Accuracy bounds and optimal computation of homography for image mosaicing applications

We describe a theoretically optimal algorithm for computing the homography between two images in relation to image mosaicing applications. First, we derive a theoretical accuracy bound based on a mathematical model of image noise and do simulation to confirm that our renormalization technique effectively attains that bound; our algorithm is optimal in that sense. Then, we apply our technique to mosaicing of images with small overlaps. By using real images, we show how our algorithm reduces the instability of the image mapping.