Mahmud Hasan, September 2013--December 2014, "BM3D Image
Denoising Using SSIM Optimized Wiener Filter", Computer
Science Department, Faculty of Science, University of Western
M.Sc. Thesis Abstract
Image denoising is considered as a salient pre-processing in
sophisticated imaging applications. Over decades, numerous
studies have been conducted in denoising. Recently proposed
Block Matching and 3D (BM3D) Filtering added a new dimension
to the study of denoising. BM3D is the current
state-of-the-art of denoising and is capable of achieving
better denoising as compared to any other existing method.
However, the performance is not yet on the bound for image
denoising. Therefore, there is scope to improve BM3D to
achieve high quality denoising. In this thesis, to improve
BM3D, we first attempted to improve Wiener filter (the core
of BM3D) by maximizing the Structural Similarity (SSIM)
between the true and the estimated image, instead of
minimizing the Mean Square Error (MSE) between them.
Moreover, for the DC-Only BM3D profile, we introduced a 3D
zigzag thresholding. Experimental results demonstrate that
regardless of the type of the image, our proposed method
achieves better denoising than that of BM3D.