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Local jet based similarity for NL-means filtering

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)

Abstract

Reducing the dimension of local descriptors in images is useful to perform pixels comparison faster. We show here that, for computing the NL-means denoising filter, image patches can be favourably replaced by a vector of spatial derivatives (local jet), to calculate the similarity between pixels. First, we present the basic, limited range implementation, and compare it with the original NL-means. We use a fast estimation of the noise variance to automatically adjust the decay parameter of the filter. Next, we present the unlimited range implementation using nearest neighbours search in the local jet space, based on a binary search tree representation.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2668-2671
Number of pages4
ISBN (Print)9780769541099
DOIs
Publication statusPublished - 1 Jan 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Keywords

  • Image denoising
  • Local jet
  • NL-mean
  • Nearest neighbour search

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