Overview
Most blindness registrations in the UK are due to age-related macular degeneration (AMD). The most common form of AMD (‘dry’ AMD) affects 9 in 10 people with the condition, but there is no treatment yet.
In AMD, light-sensitive cells die in a part of the eye called the macula. It’s the central part of the retina and we use it for seeing in fine detail, recognising faces and looking straight ahead. In the early stages, visual aids that make things look bigger or brighter can help people see better. But this doesn’t work so well in the later stages when central vision has gone.
AMD does not affect side (peripheral) vision, however. Which means that people are encouraged to learn how to make the most of this remaining vision. The trouble is that our peripheral vision isn’t very detailed and it’s harder to keep your eyes fixed on where you want to look.
Digital imaging technology makes use of what’s known as ‘super-resolution’ to improve picture quality. Moving targets are seen more clearly that stationary ones, so the technique makes use of small shifts in an image. There is also recent evidence that people can benefit from movement in their peripheral vision too, but it’s not clear how or why.
So in this project the team is testing people with and without AMD to find out how well people can use movement in their peripheral vision to recognise targets on computer screen and what the limits are on how much it can help. The aim is find out whether this could spark a new generation of better visual aids to help people with AMD in day-to-day living.
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Scientific summary
Super-resolution: maximising potential in visual impairment
Age-related macular degeneration (ARMD) is responsible for the vast majority of cases of blind registration in the UK. Unfortunately, the most common form of the disease -‘dry’ ARMD- has no effective treatment. Instead, subjects are often encouraged to develop viewing strategies that rely on peripheral vision. This project will investigate whether the principles of super-resolution can be harnessed to improve visual function in this patient group.
Super-resolution is now widely used in a number of image processing technologies and exploits small motion-induced shifts in an image to reconstruct it at a higher resolution. A key prediction of super-resolution processing is that the ability to resolve moving targets should be superior to that of static targets. Such an advantage has been previously reported in human peripheral vision, although the basis of this effect remains unresolved.
In the first part of this project the team is conducting a series of experiments to establish how to optimise the benefits of super-resolution processing in the peripheral visual field. They are then evaluating the benefits of super-resolution processing in a group of patients with ARMD, who use a preferred retinal locus for eccentric viewing. Some very recent pilot data from an independent lab suggests that visual information processing can be enhanced using externally generated image motion in patients with ARMD. Finally, the team is evaluating whether super-resolution processing holds value for individuals where other forms of acquired disease cause long-lasting under-sampling of visual images (e.g. optic neuropathy).