Abstract
The composition of retinal images presents high demands to the applied methods. Substantially different lighting conditions between the images, glarings and fade-outs within one image, large textureless regions and non-linear distortions are the main challenges. We present a fully automatic algorithm for the registration of images of the human retina and their overlay to wide field montage images combining area-based and point-based approaches. The algorithm combines an area-based as well as a point-based approach for determining similarities between images. Various measures of similarity were investigated, where the normalized correlation coefficient was superior compared to the usual definitions of transinformation. The transformation of the images was based on a quadratic model that can be derived from the spherical surface of the retina. This model was compared to four other parameterized transformations and performed best both visually and quantitatively in terms of measured misregistration. Problems may occur if the images are extremely defocused or contain very little relevant structural information.
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