Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3, 39-44, 2014
https://doi.org/10.5194/isprsarchives-XL-3-39-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
11 Aug 2014
SAR Image Segmentation Using Morphological Attribute Profiles
M. Boldt1,2, A. Thiele1,2, K. Schulz1, and S. Hinz2 1Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, Germany
2Institute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology (KIT) , Karlsruhe, Germany
Keywords: Synthetic Aperture Radar, SAR, TerraSAR-X, Object-Based Image Analysis, OBIA, Mathematical Morphology, Attribute Profiles, AP, Differential Attribute Profiles, DAP, segmentation Abstract. In the last years, the spatial resolution of remote sensing sensors and imagery has continuously improved. Focusing on spaceborne Synthetic Aperture Radar (SAR) sensors, the satellites of the current generation (TerraSAR-X, COSMO-SykMed) are able to acquire images with sub-meter resolution. Indeed, high resolution imagery is visually much better interpretable, but most of the established pixel-based analysis methods have become more or less impracticable since, in high resolution images, self-sufficient objects (vehicle, building) are represented by a large number of pixels. Methods dealing with Object-Based Image Analysis (OBIA) provide help. Objects (segments) are groupings of pixels resulting from image segmentation algorithms based on homogeneity criteria. The image set is represented by image segments, which allows the development of rule-based analysis schemes. For example, segments can be described or categorized by their local neighborhood in a context-based manner.

In this paper, a novel method for the segmentation of high resolution SAR images is presented. It is based on the calculation of morphological differential attribute profiles (DAP) which are analyzed pixel-wise in a region growing procedure. The method distinguishes between heterogeneous and homogeneous image content and delivers a precise segmentation result.

Conference paper (PDF, 1628 KB)


Citation: Boldt, M., Thiele, A., Schulz, K., and Hinz, S.: SAR Image Segmentation Using Morphological Attribute Profiles, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3, 39-44, https://doi.org/10.5194/isprsarchives-XL-3-39-2014, 2014.

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