Seeing better at night: life style, eye design and the optimum strategy of spatial and temporal summation

Abstract

Animals which need to see well at night generally have eyes with wide pupils. This optical strategy to improve photon capture may be improved neurally by summing the outputs of neighbouring visual channels (spatial summation) or by increasing the length of time a sample of photons is counted by the eye (temporal summation). These summation strategies only come at the cost of spatial and temporal resolution. A simple analytical model is developed to investigate whether the improved photon catch afforded by summation really improves vision in dim light, or whether the losses in resolution actually make vision worse. The model, developed for both vertebrate camera eyes and arthropod compound eyes, calculates the finest spatial detail perceivable by a given eye design at a specified light intensity and image velocity. Visual performance is calculated for the apposition compound eye of the locust, the superposition compound eye of the dung beetle and the camera eye of the nocturnal toad. The results reveal that spatial and temporal summation is extremely beneficial to vision in dim light, especially in small eyes (e.g. compound eyes), which have a restricted ability to collect photons optically. The model predicts that using optimum spatiotemporal summation the locust can extend its vision to light intensities more than 100,000 times dimmer than if it relied on its optics alone. The relative amounts of spatial and temporal summation predicted to be optimal in dim light depend on the image velocity. Animals which are sedentary and rely on seeing small, slow images (such as the toad) are predicted to rely more on temporal summation and less on spatial summation. The opposite strategy is predicted for animals which need to see large, fast images. The predictions of the model agree very well with the known visual behaviours of nocturnal animals.

Wide-field motion tuning in nocturnal hawkmoths

“…Instead, we suggest these reflect differences in the underlying hard wiring for spatial interactions on scales that span numerous ommatidial axes. (a) The demands of a nocturnal hovering strategy Both D. elpenor and A. atropos are active in much dimmer light than crepuscular M. sexta, and this would tend to favour lower spatial and temporal acuity (Van Hateren 1993;Warrant 1999), just as our own rod-dominated night vision, although highly sensitive, is poorly resolved and sluggish. Consistent with this result, D. elpenor and A. atropos show peak and median responses to lower spatial frequencies than M. sexta (figure 2a,c) in their motion pathways.…”

Adaptive enhancement and noise reduction in very low light-level video

“…In contrast, in nocturnal animals that move slowly temporal summation is favoured in order to maximize spatial resolution. Warrant [25] constructed a model for visual signal processing in animals that can be used to find the optimal extents of spatial and temporal summation that maximize visual performance at a given light intensity and image velocity. This biological mechanism of adaptive spatio-temporal smoothing was the initial inspiration for the work presented in this paper.…”

“…Their virtual exposures framework includes the bilateral ASTA-filter (Adaptive Spatio-Temporal Accumulation) and a tone mapping technique. The ASTAfilter, which changes to relatively more spatial filtering in favour of temporal filtering when motion is detected, is in this way related to the biological model of Warrant [25]. However, since bilateral filters are applied, the filtering is edge-sensitive and the temporal bilateral filter is additionally used for the local motion detection.…”

Elementary Motion Detection

“…Light traveling between ommatidia is focused on one rhabdomere which increases the sensitivity of the eye to light but decreases the spatial resolution. This eye design is mainly found in animals active during dim light or night (Warrant, 1999;Land, 1999).…”