Global registration of overlapping images using accumulative image features
This paper introduces a new feature-based image registration technique which registers images by finding rotation- and scale-invariant features and matching them using a novel feature matching algorithm based on an evidence accumulation process reminiscent of the generalized Hough transform. Once feature correspondence has been established, the transformation parameters are then estimated using non-linear least squares (NLLS) and the standard RANSAC (random sample consensus) algorithm. The technique is evaluated under similarity transforms  translation, rotation and scale (zoom) and also under illumination changes.
image registration feature matching evidence accumulation feature correspondence accumulator-based methods