An integrated analysis concept for errors in image registration
Birgit Möller, Stefan Posch · Pattern Recognition and Image Analysis · 2008
Image registration is an important ingredient in a wide variety of computer vision applications. Over the years countless algorithms emerged that allow for robust registration of image sequences. Unfortunately, high quality results still cannot be guaranteed in any case. Especially in interactive online systems that strongly rely on results of unsupervised registration algorithms, techniques for automatic quality analysis and failure compensation are indispensable. In this paper we present a new concept for an integrated and fully automatic detection and analysis of errors in registration. Based on a new metric for registration quality assessment, image differences are robustly detected. In addition, a hierarchical analysis scheme is proposed that allows distinguishing between various underlying error sources, all having different impacts on a registration result and requesting for individual compensation strategies.