@inproceedings{ce94799f36fe4c29a2fbba574684e2b6,
title = "A Novel Fractional Order Derivate Based Log-demons with Driving Force for High Accurate Image Registration",
abstract = "Image registration methods based on Thirion's demons method update displacement field by the image gradient obtained by integer order derivate. However, the fractional order derivate is superior to integral order derivate for computing image gradient under weak texture or smooth regions. To obtain high accurate image registration, we propose a new fractional order derivate based Log-Demons with driving force. We design a new fractional order derivate convolution mask based on Gr{\"u}nwald-Letnikov (GL) definition to get accurate image gradient. Then, we integrate fractional order derivate into Log-Demons with driving force. The experiments on synthetic and MRI brain images validate that the use of fractional order derivate to compute gradient not only improves the registration accuracy but also speeds up the registration process.",
keywords = "Image registration, convolution mask, fractional order derivate, image gradient",
author = "Cheng Xu and Ying Wen and Bing He",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 ; Conference date: 12-05-2019 Through 17-05-2019",
year = "2019",
month = may,
doi = "10.1109/ICASSP.2019.8682516",
language = "英语",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1997--2001",
booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings",
address = "美国",
}