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Table I.1.

Optimal set of parameters for the PSF-subtraction techniques and RSM algorithm for the nine ADI sequences obtained with the auto-RSM FF_BU_F. The ‘fit’ row indicates if the noise properties have been estimated using a best-fit approach while the β row indicates if a Gaussian maximum likelihood has been used to compute the intensity parameter. The variance row provides information about the region used for the noise properties computation and translates as follows: ST-Spatio-Temporal estimation, F-Frame based estimation, FM-Frame with mask estimation, SM -Segment with mask estimation, and T-Temporal estimation.

Parameters/ID NIRC2-1 NIRC2-2 NIRC2-3 SPHERE-1 SPHERE-2 SPHERE-3 LMIRCam-1 LMIRCam2 LMIRCam-3
APCA components 11 17 25 25 18 23 40 42 21
APCA segments 4 4 4 2 1 3 4 2 2
APCA FOV rotation 0.679 0.296 0.984 0.311 0.261 0.389 0.298 0.300 0.256
NMF components 12 2 14 18 18 12 14 20 18
LLSG rank 4 5 3 8 8 8 8 6 8
LLSG segments 4 4 1 4 2 2 4 2 3
LOCI tolerance 0.00752 0.00138 0.00425 0.00242 0.00128 0.00887 0.00112 0.00104 0.00218
LOCI FOV rotation 0.355 0.268 0.447 0.250 0.267 0.255 0.252 0.261 0.326
APCA δ 5 5 5 5 5 5 5 5 5
NMF δ 5 5 5 5 5 5 5 5 5
LLSG δ 5 5 3 4 1 2 4 2 5
LOCI δ 5 5 2 5 5 5 4 5 5
APCA crop size 3 3 3 3 3 3 3 3 3
NMF crop size 3 3 3 3 3 3 3 3 3
LLSG crop size 3 3 3 3 3 3 3 3 3
LOCI crop size 3 3 3 3 3 3 3 3 3
APCA Fit True True True True True True True True True
NMF Fit True True True True True True True True True
LLSG Fit True True True True True True True True True
LOCI Fit True True True True True True True True True
APCA β True True False False False False False False False
NMF β False False False False False False False False False
LLSG β True True False False False False False False False
LOCI β False True False False False False False False False
APCA variance T FM FM SM T FM ST SM FM
NMF variance FM FM ST SM FM ST ST SM ST
LLSG variance FM FM SM SM SM SM ST FM ST
LOCI variance FM T FM T ST SM SM SM SM

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