Alignment by Maximization of Mutual Information
International Journal of Computer Vision
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fast normalized cross correlation for defect detection
Pattern Recognition Letters
Computers and Electronics in Agriculture
IEEE Transactions on Image Processing
Thermography as non invasive functional imaging for monitoring seedling growth
Computers and Electronics in Agriculture
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Automatic registration of optical and IR images is a crucial step towards constructing an automated irrigation control system where plant water information is sensed via thermal imaging. The scene of the IR image is assumed to be completely included in the optical image and the alignment between the common scene in the two images may involve translation and rotation by a small angle, though a small scale difference may also be present. This automatic registration of data from two quite different, non-rigid imaging regimes presents several challenges, which cannot be overcome using common image processing techniques. In this paper, a fully automatic image registration algorithm for the alignment of optical and IR image pairs is described, where Pearson's cross-correlation between a pair of images serves as the similarity measure. A computationally efficient algorithm is designed and packaged as a software application. This work provides an intervention free process for extracting plant water stress information which can be fed into an automated irrigation scheduling program. The proposed algorithm is justified by the comparison of its registration performance with that of other potential algorithm techniques using several experimental data collections. Our results demonstrate the effectiveness of the proposed algorithm and efficiency of its application to the registration of IR and optical images.