Dynamic subsampling for image registration speedup using the mutual information variance estimate

Intensity based image registration methods are necessary in situations where feature point based methods fail, e.g multispectral images or images with repetitive textures. However the higher robustness comes at the cost of being slower than the feature point alternative. This problem can be alleviated by subsampling the pixels used to calculate the intensity matching criterion. Unfortunately there are no guidelines for the amount of allowed subsampling. In this paper we present a model for a lower bound on the number of pixel samples in image sets to keep a certain confidence about the correctness of the result, using the variance on the estimated mutual information value. With this model we can speed up the intensity based registration while remaining confident about getting correct results.