5 May 2008 Registration of multi-sensor remote sensing imagery by gradient-based optimization of cross-cumulative residual entropy
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Abstract
For multi-sensor registration, previous techniques typically use mutual information (MI) rather than the sum-of-the-squared difference (SSD) as the similarity measure. However, the optimization of MI is much less straightforward than is the case for SSD-based algorithms. A new technique for image registration has recently been proposed that uses an information theoretic measure called the Cross-Cumulative Residual Entropy (CCRE). In this paper we show that using CCRE for multi-sensor registration of remote sensing imagery provides an optimization strategy that converges to a global maximum with significantly less iterations than existing techniques and is much less sensitive to the initial geometric disparity between the two images to be registered.
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Mark R. Pickering, Mark R. Pickering, Yi Xiao, Yi Xiao, Xiuping Jia, Xiuping Jia, } "Registration of multi-sensor remote sensing imagery by gradient-based optimization of cross-cumulative residual entropy", Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69660U (5 May 2008); doi: 10.1117/12.777016; https://doi.org/10.1117/12.777016
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