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Curvelet Approach for SAR Image Denoising, Structure Enhancement, and Change Detection

Schmitt, Andreas and Wessel, Birgit and Roth, Achim (2009) Curvelet Approach for SAR Image Denoising, Structure Enhancement, and Change Detection. City Models, Roads and Traffic (CMRT), 03.-04.09.2009, Paris (France). ISSN 1682-1777

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Abstract

In this paper we present an alternative method for SAR image denoising, structure enhancement, and change detection based on the curvelet transform. Curvelets can be denoted as a two dimensional further development of the well-known wavelets. The original image is decomposed into linear ridge-like structures, that appear in different scales (longer or shorter structures), directions (orientation of the structure) and locations. The influence of these single components on the original image is weighted by the corresponding coefficients. By means of these coefficients one has direct access to the linear structures present in the image. To suppress noise in a given SAR image weak structures indicated by low coefficients can be suppressed by setting the corresponding coefficients to zero. To enhance structures only coefficients in the scale of interest are preserved and all others are set to zero. Two same-sized images assumed even a change detection can be done in the curvelet coefficient domain. The curvelet coefficients of both images are differentiated and manipulated in order to enhance strong and to suppress small scale (pixel-wise) changes. After the inverse curvelet transform the resulting image contains only those structures, that have been chosen via the coefficient manipulation. Our approach is applied to TerraSAR-X High Resolution Spotlight images of the city of Munich. The curvelet transform turns out to be a powerful tool for image enhancement in fine-structured areas, whereas it fails in originally homogeneous areas like grassland. In the change detection context this method is very sensitive towards changes in structures instead of single pixel or large area changes. Therefore, for purely urban structures or construction sites this method provides excellent and robust results. While this approach runs without any interaction of an operator, the interpretation of the detected changes requires still much knowledge about the underlying objects.

Document Type:Conference or Workshop Item (Speech, Paper)
Title:Curvelet Approach for SAR Image Denoising, Structure Enhancement, and Change Detection
Authors:
AuthorsInstitution or Email of Authors
Schmitt, AndreasAndreas.Schmitt@dlr.de
Wessel, BirgitBirgit.Wessel@dlr.de
Roth, AchimAchim.Roth@dlr.de
Date:September 2009
Refereed publication:Yes
In ISI Web of Science:No
Page Range:pp. 151-156
ISSN:1682-1777
Status:Published
Keywords:SAR, Imagery, Structure, Extraction, Change Detection, Method, Urban
Event Title:City Models, Roads and Traffic (CMRT)
Event Location:Paris (France)
Event Type:international Conference
Event Dates:03.-04.09.2009
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Anwendungen Erdbeobachtung - HGF-Kooperation EOS (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Environment and Security
Deposited By: Andreas Schmitt
Deposited On:06 Apr 2010 10:45
Last Modified:12 Dec 2013 20:49

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