International Journal of Information Technology & Computer Science ( IJITCS )
‘In this paper, we propose a novel remote sensing image registration method based on the combination of local Scale Invariant Feature Transform (SIFT) description and the spatial relationship of matching features, which is accomplished based on Canonical Correlation Analysis (CCA). Compared with SIFT which is often impacted by similar structures, the retrofitted SIFT algorithm is more robust and accurate. The method proceeds in two stages. In the first stage a putative set of correspondences is obtained based on distances between SIFT feature descriptors. In the second stage the matches are refined by imposing spatial relationship of matching features by means of CCA and the incorrect matches are rejected as outliers. By employing the CCA algorithm, a more robust and accurate registration result is achieved at the expense of moderate computational complexity. Experimental results show an overall significant reduction of the mismatches while maintaining a high rate of correct matches.
: Canonical Correlation Analysis (CCA); Mismatching; Image registration; Scale Invariant Feature Transform (SIFT)
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