PART-4: Masking of FITS Images using Photutils and Astropy: Elliptical Annulus | DESI ASTRO

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Introduction
In astronomical image processing, masking is a crucial technique for isolating specific regions of interest within an image. Whether you are interested in isolating round objects like stars or elongated structures like galaxies, masking can help you focus your analysis on particular areas. This tutorial covers both circular and elliptical masking of FITS (Flexible Image Transport System) images using the powerful Python libraries Photutils and Astropy. We will guide you through the entire process, from reading a FITS file to creating and applying both circular and elliptical masks, and finally visualizing the masked images.
Prerequisites
Before starting this tutorial, ensure you have the following Python libraries installed:
Astropy: A core package for astronomy.
Photutils: A package for detection and photometry of astronomical sources.
NumPy: A fundamental package for scientific computing.
Matplotlib: A plotting library for creating static, animated, and interactive visualizations in Python.
eading FITS Files with Astropy
Astropy's fits module provides a convenient interface for reading, writing, and manipulating FITS files. You will start by opening a FITS file and extracting the image data. This step is crucial as it forms the basis for further processing and analysis.
To create a circular mask:
Define the center and radius: Choose the coordinates for the center of the circle and the radius.
Generate the mask: Use Photutils to create a mask that highlights the circular region and masks out the rest of the image.
Applying the Circular Mask
Once the mask is created, it can be applied to the FITS image to isolate the circular region of interest. This involves using the mask to filter out all pixels outside the defined circle, effectively creating a new image where only the circular region is visible.
Visualizing the Masked Image
Visualizing the masked image helps in verifying the correctness of the mask and understanding the region of interest. Matplotlib is an excellent tool for displaying astronomical images. You will plot both the original and the masked images side by side for comparison.
Saving the Masked Image
After successfully applying the mask, you may want to save the masked image for further analysis or sharing. Astropy allows you to write the modified image data back to a new FITS file, preserving the original data and metadata.
Elliptical Masking of FITS Images
Creating an Elliptical Mask
An elliptical mask is characterized by its center coordinates (x, y), semi-major axis, semi-minor axis, and orientation angle. Photutils provides the EllipticalAperture and EllipticalAnnulus classes to define such regions.
To create an elliptical mask:
Define the ellipse parameters: Choose the center, semi-major axis, semi-minor axis, and rotation angle.
Generate the mask: Use Photutils to create an elliptical mask that isolates the desired region.
Applying the Elliptical Mask
Applying the mask involves using it to filter out pixels outside the defined elliptical region. This creates a new image where only the elliptical area of interest remains visible. This step is crucial for focusing the analysis on specific features within the image.
Visualizing the Masked Image
Visualization is key to verifying the mask's accuracy and understanding the isolated region. Matplotlib can be used to display the original and masked images side by side. This comparison helps in assessing the effectiveness of the mask and refining it if necessary.
Saving the Masked Image
After successfully masking the image, you may want to save the result for future use. Astropy's fits module allows you to write the masked image to a new FITS file, ensuring that the original data and metadata are preserved.
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