An infrared image-enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses

Background Most existing retinal prostheses contain a built-in visible-light camera module that captures images of the surrounding environment. Thus, in case of insufficient or lack of visible light, the camera fails to work, and the retinal prostheses enter a dormant or OFF state. A simple and effective solution is replacing the visible-light camera with a dual-mode camera. The present research aimed to achieve two main purposes: (1) to explore whether the dual-mode camera in prosthesis recipients works under no visible-light conditions and (2) to assess its performance. Methods To accomplish these aims, we enrolled subjects in a psychophysical experiment under simulated prosthetic vision conditions. We found that the subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible-light mode. These results inspired us to develop and propose a feasible infrared image-enhancement processing algorithm. Another psychophysical experiment was performed to verify the feasibility of the algorithm. Results The obtained results showed that the average efficiency of the subjects completing visual tasks using our enhancement algorithm (0.014 +/- 0.001) was significantly higher (p < 0.001) than that of subjects using direct pixelization (0.007 +/- 0.001). Conclusions We concluded that a dual-mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions. Dual-mode cameras combined with this infrared image-enhancement algorithm could provide a promising direction for the design of future retinal prostheses.

Automated summary

A dual-mode camera is a feasible solution for improving the performance of retinal prostheses, as it adapts better to the specific existing ambient light conditions. Our developed infrared image-enhancement algorithm significantly improves the efficiency of visual tasks.