Noise reduction methods in analysis of near infrared lunar occultation light curves for high angular resolution measurements

TL;DR

This study evaluates Fourier and Wavelet noise reduction techniques on near-infrared lunar occultation light curves, demonstrating Fourier transforms' effectiveness in enhancing signal quality without distorting fringes, thereby improving high angular resolution measurements.

Contribution

It introduces and compares Fourier and Wavelet noise reduction methods for LO data, highlighting Fourier transforms' advantages in S/N improvement and accurate angular diameter estimation.

Findings

Fourier transforms improve S/N without distorting fringes.

Wavelet transforms cause slight fringe smoothing, affecting diameter estimates.

Fourier method enhances model fitting, especially for fainter sources.

Abstract

Lunar occultation (LO) technique in the near-infrared provides angular resolution down to milliarcseconds on the occulted source even with ground-based 1m class telescopes. LO observations are limited to brighter objects because they require high signal to noise ratio (S/N ~ 40) for proper extraction of angular diameter values. Hence, methods to improve the S/N ratio by reducing noise using Fourier and Wavelet transforms have been explored in this study. A sample of 54 near-infrared LO light curves observed with IR Camera at Mt Abu observatory has been used. It is seen that both Fourier and Wavelet methods have shown improvement in S/N, compared to the original data. However, the application of wavelet transforms results in slight smoothening of the fringes resulting in a higher angular diameter value. Fourier transforms which reduce discrete noise frequencies do not distort the fringe. Fourier transform method seems to be effective in S/N improvement, as well as improved model fit particularly in the fainter regime of our sample. They also provide a better model fit for brighter sources in some cases though there may not be significant S/N improvement.