Combined wavelet and curvelet denoising of SAR images

Birgir Bjorn Saevarsson*, Johannes R. Sveinsson, Jon Atli Benediktsson

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

41 Citations (Scopus)

Abstract

Synthetic aperture radar (SAR) images are corrupted by speckle noise due to random interference of electromagnetic waves. The speckle degrades the quality of the images and makes interpretations, analysis and classifications of SAR images harder. Therefore, some speckle reduction is necessary prior to the processing of SAR images. The speckle noise can be modeled as multiplicative i.i.d. Rayleigh noise. Logarithmic transformation of SAR images convert the multiplicative noise models to additive noise. In this paper, two combinations of time invariant wavelet and curvelet transforms will be used for denoising of SAR images. The first one is called the combined filtering algorithm (CFA). This method is based on a constrained optimization problem, both in the wavelet and curvelet domains. The second method is called the adaptive combined method (ACM) which uses the wavelet transform to denoise homogeneous areas and the curvelet transform to denoise areas with edges.

Original languageEnglish
Pages4235-4238
Number of pages4
Publication statusPublished - 2004
Event2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States
Duration: 20 Sep 200424 Sep 2004

Conference

Conference2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
Country/TerritoryUnited States
CityAnchorage, AK
Period20/09/0424/09/04

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