The module provides tools and algorithms for estimating the background of astronomical data.
Estimating backgrounds is an important step in performing photometry. Ideally, we could perfectly describe the background with a scalar value or with some distribution. Unfortunately, it's impossible for us to precisely separate the background and foreground signals. Here, we use mixture of robust statistical estimators and meshing to let us get the spatially varying background from an astronomical photo.
Let's show an example
using Photometry using FITSIO using Plots # Download our image, courtesy of astropy hdu = FITS(download("https://rawcdn.githack.com/astropy/photutils-datasets/8c97b4fa3a6c9e6ea072faeed2d49a20585658ba/data/M6707HH.fits")) image = read(hdu) # Plot function imshow(image; kwargs...) xs, ys = axes(image) data = transpose(image) heatmap(xs, ys, data; aspect_ratio=1, xlim=extrema(xs), ylim=extrema(ys), kwargs...) end imshow(image)