- Title
- Multimodal image registration technique based on improved local feature descriptors
- Creator
- Teng, Shyh; Hossain, Tanvir; Lu, Guojun
- Date
- 2015
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/76483
- Identifier
- vital:7562
- Identifier
-
https://doi.org/10.1117/1.JEI.24.1.013013
- Identifier
- ISSN:1017-9909
- Abstract
- Multimodal image registration has received significant research attention over the past decade, and the majority of the techniques are global in nature. Although local techniques are widely used for general image registration, there are only limited studies on them for multimodal image registration. Scale invariant feature transform (SIFT) is a well-known general image registration technique. However, SIFT descriptors are not invariant to multimodality. We propose a SIFT-based technique that is modality invariant and still retains the strengths of local techniques. Moreover, our proposed histogram weighting strategies also improve the accuracy of descriptor matching, which is an important image registration step. As a result, our proposed strategies can not only improve the multimodal registration accuracy but also have the potential to improve the performance of all SIFT-based applications, e.g., general image registration and object recognition.
- Publisher
- SPIE
- Relation
- Journal of Electronic Imaging Vol. 24, no. 1 (2015), p.
- Rights
- Copyright © SPIE and IS&T
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; Key-point description; Image registration; Object recognition; Descriptor matching; Image registration techniques; Keypoints; Multimodal image registration; Multimodal registration; Scale invariant feature transforms; SIFT descriptors; Weighting strategies; Medical imaging
- Full Text
- Reviewed
- Hits: 2833
- Visitors: 3186
- Downloads: 420
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Published version | 10 MB | Adobe Acrobat PDF | View Details Download |