Paper
15 April 2008 Subsidence measurement and DSM extraction of IFSAR data using anisotropic diffusion and wavelet denoising filters
Kenneth Sartor, Josef De Vaughn Allen, Emile Ganthier, Mark Rahmes, Gnana Bhaskar Tenali, Samuel Kozaitis
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Abstract
The most commonly used smoothing algorithms for complex data processing are low pass filters. Unfortunately, an undesired side effect of the aforementioned techniques is the blurring of scene discontinuities in the interferogram. For Digital Surface Map (DSM) extraction and subsidence measurement, the smoothing of the scene discontinuities can cause inaccuracy in the final product. Our goal is to perform spatially non-uniform smoothing to overcome the aforementioned disadvantages. We achieve this by using an Anisotropic Non-Linear Diffuser (ANDI). Here, in this paper we will show the utility of ANDI filtering on simulated and actual Interferometric Synthetic Aperture Radar (IFSAR) data for preprocessing, subsidence measurement and DSM extraction to overcome the difficulties of typical filters. We also compare the results of the ANDI filter with a wavelet filter. Finally, we detail some of our results of the New Orleans IFSAR research project with Canadian Space Agency, NASA, and USGS. The Harris LiteSiteTM Urban 3D Modeling software is used to illustrate some of the results of our RADARSAT-1 processing.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth Sartor, Josef De Vaughn Allen, Emile Ganthier, Mark Rahmes, Gnana Bhaskar Tenali, and Samuel Kozaitis "Subsidence measurement and DSM extraction of IFSAR data using anisotropic diffusion and wavelet denoising filters", Proc. SPIE 6970, Algorithms for Synthetic Aperture Radar Imagery XV, 69700L (15 April 2008); https://doi.org/10.1117/12.777731
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KEYWORDS
Interferometric synthetic aperture radar

Digital filtering

Wavelets

Synthetic aperture radar

Image processing

3D modeling

Anisotropic diffusion

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