Zaied Zaman, September 2017--August 2019, "Optimizing the Usage of 2D and 3D Transformations to Improve the BM3D Image Denoising Algorithm", Computer Science Department, Faculty of Science, University of Western Ontario, Canada

M.Sc. Thesis Abstract

Image denoising is one of the most important preprocessing steps before a wide range of applications such as image restoration, visual tracking, image segmentation, etc. Numerous studies have been conducted to improve the denoising performance. Block Matching and 3D (BM3D) filtering is the current state-of-the-art algorithm in image denoising and can provide better denoising performance than other existing methods. However, still, there is scope to improve the performance of BM3D. In this thesis, we have pointed out an aspect of the algorithm which can be improved and suggested an approach to improve it. We have proposed to perform a 2D and 3D transformation on certain patches rather than performing a 3D transformation on all the patches.