Abstract
Image registration is a significant step in a wide range of practical applications and it is a fundamental problem in various computer vision tasks. In this paper, we propose a highly accurate and fast parametric registration method for mobile phone photos. The proposed algorithm is based on a fast and accurate elastic registration algorithm, the Local All-Pass (LAP) algorithm, which performs in a coarse-to-fine manner. At each iteration, the LAP displacement field is fitted by a parametric model. Thus the image registration problem is equivalent to finding a few parameters to describe the displacement field. The fitting step can be performed very efficiently by solving a linear system of equations. In terms of the fitting model, it is easy to change the type of models to do the parametric fitting for specific applications. Experimental results on both synthetic and real images demonstrate the high accuracy and computational efficiency of the proposed algorithm.
Original language | English |
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Title of host publication | 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings |
Publisher | IEEE Computer Society Press |
Pages | 1312-1316 |
Number of pages | 5 |
ISBN (Electronic) | 9781538662496 |
DOIs | |
Publication status | Published - Sept 2019 |
Event | 26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan, Province of China Duration: 22 Sept 2019 → 25 Sept 2019 |
Publication series
Name | Proceedings - International Conference on Image Processing, ICIP |
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Volume | 2019-September |
ISSN (Print) | 1522-4880 |
Conference
Conference | 26th IEEE International Conference on Image Processing, ICIP 2019 |
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Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 22/09/19 → 25/09/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Elastic registration
- Image registration
- Local All-Pass filters
- Parametric fitting
- Quadratic polynomial function
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing