A FAST AND ENERGY EFFICIENT PARALLEL IMAGE FILTERING IMPLEMENTATION ON RASPBERRY PI'S GPU

This paper presents a powerful processing technique for fast and energy-efficient image filtering algorithm focusing energy and time-sensitive embedded and robotic platforms. Digital video processing is getting more and more popular in battery-powered devices like mobile robots and smartphones whereas in most cases, it leads overhead on the main central processing unit (CPU) and it consumes a significant amount of energy from the battery. It is suitable for parallelism since there is no data dependency between the steps of the two-dimensional convolution algorithm. We propose a vector version of the two-dimensional convolution algorithm, which can run parallel on embedded processors that has general purpose graphic processing unit (GPGPU), to reduce computation time and energy consumption. Our in-depth experiments shows that using GPGPU could reduce the execution time while guaranteeing lower power consumption and offloading the system CPU. Experimental results showed that we achieved up to 105 times faster operation and 100 times less energy consumption compared to the CPU implementation. Besides, we reduced the CPU overhead up to 10 times.