Subpixel Registration With Gradient Correlation

作者：Tzimiropoulos Georgios^*; Argyriou Vasileios; Stathaki Tania

来源：IEEE Transactions on Image Processing, 2011, 20(6): 1761-1767.

DOI：10.1109/TIP.2010.2095867

• Gradient correlation methods
• subpixel image registration

We address the problem of subpixel registration of images assumed to be related by a pure translation. We present a method which extends gradient correlation to achieve subpixel accuracy. Our scheme is based on modeling the dominant singular vectors of the 2-D gradient correlation matrix with a generic kernel which we derive by studying the structure of gradient correlation assuming natural image statistics. Our kernel has a parametric form which offers flexibility in modeling the functions obtained from various types of image data. We estimate the kernel parameters, including the unknown subpixel shifts, using the Levenberg-Marquardt algorithm. Experiments with LANDSAT and MRI data show that our scheme outperforms recently proposed state-of-the-art phase correlation methods.

• 出版日期2011-6