Drizzle in astrophotography is a digital image processing method for the linear reconstruction of undersampled images. It is normally used for the combination of astronomical images and was originally developed for the Hubble Deep Field observations made by the Hubble Space Telescope.
The algorithm, known as variable-pixel linear reconstruction, or informally as “Drizzle”, preserves photometry and resolution, can weight input images according to the statistical significance of each pixel, and removes the effects of geometric distortion on both image shape and photometry.
In addition, it is possible to use drizzling to combine dithered images in the presence of cosmic rays. Drizzling is commonly used by amateur astrophotographers, particularly for processing large amounts of planetary image data.
Drizzling an astronomical image allows for a larger image to be created with improved resolution and higher numerical image scale. It also helps to compensate for undersampled data, as it does not magically increase the resolution of well-sampled images. Drizzle flips things around and expands the resolution of the image by taking 1 pixel and expanding it into 2×2 pixels. This helps to increase the detail and accuracy of the image, making it easier to see faint details.
Drizzle can help you improve your photos and reduce pixelation in undersampled images. It essentially expands the original image’s resolution and then fills in or interpolates the values in between. This has the effect of reducing pixelation and smoothing out pixel edges.
In the video below I demonstrate how to manually drizzle in PixInsight and the improvement it makes to the image. In more recent versions of PixInsight drizzle can be performed automatically by using the Weighted Batch Preprocessing (WBPP) script when calibrating, aligning and stacking the data.