The James Webb Space Telescope (JWST) is the current state-of-the-art space telescope run by NASA. It is used to capture images of our universe and to explore the science behind its formation. In many of the images captured by the JWST, we can see a hexagonal pattern of light coming off of bright stars due to diffraction (explained more here). While these patterns are very interesting and can be quite beautiful, we have an interest in removing them to achieve a more "natural" image, without the physical artifact. To do so can be challenging. 

In this project we will explore many different techniques in order to identify these diffraction patterns and then to remove them from the image while maintaining as much of the rest of the original as possible. Some of the detection methods include frequency spectrum analysis and edge detection. Removal methods include averaging, deblurring, localized averaging, and dictionary learning.