A New Approach for SAR Images Matching Based on Optimal Gradient Filter and Multi-Window Method

Mohammad Amin Ghannadi Department of surveying and Geomatics engineering,

University of Tehran

Mohammad Saadat Seresht Department of surveying and Geomatics engineering,

University of Tehran

Mahdi Motagh Helmholtz Center Potsdam, GFZ

Akram Eftekhari Department of surveying and Geomatics engineering,

University of Tehran

Introduction

Nowadays, with the development of science and technology,

particularly the various missions in order to obtain radar images

from around the world, Discussions of these images in order to

produce a variety of terrain elevation model has important.

Digital Elevation Models (DEM) can be generate by

interferometric SAR and Radargrammetry techniques from SAR

images. SAR images matching is one the important discussed

issues in this study. Because of different geometrical phenomena

for example shadow, foreshortening and layover and also the

effect of speckle noise on the images, SAR image matching is

more complicated than optical image matching. The eefficient

algorithm for matching of SAR images is one of the key points

for improving both accuracy and efficiency. In this paper a new

Feature Base image matching technique is defined based on

optimal gradient filter and multi-window approach.

Proposed method

In this algorithm, a SAR image is firstly filtered by a speckle

suppression algorithm and then a SIFT (Scale invariant feature

transform) algorithm is used to extract feature points.

Furthermore we use pyramid scheme, expanded correlation

window and applying optimal gradient filter for compute the

cross-correlation coefficient. The maximum value of cross-

correlation coefficient defines the matching pixel. Finally, for the

evaluation this method we use the epipolar geometry and

compared the method with one of the classical methods. In this

article we use a pair of spotlight long base line TerraSAR-X

images from JAM (IRAN).

(C) (A)

The proposed method Steps

Result and discussion

This multi step algorithm can be used for coarse matching. 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 proposed algorithm.

In simple NCC method 67 points

are matched with using proposed (1) (2)

algorithm.

The face images, (1) is part of left

primary image and (2) is part of

right primary image, (3) and (4) are

OGM images.

The result shows that our proposed (3) (4)

method is superior to the classical

approach in terms of accuracy and

number of matched points.

In (5) match point with using

proposed algorithm is shown

(5)

Conclusion

The result shows that our proposed multi step image

matching is superior to the NCC methods in terms of accuracy

and number of matched points.

References

[1] Bin Pan, Peng Chen, Ming Cong, ''A New Approach on

Topographic Feature Point Extraction of SAR Imagery'', IEEE, (

2010).

[2] Bogustaw Cyganek and J. Paul Siebert, An Introduction to 3D

Computer Vision Techniques and Algorithms, pp.209-216, (2009).

[3] Brandt Tso and Paul Mather ''Classification Methods for

Remotely Sensed Data'' (2nd ed), CRC Presst, pp. 37–38.

ISBN 1-4200-9072-0, (2009).

[4] F.Fayard, S. Meric, and E. Pottier, "Generation of DEM by

radargrammetric techniques," in Geoscience and Remote

Sensing Symposium (IGARSS), IEEE International, pp. 4342-

4345, (2010).

[5] Gonzalez,R.C. and Woods, R.H, ''Digital Image Processing''

2nd ed., Prentice Hall, Upper Saddle River, NJ, (2002).

[6] Lowe, ''Distinctive image features from scale-invariant key

points'', International Journal of Computer Vision, (2004).

[7] M. Liao, H. Lin, and Z. Zhang, "Automatic registration of InSAR

data based on Least-square matching and multi-step strategy,"

Photogrammetric engineering and remote sensing, vol. 70, pp.

1139-1144, (2004).

[8] P. Paillou and M. Gelautz, "Relief reconstruction from SAR

stereo pairs: the “optimal gradient” matching method,"

Geoscience and Remote Sensing, IEEE Transactions on, vol. 37,

pp. 2099-2107, (1999 (.

[9] Stephane Meric, Frank Fayard, Eric Pottier, '' A Multi Window

Approach for Radargrammetry Improvements '', IEEE,

Geoscience and Remote Sensing , vol.49.no.10, (2011).

Images C B A Imaging Date

30/04/2012 28/04/2012 17/04/2011

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Image Type Spotlight

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Proccesing Type SSC SSC

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