NDLI: A Robust and Fast Non-local Means Algorithm for Image Denoising

Content Provider	IEEE Xplore Digital Library
Author	Yanli Liu Jin Wang Chen Xi Yanwen Guo Qunsheng Peng
Copyright Year	2007
Description	Author affiliation: Zhejiang Univ., Hangzhou (Yanli Liu; Jin Wang; Chen Xi)
Abstract	In the paper, we propose a robust and fast image denoising method. The approach integrates both 'Non-Local means algorithm and Laplacian Pyramid. Given an image to be denoised, we first decompose it into Laplacian pyramid. Exploiting the redundancy property of Laplacian pyramid, we then perform non-local means on every level image of Laplacian pyramid. Essentially, we use the similarity of image features in Laplacian pyramid to act as weight to denoise image. Since the features extracted in Laplacian pyramid are localized in spatial position and scale, they are much more able to describe image, and computing the similarity between them is more reasonable and more robust. Also, based on the efficient Summed Square Image (SSI) scheme and Fast Fourier Transform (FFT), we present an accelerating algorithm to break the bottleneck of non-local means algorithm -similarity computation of compare windows. After speedup, our algorithm is fifty times faster than original non-local means algorithm. Experiments demonstrated the effectiveness of our algorithm.
Starting Page	30
Ending Page	30
File Size	46298
Page Count	1
File Format	PDF
ISBN	9781424415786
DOI	10.1109/CADCG.2007.4407844
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laplace equations Fast Fourier transforms Character generation Feature extraction Robustness Acceleration Image denoising
Content Type	Text
Resource Type	Article

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