Suitability of recent hardware accelerators (DSPs, FPGAs, and GPUs) for computer vision and image processing algorithms

To address these issues, we introduce and discuss important considerations when selecting suitable hardware accelerators for computer vision and image processing tasks, and present a comprehensive review of hardware accelerators. We discuss the practical details of chip architectures, available tools and utilities, development time, and the relative advantages and disadvantages of using DSPs, FPGAs, and GPUs. We provide practical information about state-of-the-art DSPs, FPGAs, and GPUs as well as examples from the literature. Our goal is to enable developers to make a comprehensive comparison between various hardware accelerators, and to select a hardware accelerator that is most suitable for their specific application.