학술논문

Likelihood ratio map for direct exoplanet detection
Document Type
Conference
Source
2022 IEEE 5th International Conference on Image Processing Applications and Systems (IPAS) Image Processing Applications and Systems (IPAS), 2022 IEEE 5th International Conference on. Five:1-5 Dec, 2022
Subject
Computing and Processing
Signal Processing and Analysis
Laplace equations
Planets
Image processing
Extrasolar planets
Imaging
Stars
Task analysis
exoplanet detection
direct imaging
angular differential imaging
maximum likelihood
detection map
likelihood ratio
Language
Abstract
Direct imaging of exoplanets is a challenging task due to the small angular distance and high contrast relative to their host star, and the presence of quasi-static noise. We propose a new statistical method for direct imaging of exoplanets based on a likelihood ratio detection map, which assumes that the noise after the background subtraction step obeys a Laplacian distribution. We compare the method with two detection approaches based on signal-to-noise ratio (SNR) map after performing the background subtraction by the widely used Annular Principal Component Analysis (AnnPCA). The experimental results on the Beta Pictoris data set show the method outperforms SNR maps in terms of achieving the highest true positive rate (TPR) at zero false positive rate (FPR).