A high-throughput 16× super resolution processor for real-time object recognition SoC

High-resolution image offers more details compared to low-resolution image and consequently improves the accuracy of object recognition. However, higher resolution requires a costly hardware for large image sensor, or computation for additional signal processing. In this paper, we present a high-throughput super resolution processor for high-resolution object recognition. In order to perform super resolution with the real-time object recognition SoC, the algorithm-specific hardware is proposed with 2-D image cache and locality-sensitive hashing accelerator for high-throughput image fetching and searching. As a result, the proposed super resolution processor generates up to 16× higher resolution images with 3,125 fps throughput and 2.0 nJ/pixel energy efficiency, enabling high-resolution pre-processing for real-time object recognition.