Multimodal image registration technique based on improved local feature descriptors

Shyh Wei Teng; Md. Tanvir Hossain; Guojun Lu

doi:10.1117/1.JEI.24.1.013013

12 January 2015 Multimodal image registration technique based on improved local feature descriptors

Shyh Wei Teng, Md. Tanvir Hossain, Guojun Lu

Author Affiliations +

Journal of Electronic Imaging, Vol. 24, Issue 1, 013013 (January 2015). https://doi.org/10.1117/1.JEI.24.1.013013

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.

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Shyh Wei Teng, Md. Tanvir Hossain, and Guojun Lu "Multimodal image registration technique based on improved local feature descriptors," Journal of Electronic Imaging 24(1), 013013 (12 January 2015). https://doi.org/10.1117/1.JEI.24.1.013013

Published: 12 January 2015

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