Noise-weighted angular differential imaging

TL;DR

This paper discusses an enhancement to the angular differential imaging technique by introducing a noise-weighted derotation and median-combination method, which improves the signal-to-noise ratio in high contrast imaging.

Contribution

It proposes a modified algorithm for ADI that incorporates noise-weighting, leading to improved detection capabilities in high contrast imaging.

Findings

Enhanced signal-to-noise ratio with the new method

Small algorithmic change yields significant gains

Applicable to high contrast imaging scenarios

Abstract

Angular differential imaging (ADI) (Marois et al. 2006) is an observational technique in high contrast imaging where the telescope is used in pupil tracking mode so that the image of the sky rotates with respect to the optical surfaces. Bright "speckle" light caused by optical errors remains fixed in the image, while planets and disks rotate with the sky. The resulting dataset is then post-processed to remove the speckles, de-rotated to undo the sky motion, and median-collapsed to create a final data product. The postprocessing algorithms to remove the speckles are an active area of research and beyond the scope of this note. We consider the derotation and median-combination, where we show gains in signal-to-noise ratio are possible with a small change to the algorithm.