Image denoising techniques: An overview

• Main Authors: Jebur R.S., Der C.S., Hammood D.A., Weng L.Y.
• Other Authors: 57214077047
• Format: Conference Paper
• Published: American Institute of Physics Inc. 2024
• Subjects: AI; Image Denoising; PSNR and SSIM

This article provides an in-depth overview of image denoising. Furthermore, the technical aspects developed for image denoising are highlighted in a wider sense. Image denoising is the removal of noise from a noisy image. Most importantly, one has to keep track of the information on image details. The challenges of image denoising, on the other hand, have not improved significantly. A general review for the image denoising mechanisms will be presented. Those mechanisms contain more than one filter like Baysion, Mean, Median, Gaussian, Guide, as well as collaborative filters along with various noise kinds like salt and peppers, speckle, Gaussian, and realistic noise. Each one has pros and cons. There exist mechanisms for denoising images which are developed and improved using ANN, CNN, AI, fuzzy algorithms and Coccuo search. To reduce noise and improve image quality, many techniques have been developed, including wavelet threshold-based strategies, linear and nonlinear filters. The majority of existing mechanisms are not trying to mitigate the multiple noise effects. This work discusses these noise techniques and types. � 2023 American Institute of Physics Inc.. All rights reserved.