Iterative fitting after elastic registration: An efficient strategy for accurate estimation of parametric deformations
Refereed conference paper presented and published in conference proceedings

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其它資訊
摘要We propose an efficient method for image registration based on iteratively fitting a parametric model to the output of an elastic registration. It combines the flexibility of elastic registration - able to estimate complex deformations - with the robustness of parametric registration - able to estimate very large displacement. Our approach is made feasible by using the recent Local All-Pass (LAP) algorithm; a fast and accurate filter-based method for estimating the local deformation between two images Moreover, at each iteration we fit a linear parametric model to the local deformation which is equivalent to solving a linear system of equations (very fast and efficient). We use a quadratic polynomial model however the framework can easily be extended to more complicated models. The significant advantage of the proposed method is its robustness to model mis-match (e.g. noise and blurring). Experimental results on synthetic images and real images demonstrate that the proposed algorithm is highly accurate and outperforms a selection of image registration approaches.
著者Zhang XX, Gilliam C, Blu T
會議名稱24th IEEE International Conference on Image Processing (ICIP)
會議開始日17.09.2017
會議完結日20.09.2017
會議地點Beijing
會議國家/地區中國
期刊名稱2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
會議論文集題名2017 24th IEEE International Conference on Image Processing (ICIP)
出版作品名稱2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
出版年份2017
出版社IEEE
頁次1492 - 1496
國際標準書號978-1-5090-2175-8
國際標準期刊號1522-4880
語言英式英語
關鍵詞Image registration,Iterative fitting,Elastic registration,Parametric registration,Local All-Pass filters
Web of Science 學科類別Imaging Science & Photographic Technology;Imaging Science & Photographic Technology

上次更新時間 2020-21-11 於 02:47