Gaussian Denoising for the First Image from The James Webb Space Telescope “Carina Nebula” using Non-Linear Filters - Abdul Wadood *, Mohammed; Ghalib Jaber, Asmaa (Journal of Economics and Administrative Sciences, 2024)
Noise, including Gaussian noise, distorts images during transition or acquisition process, reducing required information. Removing or reducing this noise is crucial in image processing. The James Webb Space Telescope (JWST) is a vital tool for enhancing our understanding of the universe, providing valuable scientific data and inspiring global interest. In this paper we introduce several nonlinear (Non-Local Mean, Bilateral, and classical) filters to remove the Gaussian noise from the Carina Nebula Image, the first image taken by (JWST) on 12 July 2022. These nonlinear filters were therefore selected to highlight the significance of selecting the right technique that can handle, process, and preserve as many details as possible. They also serve to elucidate the degree of advancement achieved in the field of denoising and the distinction between the classical filters and the more sophisticated filters that have evolved to handle finer details. Classic filters deal with the pixels themselves and their neighbors and then perform the desired statistical process. While advanced filters consider the similarities and distances between the central pixel and its neighbors, they preserve the edges of the image as advanced features. Based on quality measurements (PSNR) and (SSIM), the filter results were compared. The results show that the Bilateral filter gives high performance in restoring images under different Gaussian noise densities compared with the other denoising filters where it gives values of (30.65) and (0.93) for (PSNR) and (SSIM) respectively Which is higher than the results of the filters. Paper type :Research paper.