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W. Fink, M. Tarbell; Artificial Vision Simulator (AVS) for Enhancing and Optimizing Visual Perception of Retinal Implant Carriers . Invest. Ophthalmol. Vis. Sci. 2005;46(13):1145.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose:To computer–enhance in real time low–resolution vision, provided by a retinal implant that would enable a blind person to attain unaided mobility and large print reading, two important quality of life indicators. Methods:The human retina is not a mere receptor of photonic information, but performs significant image processing thanks to its layered neural network structure. The current state–of–the–art and near future epi–retinal implants provide only tens of electrodes, thereby allowing only for a very limited visual perception (pixelization). Therefore, it is crucial to enhance this limited perception by means of real time image processing. Since tens of pixels/electrodes allow only for a very crude approximation of the about 10,000 times higher optical resolution of the external camera image feed, the preservation and enhancement of contrast differences and transitions, such as edges, become very important as opposed to picture details such as texture. Results:We have created a software package, the Artificial Vision Simulator (AVS), that interfaces with Firewire (IEEE 1394) cameras and displays the captured video stream in a user–defined pixelization, mimicking the visual perception with a retinal implant electrode array, in real time (30 fps). The software package further comprises a suite of efficient image manipulation and processing algorithms/modules that have been developed to alter/modify the captured video stream in real time (30 fps), such as: video pixelization to simulate the vision provided by a retinal implant electrode array; contrast correction/enhancement; brightness correction/enhancement; grayscale histogram equalization for luminance control under severe lighting conditions such as dark face against sunlight, or dark–in–dark scenes under low light conditions; reduction of available (user–defined) grayscale levels for reduction of data volume to be transmitted to the retinal implant; edge detection; and image inversion. Conclusions:Real time image processing can potentially enhance the visual perception of a retinal implant carrier and, in addition, may be able to reduce the amount of data, i.e., data rate, to be transmitted to the retinal prosthesis. This would have a beneficial effect on both energy consumption and heat dissipation by the retinal prosthesis. The Artificial Vision Simulator (AVS) is currently being interfaced to actual epi–retinal implant carriers for visual perception enhancement.
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