Low-level computer vision algorithms have high computational requirements. In this study, we present two realtime\r\narchitectures using resource constrained FPGA and GPU devices for the computation of a new algorithm\r\nwhich performs tone mapping, contrast enhancement, and glare mitigation. Our goal is to implement this operator\r\nin a portable and battery-operated device, in order to obtain a low vision aid specially aimed at visually impaired\r\npeople who struggle to manage themselves in environments where illumination is not uniform or changes rapidly.\r\nThis aid device processes in real-time, with minimum latency, the input of a camera and shows the enhanced\r\nimage on a head mounted display (HMD). Therefore, the proposed operator has been implemented on batteryoperated\r\nplatforms, one based on the GPU NVIDIA ION2 and another on the FPGA Spartan III, which perform at\r\nrates of 30 and 60 frames per second, respectively, when working with VGA resolution images (640 Ã?â?? 480).
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