Image registration of infrared and visible based on SIFT and SURF

Huan Wu; Jianqiang Huang; Xiaoying Wang; Jianbang Jia

doi:10.1117/12.2503048

9 August 2018 Image registration of infrared and visible based on SIFT and SURF

Huan Wu, Jianqiang Huang, Xiaoying Wang, Jianbang Jia

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108062J (2018) https://doi.org/10.1117/12.2503048
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

The registration of infrared and visible images is a common multi-modal image registration, which is widely used in military, remote sensing and other fields. After describing the registration of infrared and visible images, this paper mainly introduces the SIFT(Scale Invariant Feature Transform) algorithm and SURF(Speeded Up Robust Features) algorithm based on local invariant feature in image registration. First, we extract SIFT and SURF key points of infrared and visible images respectively. Next, we use approximation nearest neighbor search method based on k-d tree algorithm to match key points. Finally, in order to improve the matching accuracy, the RANSAC algorithm is used to eliminate the error matching points. The experiment shows that for these two algorithms, the number of key points in infrared image is obviously smaller than that of visible light image. For these two images, the SURF algorithm is better than the SIFT algorithm.

Citation Download Citation

Huan Wu, Jianqiang Huang, Xiaoying Wang, and Jianbang Jia "Image registration of infrared and visible based on SIFT and SURF", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108062J (9 August 2018); https://doi.org/10.1117/12.2503048

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KEYWORDS

Infrared imaging

Infrared radiation

Visible radiation

Image registration

Feature extraction

Image processing

Convolution

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