Volume 4, Issue 5, September 2011, Pages 874 - 885
Automatic registration of remote sensing images based on SIFT and fuzzy block matching for change detection
Cai Guo-Rong, Li Shao-Zi, Wu Yun-Dong, Chen Shui-Li, Su Song-Zhi
Received 11 March 2011, Accepted 23 June 2011, Available Online 1 September 2011.
- https://doi.org/10.2991/ijcis.2011.4.5.13How to use a DOI?
- Registration, scale invariant feature transform, fuzzy membership, fuzzy similarity measure, change detection.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 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 - https://doi.org/10.2991/ijcis.2011.4.5.13 ID - Guo-Rong2011 ER -