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Journal of Electronic Imaging • new

Fast separable nonlocal means
Author(s): Sanjay Ghosh; Kunal N. Chaudhury
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Paper Abstract

We propose a simple and fast algorithm called PatchLift for computing distances between patches (contiguous block of samples) extracted from a given one-dimensional signal. PatchLift is based on the observation that the patch distances can be efficiently computed from a matrix that is derived from the one-dimensional signal using lifting; importantly, the number of operations required to compute the patch distances using this approach does not scale with the patch length. We next demonstrate how PatchLift can be used for patch-based denoising of images corrupted with Gaussian noise. In particular, we propose a separable formulation of the classical nonlocal means (NLM) algorithm that can be implemented using PatchLift. We demonstrate that the PatchLift-based implementation of separable NLM is a few orders faster than standard NLM and is competitive with existing fast implementations of NLM. Moreover, its denoising performance is shown to be consistently superior to that of NLM and some of its variants, both in terms of peak signal-to-noise ratio/structural similarity index and visual quality.

Paper Details

Date Published: 25 April 2016
PDF: 14 pages
J. Electron. Imaging. 25(2) 023026 doi: 10.1117/1.JEI.25.2.023026
Published in: Journal of Electronic Imaging Volume 25, Issue 2
Show Author Affiliations
Sanjay Ghosh, Indian Institute of Science (India)
Kunal N. Chaudhury, Indian Institute of Science (India)


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