A survey of image registration techniques
ACM Computing Surveys (CSUR)
Proceedings of the seventh annual ACM symposium on Parallel algorithms and architectures
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
GA-Based Parallel Image Registration on Parallel Clusters
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Data Exchanges and Interoperability in Distributed Earth Science Information Systems
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
First Evaluation of Parallel Methods of Automatic Global Image Registration Based on Wavelets
ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
IEEE Transactions on Image Processing
Remote sensing image registration techniques: a survey
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
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Image registration is a classical problem that addresses the problem of finding a geometric transformation that best aligns two images. Since the amount of multisensor remote sensing imagery are growing tremendously, the search for matching transformation with mutual information is very time-consuming and tedious, and fast and automatic registration of images from different sensors has become critical in the remote sensing framework. So the implementation of automatic mutual information based image registration methods on high performance machines needs to be investigated. First, this paper presents a parallel implementation of a mutual information based image registration algorithm. It takes advantage of cluster machines by partitioning of data depending on the algorithm's peculiarity. Then, the evaluation of the parallel registration method has been presented in theory and in experiments and shows that the parallel algorithm has good parallel performance and scalability.