Paper
28 September 2009 Automatic registration of SAR and optical imagery using cross-cumulative residual entropy
Author Affiliations +
Abstract
It is often useful to fuse remotely sensed data taken from different sensors. However, before this multi-sensor data fusion can be performed the data must first be registered. In this paper we investigate the use of a new information-theoretic similarity measure known as Cross-Cumulative Residual Entropy (CCRE) for multi-sensor registration of remote sensing imagery. The results of our experiments show that the CCRE registration algorithm was able to automatically register images captured with SAR and optical sensors with 100% success rate for initial maximum registration errors of up to 30 pixels and required at most 80 iterations in the successful cases. These results demonstrate a significant improvement over a recent mutual-information based technique.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark R. Pickering, Yi Xiao, and Xiuping Jia "Automatic registration of SAR and optical imagery using cross-cumulative residual entropy", Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770W (28 September 2009); https://doi.org/10.1117/12.830046
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Cited by 1 scholarly publication.
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KEYWORDS
Image registration

Synthetic aperture radar

Sensors

Optimization (mathematics)

Image processing

Motion estimation

Image fusion

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