Importance weighted image enhancement for prosthetic vision: An augmentation framework

Augmentations to enhance perception in prosthetic vision (also known as bionic eyes) have the potential to improve functional outcomes significantly for implantees. In current (and near-term) im-plantable electrode arrays resolution and dynamic range are highly constrained in comparison to images from modern cameras that can be head mounted. In this paper, we propose a novel, generally applicable adaptive contrast augmentation framework for prosthetic vision that addresses the specific perceptual needs of low resolution and low dynamic range displays. The scheme accepts an externally defined pixel-wise weighting of importance describing features of the image to enhance in the output dynamic range. Our approach explicitly incorporates the logarithmic scaling of enhancement required in human visual perception to ensure perceivability of all contrast augmentations. It requires no pre-existing contrast, and thus extends previous work in local contrast enhancement to a formulation for general image augmentation. We demonstrate the generality of our augmentation scheme for scene structure and looming object enhancement using simulated prosthetic vision.