Superposition eyes produce real, erect images on a retina separated from the optical elements by a clear zone. In refracting superposition eyes, the optical elements may lens cylinders or corneal lens/lens cylinder combinations. These act as inverting telescopes. Resolution can as good as in an apposition eye with similar-sized facets; the sensitivity is usually much greater than in an apposition eye of the same size.
Double eyes, with different resolution in the two parts; occur in both insects and crustaceans. Superposition eyes often exhibit eye glow when they are from the viewing direction; which results from a reflecting tapetum behind the retina. Butterflies have afocal apposition eyes. This system is closely related to refracting superposition; except that the telescopic elements have a much higher magnification than those of moth superposition eyes.
Ordinary apposition eyes
Light enters the rhabdom as a parallel beam, rather than as a focused image as in ordinary apposition eyes. Shrimps, crayfish, and lobsters have superposition eyes in which the optical elements are not lenses but mirrors. The reflecting surfaces are at right angles to the eye surface and form a square array.
They have introduced an efficient method to superimpose eye fundus images from persons with diabetes screened over many years for diabetic retinopathy. The method is fully automatic and robust to camera changes and color variations across the images both in space and time. All the stages of the process are designing for longitudinal analysis of cohort public health databases where retinal examinations are at approximately yearly intervals.
The eye fundus images
In this paper, a method is presented for superimposition (i.e. registration); of eye fundus images from persons with diabetes screened over many years for diabetic retinopathy. The method is fully automatic and robust to camera changes and color variations across the images both in space and time. All the stages of the process are designed for longitudinal analysis of cohort public health databases where retinal examinations are made at approximately yearly intervals.
The method relies on a model correcting two radial distortions and an affine transformation between pairs of images which is robustly fitted on salient points. Each stage involves linear estimators followed by non-linear optimization. The model of image warping is also invertible for fast computation.
The method has validated on a simulated montage and on public health databases with 69 patients with high-quality images (271 pairs acquired mostly with different types of camera and 268 pairs acquired mostly with the same type of camera) with success rates of 92% and 98% and five patients (20 pairs); with low quality images with a success rate of 100%. Compared to two state-of-the-art methods ours gives better results.