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Neural network based image registration using synthetic reference image rotation

Publisher : Lecture Notes in Computational Vision and Biomechanics

Year : 2019

Abstract :

Typical image registration techniques use a set of features from a target and reference images and search in the affine transformation space using a similarity metric. Neural Networks typically have employed two choices—geometric transformations to find correlation between images and a similarity metric. In this paper, however, we have proposed and employed a simple and effective method for image registration using neural networks. The image registration has been formulated as a classification problem. By generating and learning exhaustive synthetic reference image transformations appropriate re-transformation for target image is computed for effective registration. The proposed work is tested on satellite imagery. © Springer Nature Switzerland AG 2019.

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