A survey of image registration techniques
ACM Computing Surveys (CSUR)
Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization
ACM Transactions on Mathematical Software (TOMS)
Alignment Using Distributions of Local Geometric Properties
IEEE Transactions on Pattern Analysis and Machine Intelligence
Immune network modelling in design optimization
New ideas in optimization
ICP Registration Using Invariant Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
The Correlation Ratio as a New Similarity Measure for Multimodal Image Registration
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
An Evolutionary Immune Network for Data Clustering
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
An artificial immune system approach to document clustering
Proceedings of the 2005 ACM symposium on Applied computing
Medical Image Registration Based on More Features and Artificial Immune Algorithm
JCAI '09 Proceedings of the 2009 International Joint Conference on Artificial Intelligence
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Fast parametric elastic image registration
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Image registration is the process that allows geometric alignment of two images by determining the transformation that provides the most accurate match between two images. It is a crucial underlying process in many remote sensing applications such as multi-temporal classification, change detection, environmental monitoring, cloud removal, video geo-registration and map updating, etc. In this paper, we introduce a new approach for automated image registration without the need of sensors parameters and control points. The main characteristic of the algorithm is the use of a powerful search strategy based on artificial immune system AIS and mutual information as similarity measure. The method was implemented and tested using a variety of high-resolution satellite imagery such as Ikonos 0.8 metre resolution, QuickBird 0.8 m and WorldView-2 0.5 metres respectively taken from Brazil, Iran and China. Experimental results and comparative studies demonstrate the effectiveness of the proposed approach for registration of high resolution satellite images.