Industrial image processing tasks, especially in the domain of optical metrology, are becoming more and more complex. While in recent years standard PC components were sufficient to fulfill the requirements, special architectures have to be used to build high-speed image processing systems today. For example, for adaptive optical systems in large scale telescopes, the latency between capturing an image and steering the mirrors is critical for the quality of the resulting images. Commonly, the applied image processing algorithms consist of several tasks with different granularities and complexities. Therefore, we combined the advantages of multicore CPUs, GPUs, and FPGAs to build a heterogeneous image processing pipeline for adaptive optical systems by presenting new architectures and algorithms. Each architecture is well-suited to solve a particular task efficiently, which is proven by a detailed evaluation. With the developed pipeline it is possible to achieve a high throughput and to reduce the latency of the whole steering system significantly. 
Fast image processing for optical metrology utilizing heterogeneous computer architectures