Automatic registration of remote sensing images based on SIFT and fuzzy block matching for change detection

DOI

10.2991/ijcis.2011.4.5.13How to use a DOI?

Keywords

Registration, scale invariant feature transform, fuzzy membership, fuzzy similarity measure, change detection.

Abstract

This paper presents an automated image registration approach to detecting changes in multi-temporal remote sensing images. The proposed algorithm is based on the scale invariant feature transform (SIFT) and has two phases. The first phase focuses on SIFT feature extraction and on estimation of image transformation. In the second phase, Structured Local Binary Haar Pattern (SLBHP) combined with a fuzzy similarity measure is then used to build a new and effective block similarity measure for change detection. Experimental results obtained on multi-temporal data sets show that compared with three mainstream block matching algorithms, the proposed algorithm is more effective in dealing with scale, rotation and illumination changes.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Cai Guo-Rong
AU  - Li Shao-Zi
AU  - Wu Yun-Dong
AU  - Chen Shui-Li
AU  - Su Song-Zhi
PY  - 2011
DA  - 2011/09/01
TI  - Automatic registration of remote sensing images based on SIFT and fuzzy block matching for change detection
JO  - International Journal of Computational Intelligence Systems
SP  - 874
EP  - 885
VL  - 4
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.5.13
DO  - 10.2991/ijcis.2011.4.5.13
ID  - Guo-Rong2011
ER  -