PYTHON:Mastering Masking Technique| Astronomical FITS Image/Spectra| Astropy & Photutils| DESI ASTRO

CHAPTER TIMESTAMPS
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00:00:00 Introduction
00:00:10 Mask Particual pIxel
00:16:27 Mask Pixel Above Threshold Intensity Value
00:29: 51 Rectangular Masking
00:41: 33 Elliptical/Circular Masking
01:00:33 Elliptical Annlus Masking
01:08:44 MASK FITS Spectra
01:28:31 MASK Spectral Data Cube

FITS (Flexible Image Transport System) is the standard file format used in astronomy for storing and analyzing data. Let’s break it down:

FITS Images: These are 2D arrays that show images of the sky, where each pixel represents light intensity from a specific point in space.
Spectra: Spectral data reveals how light intensity changes across different wavelengths, providing insights into the composition, temperature, and motion of celestial objects.
Data Cubes: These are 3D datasets that combine spatial and spectral information. Imagine a stack of 2D images, each corresponding to a specific wavelength, forming a "cube" of data.
Masking: In this context, masking is a technique used to isolate or exclude specific parts of the data. For example:

In FITS images, masking can be applied to remove noisy or invalid pixels, such as those caused by cosmic rays or defective detectors.
For spectra and data cubes, masking might exclude wavelengths or regions with interference or noise, ensuring the analysis focuses only on reliable data.
Masking is a critical step in cleaning and preparing astronomical data, allowing researchers to focus on the most meaningful parts of their observations.