Eliminating Effect of Image Border with Image Periodic Decomposition for Phase Correlation Based Image Registration

In remote sensing community, accurate image registration is the basement of the subsequent application of remote sensing images. Phase correlation based image registration has drawn extensive attention due to its high accuracy and high efficiency. But the effect of image border corrupted its registration accuracy and success rate. Currently, the main solution is blurring off the border of image by weighting window function with reference and sensed image. However, the approach also inevitably filters out non-border information of an image, which is useful to image registration based on phase correlation. In this paper, another way of thinking to eliminate the effect of image border is proposed, namely decomposing the image into two images, one is periodic image and the other is smooth image. Engulfing the original image by the periodic one has no direct effect on the image border due to applying Fourier Transform. The smooth image is analogous to an error image, which has little information except at the border. The novel algorithm of eliminating the image border can improve the success rate and registration accuracy of phase correlation based image registration. To illustrate its superiority, we showed the corresponding magnitude of Fourier Transform of image visually and compared two measurements with other three state-of-the-art algorithms quantitatively.