CMRT09

Stilla, Uwe

Bibliographic data

Monograph

Persistent identifier:: 856955019

Author:: Stilla, Uwe

Title:: CMRT09

Sub title:: object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]

Scope:: X, 234 Seiten

Year of publication:: 2009

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856955019

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: CURVELET APPROACH FOR SAR IMAGE DENOISING, STRUCTURE ENHANCEMENT, AND CHANGE DETECTION Andreas Schmitt, Birgit Wessel, Achim Roth

Document type:: Monograph

Structure type:: Chapter

In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 155 (a) Color composite • •V ■ ii-'\ ÀŸ- (c) Detected changes 1 - 2 № y. Jr 1 7 (b) Detected changes 1-3 f < ■ .. 7 . X 7# ,/yr* (d) Detected changes 2-3 (a) Optical image ©GoogleEarth (b) SAR image 1 Figure 5: Construction site near "Donnersberger Briicke” (1: 30.03.2008,2: 22.09.2008,3: 17.03.2009) construction sites along the railway tracks where new residential and office buildings are planned. As radiometrically enhanced products they share a pixel spacing of 1.25 m on ground. The color composite (Fig. 6(a), 1:R, 2:G, 3:B) shows many colored regions, that help to identify the construction sites. But it is still impossible to interpret these changes. Fig. 6(b) indicates the detected changes by the curvelet approach. Many green struc tures stand for an increase in reflectivity over the period of one year. A higher reflectivity refers to new objects, e.g. walls or houses while the darkened regions (in red) usually refer to strong scatterers that have disappeared, e.g. scaffoldings. At the bot tom left there are sequences of green and red lines which can be interpreted as new buildings. One the one hand a new risen build ing causes a higher reflectivity (green), on the other hand it also causes new radar shadows (red). Some long green or red lines can be perceived in the middle of the image that refer to trains in the railway depots. Having a look at Fig. 6(c) and 6(d) much more small structures especially at the top right appear. Most of these are marked in red in Fig. 6(c) and in green in Fig. 6(d), so that they compensate each other over the whole year (Fig. 6(b)). Figure 6: Change detection (cf. Fig. 5) These changes are mainly found in the ’’Hirschgarten” park (see Fig. 5(a) at the top right) comparing the images acquired in spring with those acquired in fall. As these changes are restricted to nat ural surroundings, they supposedly refer to seasonal changes in the reflectivity by the tree’s growth. The blank branches in March cause a much higher reflectivity in the co-polarized channel than the leaves in September. Again the curvelet approach produces a change image with no single pixel disturbances. Changes in the underlying structures are emphasized. Unfortunately it is a diffi cult task to distinguish man-made changes from seasonal changes in the natural surrounding without a high resolution land cover mask. 6 CONCLUSION A new approach for SAR image enhancement and change de tection based on the curvelet transform has been proposed and applied to TerraSAR-X data of the city center of Munich. As in put data any amplitude image can be used, for change detection two equally sized and co-registered images are necessary. Radar

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