GPU-Accelerated Frame Pre-Processing for Use in Low Latency Computer Vision Applications

The attention for low latency computer vision and video processing applications are growing for every year, not least the VR and AR applications. In this thesis the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Radial Dis- tortion algorithms are implemented using both CUDA and OpenCL to determine whether these type of algorithms are suitable for implementations aimed to run at GPUs when low latency is of utmost importance. The result is an implemen- tation of the block versions of the CLAHE algorithm which utilizes the built in interpolation hardware that resides on the GPU to reduce block effects and an im- plementation of the Radial Distortion algorithm that corrects a 1920x1080 frame in 0.3 ms. Further this thesis concludes that the GPU-platform might be a good choice if the data to be processed can be transferred to and possibly from the GPU fast enough and that the choice of compute API mostly is a matter of taste.