Natural Image Denoising: Optimality and Inherent Bounds

10 years 8 months ago
Natural Image Denoising: Optimality and Inherent Bounds
The goal of natural image denoising is to estimate a clean version of a given noisy image, utilizing prior knowledge on the statistics of natural images. The problem has been studied intensively with considerable progress made in recent years. However, it seems that image denoising algorithms are starting to converge and recent algorithms improve over previous ones by only fractional dB values. It is thus important to understand how much more can we still improve natural image denoising algorithms and what are the inherent limits imposed by the actual statistics of the data. The challenge in evaluating such limits is that constructing proper models of natural image statistics is a long standing and yet unsolved problem. To overcome the absence of accurate image priors, this paper takes a non parametric approach and represents the distribution of natural images using a huge set of 1010 patches. We then derive a simple statistical measure which provides a lower bound on the optimal Baye...
Anat Levin, Boaz Nadler
Added 20 Mar 2011
Updated 29 Apr 2011
Type Journal
Year 2011
Where CVPR
Authors Anat Levin, Boaz Nadler
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