TR2019-079

Robust Mutual Information-Based Multi-Image Registration


    •  Liu, D., Mansour, H., Boufounos, P.T., "Robust Mutual Information-Based Multi-Image Registration", IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 2019, pp. 915-918.
      BibTeX TR2019-079 PDF
      • @inproceedings{Liu2019jul,
      • author = {Liu, Dehong and Mansour, Hassan and Boufounos, Petros T.},
      • title = {Robust Mutual Information-Based Multi-Image Registration},
      • booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
      • year = 2019,
      • pages = {915--918},
      • month = jul,
      • url = {https://www.merl.com/publications/TR2019-079}
      • }
  • MERL Contacts:
  • Research Areas:

    Computer Vision, Machine Learning, Signal Processing

Image registration is of crucial importance in image fusion such as pan-sharpening. Mutual information (MI)-based methods have been widely used and demonstrated effectiveness in registering multi-spectral or multi-modal images. However, MI-based methods may fail to converge in searching registration parameters, resulting mis-registration. In this paper, we propose an outlier robust method to improve the robustness of MI-based registration for multiple rigid transformed images. In particular, we first generate registration parameter matrices using a MI-based approach, then we decompose each parameter matrix into a low-rank matrix of inlier registration parameters and a sparse matrix corresponding to outlier parameter errors. Results of registering multi-spectral images with random rigid transformations show significant improvement and robustness of our method.