descriptions of the process and tutorials are provided in the Drizzlepac Handbook.

Reader's Guide

Drizzle is notable for its widespread use in both professional and amateur astrophotography. Originally developed for the Hubble Deep Field observations, it has become a standard tool for combining dithered images from HST cameras and other telescopes. The method preserves photometry and resolution while removing geometric distortion effects, and it can weight input images according to the statistical significance of each pixel. For amateur astrophotographers, drizzling is commonly used for processing large amounts of planetary image data, typically several thousand frames, and can also recover higher resolution stills from terrestrial video recordings. According to astrophotographer David Ratledge, results using the DRIZZLE command can be spectacular with amateur instruments. The algorithm is freely available in the Drizzlepac Python package, and its legacy is tied to enabling high-quality image reconstruction from undersampled data, particularly for the Hubble Space Telescope.

Did You Know?

• Drizzle was originally developed for the Hubble Deep Field observations made for the Hubble Space Telescope.
• The algorithm is also known informally as 'variable-pixel linear reconstruction'.
• Drizzle can combine dithered images in the presence of cosmic rays.