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A Real-Time FHD Learning-Based Super-Resolution System Without a Frame Buffer
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DOI：10.1109/TCSII.2017.2749336.png)
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Abstract
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This brief presents a real-time learning-based super-resolution (SR) system without a frame buffer. The system running on an Altera Stratix IV field programmable gate array can achieve output resolution of 1920 x 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.
Keywords:
Super resolution
anchored neighborhood regression
real-time
FPGA
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