The field of view of high-resolution ophthalmoscopes that require the use of adaptive optics (AO) wavefront correction is limited by the isoplanatic patch of the eye, which varies across individual eyes and with the portion of the pupil used for illumination and/or imaging. Therefore all current AO ophthalmoscopes have small fields of view comparable to, or smaller than, the isoplanatic patch, and the resulting images have to be stitched off-line to create larger montages. These montages are currently assembled either manually, by expert human graders, or automatically, often requiring several hours per montage. This arguably limits the applicability of AO ophthalmoscopy to studies with small cohorts and moreover, prevents the ability to review a real-time captured montage of all locations during image acquisition to further direct targeted imaging. In this work, we propose stitching the images with our novel algorithm, which uses oriented fast rotated brief (ORB) descriptors, local sensitivity hashing, and by searching for a ‘good enough’ transformation, rather than the best possible, to achieve processing times of 1-2 minutes per montage of 250 images. Moreover, the proposed method produces montages which are as accurate as previous methods, when considering the image similarity metrics: normalised mutual information (NMI), and normalised cross correlation (NCC).