Algorithms for subpixel registration
Computer Vision, Graphics, and Image Processing
A survey of image registration techniques
ACM Computing Surveys (CSUR)
Computing occluding and transparent motions
International Journal of Computer Vision
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Correction to Construction of Panoramic Image Mosaics with Global and Local Alignment
International Journal of Computer Vision
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Symmetric Sub-Pixel Stereo Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Projective registration with difference decomposition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Precise Simultaneous Estimation of Image Deformation Parameters
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 11 - Volume 11
Sub-Pixel Estimation Error Cancellation on Area-Based Matching
International Journal of Computer Vision
Complex correlation statistic for dense stereoscopic matching
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Digital image translational and rotational motion stabilization using optical flow technique
IEEE Transactions on Consumer Electronics
A fast parametric motion estimation algorithm with illumination and lens distortion correction
IEEE Transactions on Image Processing
Performance evaluation using mandelbrot images for images registration algorithms
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Area-based matching is a fundamental image processing method that obtains displacement between image regions. In addition, the similarity interpolation method to estimate sub-pixel displacement is commonly used to enhance resolution.This paper proposes a novel 2D sub-pixel displacement estimation method based on similarity interpolation. The method estimates the displacement as an intersection point of two lines, which are approximations of zero positions of the partial derivatives with respect to each motion parameter. The proposed method requires a non-iterative computation. Furthermore, the method engenders only slightly higher calculation costs than the conventional similarity interpolation method. Moreover, the method is suitable for hardware implementation.We show that the proposed method can be extended to obtain the N-parameter of image deformation with non-iterative computation. Using similarity measures obtained at discrete positions in the parameter space, our method provides a highly accurate maximum position of the similarity in sub-sampling resolution; that position corresponds to the image deformation parameters.Experimental results using both synthetic and real images demonstrate that our method can estimate parameters more accurately than conventional methods.