3d Object Coordinates Extraction by Radargrammetry and Multi Step Image Matching

Abstract

Nowadays by high resolution SAR imaging systems as Radarsat-2, TerraSAR-X and COSMO-skyMed, three-dimensional terrain data extraction using SAR images is growing. InSAR and Radargrammetry are two most common approaches for removing 3D object coordinate from SAR images. Research has shown that extraction of terrain elevation data using satellite repeat pass interferometry SAR technique due to atmospheric factors and the lack of coherence between the images in areas with dense vegetation cover is a problematic. So the use of Radargrammetry technique can be effective. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-stage algorithm founded on the combination of feature based and area based image matching. Then the RPCs that calculate for each images use for extracting 3D coordinate in matched points. At the end, the coordinates calculating that compare with coordinates extracted from 1 meters DEM. The results show root mean square errors for 360 points are 3.09 meters. We use a pair of spotlight TerraSAR-X images from JAM (IRAN) in this article.

Optimal texture image reconstruction method for improvement of SAR image matching

“…Matching approaches are classified into two main categories: area‐based matching (ABM) and feature‐based matching (FBM) methods [7]. However, in some applications, hybrid methods are considered as well [11, 12]. ABM methods are more appropriate for dense matching, while FBM methods are the most suitable for sparse matching [13].…”

Geographical analysis of forest types based on a digital elevation model generated from synthetic aperture radar

“…It is used in many research areas including, modelling water flow for hydrology, terrain analysis in geomorphology and physical geography, landscape development, land use studies and forest analysis. The DEM is usually generated from optical stereo image pairs, interferometric SAR images and LiDAR data [1]. In recent years, space SAR interferometry has been increasingly used for a DEM generation [2], because it is has all-day and all-weather working abilities, wide spatial coverage, fine spatial resolution, high measurement precision and makes redundant ground instrumentation [3].…”

Efficient method for outlier removal in SAR image matching based on epipolar geometry

“…The goal of matching is the detection of corresponding points in image pairs. The matching process is an important step in radargrammetry [1–6], interferometry [7, 8], image registration [9–15], image fusion, and change detection [9]. The matching process in synthetic aperture radar (SAR) imagery has complexities owing to geometric distortions such as layover and foreshortening.…”