Abstract By employing the previous Voronoi approach and replacing its nearest neighbor approximation with Drizzle in iterative signal extraction, we develop a fast iterative Drizzle algorithm, named fiDrizzle, to reconstruct the underlying band-limited image from undersampled dithered frames. Compared with the existing iDrizzle, the new algorithm improves rate of convergence and accelerates the computational speed. Moreover, under the same conditions (e.g. the same number of dithers and iterations), fiDrizzle can make a better quality reconstruction than iDrizzle, due to the newly discovered High Sampling caused Decelerating Convergence (HSDC) effect in the iterative signal extraction process. fiDrizzle demonstrates its powerful ability to perform image deconvolution from undersampled dithers.
Keywords techniques: image processing — methods: observational — stars: imaging — planets and satellites: detection — gravitational lensing
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