A Real-Time FHD Learning-Based Super-Resolution System Without a Frame Buffer

摘要

This brief presents a real-time learning-based superresolution (SR) system without a frame buffer. The system running on an Altera Stratix IV field programmable gate array can achieve output resolution of 1920 × 1080 (FHD) at 60 fps. The proposed architecture performs an anchored neighborhood regression algorithm that generates a high-resolution image from a low-resolution image input using only numbers of line buffers. This real-time system without a frame buffer makes it possible to integrate SR operation into image sensors or display drivers carrying out computational photography and display.