SUMMARYArea-based matching is a fundamental image processing operation to obtain the displacement between images. Also, the similarity interpolation method to estimate subpixel displacement is commonly used to enhance resolution. Conventionally, similarity interpolation estimation is performed by assuming that the horizontal and vertical displacements are independent. Almost no investigations of estimation error over the conventional method have been made, but it is inferred experientially that subpixel estimation with image interpolation or gradient-based methods is more precise than the similarity interpolation method. This paper proposes a novel 2D subpixel displacement estimation method based on similarity interpolation through modeling of 2D self-similarity. The proposed method requires no "a priori" knowledge of 2D similarity and no images at all. It adopts no iteration. Furthermore, the proposed method entails only slightly higher calculation costs than the conventional similarity interpolation method. The proposed method can obtain more precise estimation than both the conventional similarity interpolation method and the image interpolation method using comparison of subpixel estimation accuracy. An experiment using actual images demonstrates the effectiveness of the proposed method.