Drizzle: A Method for the Linear Reconstruction of Undersampled Images

Abstract

We have developed a method for the linear reconstruction of an image from undersampled, dithered data. 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 both on image shape and photometry. This paper presents the method and its implementation. The photometric and astrometric accuracy and image fidelity of the algorithm as well as the noise characteristics of output images are discussed. In addition, we describe the use of drizzling to combine dithered images in the presence of cosmic rays.