Subsidence measurement and DSM extraction of IFSAR data using anisotropic diffusion and wavelet denoising filters
Proceedings of SPIE - the International Society for Optical Engineering
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 LiteSite™ Urban 3D Modeling software is used to illustrate some of the results of our RADARSAT-1 processing.
Sartor, K., De Vaughn Allen, J., Ganthier, E., Rahmes, M., Tenali, G. B., & Kozaitis, S. (2008). Subsidence measurement and DSM extraction of IFSAR data using anisotropic diffusion and wavelet denoising filters. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, 6970 doi:10.1117/12.777731