Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 723-728, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-723-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
13 Sep 2017
THE IMAGE REGISTRATION OF FOURIER-MELLIN BASED ON THE COMBINATION OF PROJECTION AND GRADIENT PREPROCESSING
D. Gao, X. Zhao, and X. Pan School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, 100044 Beijing, Chin
Keywords: Non-parallel image pairs, Projection transformation, gradient preprocessing, Fourier-Mellin transformation, image registration Abstract. Image registration is one of the most important applications in the field of image processing. The method of Fourier Merlin transform, which has the advantages of high precision and good robustness to change in light and shade, partial blocking, noise influence and so on, is widely used. However, not only this method can’t obtain the unique mutual power pulse function for non-parallel image pairs, even part of image pairs also can’t get the mutual power function pulse. In this paper, an image registration method based on Fourier-Mellin transformation in the view of projection-gradient preprocessing is proposed. According to the projection conformational equation, the method calculates the matrix of image projection transformation to correct the tilt image; then, gradient preprocessing and Fourier-Mellin transformation are performed on the corrected image to obtain the registration parameters. Eventually, the experiment results show that the method makes the image registration of Fourier-Mellin transformation not only applicable to the registration of the parallel image pairs, but also to the registration of non-parallel image pairs. What’s more, the better registration effect can be obtained
Conference paper (PDF, 1689 KB)


Citation: Gao, D., Zhao, X., and Pan, X.: THE IMAGE REGISTRATION OF FOURIER-MELLIN BASED ON THE COMBINATION OF PROJECTION AND GRADIENT PREPROCESSING, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 723-728, https://doi.org/10.5194/isprs-archives-XLII-2-W7-723-2017, 2017.

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