A survey of image registration techniques
ACM Computing Surveys (CSUR)
Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
Performance bounds on image registration
IEEE Transactions on Signal Processing
Extended Ziv-Zakai lower bound for vector parameter estimation
IEEE Transactions on Information Theory
An FFT-based technique for translation, rotation, and scale-invariant image registration
IEEE Transactions on Image Processing
Fundamental performance limits in image registration
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Fast algorithm for multisource image registration based on geometric feature of corners
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
How Accurate Can Block Matches Be in Stereo Vision?
SIAM Journal on Imaging Sciences
Hi-index | 35.69 |
Image registration is a fundamental and important task in image processing. The goal essentially is to estimate the transformation that aligns two images. We focus on the general rigid body transformation case. In this paper, we derive the Ziv-Zakai bounds (ZZB) on image registration by assuming an uncertainty model for the rotation and translation errors, and propose to use the ZZB as a benchmark to evaluate the registration ability of an image pair. We also compare the performance of several image registration algorithms with the derived bounds when applied to several datasets.