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An adaptive SAR image speckle reduction algorithm based on undecimated wavelet transform and non-local means

  • Fan Yang
  • , Ze Yu
  • , Chunsheng Li
  • Beihang University

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

Abstract

Speckle noise is an inherent problem in synthetic aperture radar (SAR) images. Recently, non-local (NL) means performs well in speckle reduction. However, there exist two issues in traditional NL means. Speckle noise and strong targets would affect the correctness, thus resulting in over smoothing and speckles unchanged. In this paper, an improved algorithm combined with wavelet transform and adaptive NL means is proposed. First, linear minimum mean-square error (LMMSE) filtering in undecimated wavelet domain is operated and we get a "clean" image. Second, we eliminate the influence of strong targets adaptively when similarity is derived. At last, under the help of similarity, original image rather than the "clean" image is filtered. Proposed method performs better in both speckle reduction and strong targets preserving compared with the traditional method.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1030-1033
Number of pages4
ISBN (Electronic)9781509033324
DOIs
StatePublished - 1 Nov 2016
Event2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November
ISSN (Electronic)2153-7003

Conference

Conference2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • Non-local means
  • adaptivity
  • despeckling
  • undecimated wavelet

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