| Full text | |
| Author(s): |
Barreto, Thiago L. M.
;
Rosa, Rafael A. S.
;
Wimmer, Christian
;
Moreira, Joao R.
;
Bins, Leonardo S.
;
Almeida, Jurandy
;
Cappabianco, Fabio A. M.
;
IEEE
Total Authors: 8
|
| Document type: | Journal article |
| Source: | 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS); v. N/A, p. 4-pg., 2017-01-01. |
| 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. (AU) | |
| FAPESP's process: | 16/06441-7 - Semantic information retrieval in large video databases |
| Grantee: | Jurandy Gomes de Almeida Junior |
| Support Opportunities: | Regular Research Grants |