Title

Recursive non-local means filter for video denoising

Author

Redha Almahdi

Date of Award

2016

Degree Name

M.S. in Computer Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Russell C. Hardie

Abstract

In this thesis, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on Non-Local Means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patched, within a given search window. The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video processing, can be computationally demanding. Note that the size of a 3D search window is the size of the 2D search window multiplied by the number of frames being used to form the output. Exploiting a large number of frames in this manner can be prohibitive for real-time video processing. Here we propose a novel Recursive NLM (RNLM) algorithm for video processing. Our RNLM method takes advantage of recursion for cop- mutationally savings, compared with the direct 3D NLM. However, like the 3D NLM, our method is still able to exploit both spatial and temporal redundancy for improved performance, compared with 2D NLM. In our approach, the first frame is processed with single-frame NLM. Subsequent frames are estimated using a weighted sum of pixels from the current-frame and a pixel from the previous frame estimate. Only the single best matching patch from the previous estimate is incorporated into the current estimate. Several experimental results are presented here to demonstrate the efficacy of our proposed method in terms of quantitative and subjective image quality, as well as processing speed.

Keywords

Digital images Deconvolution, Digital video Quality, Image processing Digital techniques, Electrical Engineering, Computer Engineering, Denoising, Video restoration, Non-Local Means, Recursive

Rights Statement

Copyright 2016, author

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