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Low-level computer vision algorithms have high computational requirements. In this study, we present two real-time architectures using resource constrained FPGA and GPU devices for the computation of a new algorithm which performs tone mapping, contrast enhancement, and glare mitigation. Our goal is to implement this operator in a portable and battery-operated device, in order to obtain a low vision aid specially aimed at visually impaired people who struggle to manage themselves in environments where illumination is not uniform or changes rapidly. This aid device processes in real-time, with minimum latency, the input of a camera and shows the enhanced image on a head mounted display (HMD). Therefore, the proposed operator has been implemented on battery-operated platforms, one based on the GPU NVIDIA ION2 and another on the FPGA Spartan III, which perform at rates of 30 and 60 …