General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
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Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2013 Vol.5(1): 88-92 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2013.V5.653

Automatic Remote-sensing Image Registration Using SURF

Rochdi Bouchiha and Kamel Besbes

Abstract—Image registration is a key, essential element in analysis of Remote sensing images. Registration is critical both for initial processing and for end-user processing of those image products for data fusion, and change detection. This paper focused on the feature-based category of image registration algorithms. Many techniques for the detection and description of images' local characteristics have been proposed to register a set of images without user intervention. However, it is unclear which descriptors are more appropriate. The descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the sensor. In our evaluation, we have separated the detector from the descriptor as their performance depends on the interest point detector used. The descriptors are compared according to their recall and runtime efficiency and this deals with several geometric and photometric changes. We also propose an extension to the SURF descriptor and the results show the effectiveness of proposed improvements compared to base SURF method. Furthermore, we observe that the SURF descriptor outperforms the others' descriptors. Finally, based on the test results, we propose an approach to register automatically remotely sensed images.

Index Terms—Automatic registration, feature-based registration, remote sensing.

The authors are with the microelectronic and instrumentation laboratory, Faculty of Sciences, University of Monastir, Tunisia (e-mail:,


Cite: Rochdi Bouchiha and Kamel Besbes, "Automatic Remote-sensing Image Registration Using SURF," International Journal of Computer Theory and Engineering vol. 5, no. 1, pp. 88-92, 2013.

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