Volume XL-1/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 181-184, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-181-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 181-184, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-181-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  24 Sep 2013

24 Sep 2013

USING MULTI RESOLUTION CENSUS AND RANKLET TRANSFORMATION IN LONG BASE LINE SAR IMAGE MATCHING

M. A. Ghannadi1, M. Saadat Seresht1, M. Motagh2, and A. Eftekhari1 M. A. Ghannadi et al.
  • 1Dept. of surveying and Geomatics engineering, University of Tehran, Tehran, Iran
  • 2Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Potsdam, Germany

Keywords: SAR image matching, Census transformation, Ranklet transformation, FBM

Abstract. Stereo radargrammetry is a mature technique for deriving height information from SAR image pairs. Generally height derived method by Radargrammetry consists of two stages: Images matching and space intersection. In this paper we propose a multi-step image matching algorithm founded on feature based matching. In this multi step algorithm, a SAR image is firstly filtered by a speckle suppression algorithm. a SIFT (Scale invariant feature transform) is used to extract feature points. Then we use non parametric Transformation as discriptor for the points extracted. Matching is sometimes more efficient when operating on image signals that have been transformed in some way, rather than operating on the pure intensity values themselves; In this article we use a pair of spotlight long base line TerraSAR-X images from JAM (IRAN). In a part with 700 × 700 pixels of these images 90 points are matched with using Ranklet algorithm. The mean absolute error of the corresponding points is 0.9 pixel. This match points number is 49 points with using multi resolution Census. The result shows that our proposed multi step image matching is superior to the Most FBM methods in terms of accuracy and number of matched points.