Please use this identifier to cite or link to this item: https://repositorio.unifesp.br/handle/11600/55295
Title: BMINSAR: A NOVEL APPROACH FOR INSAR PHASE DENOISING BY CLUSTERING AND BLOCK MATCHING
Authors: Barreto, Thiago L. M.
Rosa, Rafael A. S.
Wimmer, Christian
Moreira, Joao R.
Bins, Leonardo S.
Almeida, Jurandy [UNIFESP]
Cappabianco, Fabio A. M. [UNIFESP]
Keywords: Remote Sensing
InSAR
BM3D
Non Local Means
Interferometric Phase Denoising
Issue Date: 2017
Publisher: IEEE
Citation: 2017 Ieee International Geoscience And Remote Sensing Symposium (Igarss). New York, v. , p. 2357-2360, 2017.
Abstract: We present a novel approach for phase denoising in Interferometric Synthetic Aperture Radar (InSAR) images, named as Block-Matching InSAR (BMInSAR). It uses k-means clustering to solve the block matching similarity search problem, thus simplifying preprocessing steps and filtering several reference-blocks at once. Also, we propose a novel methodology based on ground-truth GPS measurements to assess the filtering quality of Digital Elevation Models (DEMs) derived from a pair of Very High-Resolution (VHR) SAR complex images. Our dataset was obtained by X-Band airborne sensor OrbiSAR-2 from BRADAR. BMInSAR significantly outperforms the state-of-the-art filtering methods in both accuracy and execution time. After filtering with BMInSAR, we achieved an accuracy of 21 cm in the resulting DEM of a homogeneous lawn area, which is quite similar to that obtained by LiDAR technology.
URI: https://repositorio.unifesp.br/handle/11600/55295
ISSN: 2153-6996
Other Identifiers: https://doi.org/10.1109/IGARSS.2017.8127464
Appears in Collections:Trabalho apresentado em evento

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