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A coarse to fine procedure for very precise and fast subpixel image registration in frequency domain

机译:从粗到精的过程,可在频域中实现非常精确和快速的子像素图像配准

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Automatic Image Registration (AIR) is a challenging task in many image processing applications. In this paper, an AIR method is proposed which is mainly useful for registration of satellite images that are captured in the same frequency band. In this work, images are registered precisely, by means of a coarse to fine approach which is fully implemented in the frequency domain. To find a coarse estimation of motion parameters, enhanced windowing and modified Vandewalle's method are introduced. Then, accuracy of rotation estimation is increased to a fraction of a degree, by use of Taylor expansion on the log-spectrum of the images. Afterwards, accuracy of shift estimation is enhanced to sub-pixel, by using the phase difference procedure. The performance of our method is evaluated in three experiments. Results show that the suggested framework is able to estimate large and small motion parameters with high speed and great accuracy. Suggested method is also robust to noise and is superior in performance to other five methods which are being used in this paper.
机译:在许多图像处理应用程序中,自动图像配准(AIR)是一项具有挑战性的任务。在本文中,提出了一种AIR方法,该方法主要用于在相同频带中捕获的卫星图像的配准。在这项工作中,图像是通过在频域中完全实现的从粗到细的方法精确配准的。为了找到运动参数的粗略估计,引入了增强的窗口和改进的Vandewalle方法。然后,通过在图像的对数谱上使用泰勒展开,将旋转估计的精度提高到一定程度。之后,通过使用相位差过程,将偏移估计的精度提高到子像素。我们的方法的性能在三个实验中进行了评估。结果表明,所提出的框架能够快速,准确地估计大小运动参数。建议的方法对噪声也很鲁棒,并且在性能上优于本文中使用的其他五种方法。

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