  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.
