A Practical Guide to Multi-Image Alignment

Aguerrebere, Cecilia; Delbracio, Mauricio; Bartesaghi, Alberto; Sapiro, Guillermo

doi:10.1109/icassp.2018.8461588

Cited by 4 publications

(1 citation statement)

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“…Image registration is a process of image matching and transformation of two or more different images. It is widely used in such fields as panoramic image splicing [1,2], high dynamic range imaging [3], simultaneous localization and mapping (SLAM) [4], and so on.…”

Section: Introductionmentioning

confidence: 99%

Image Registration Algorithm Based on Convolutional Neural Network and Local Homography Transformation

Wang

Jiang

et al. 2020

Applied Sciences

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In order to overcome the poor robustness of traditional image registration algorithms in illuminating and solving the problem of low accuracy of a learning-based image homography matrix estimation algorithm, an image registration algorithm based on convolutional neural network (CNN) and local homography transformation is proposed. Firstly, to ensure the diversity of samples, a sample and label generation method based on moving direct linear transformation (MDLT) is designed. The generated samples and labels can effectively reflect the local characteristics of images and are suitable for training the CNN model with which multiple pairs of local matching points between two images to be registered can be calculated. Then, the local homography matrices between the two images are estimated by using the MDLT and finally the image registration can be realized. The experimental results show that the proposed image registration algorithm achieves higher accuracy than other commonly used algorithms such as the SIFT, ORB, ECC, and APAP algorithms, as well as another two learning-based algorithms, and it has good robustness for different types of illumination imaging.

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