A Real-Time Learning-Based Super-Resolution System Using Direct Simple Functions

被引：0
|
作者：
Zha, Daolu [1 ]
Jin, Xi [1 ]
Shang, Rui [2 ]
Yang, Pengfei [1 ]
机构：
[1] Univ Sci & Technol China, Sch Phys Sci, Hefei, Anhui, Peoples R China
[2] Suzhou Graphichina Microelect Technol Co Ltd, Suzhou, Peoples R China
来源：
2018 IEEE 29TH INTERNATIONAL CONFERENCE ON APPLICATION-SPECIFIC SYSTEMS, ARCHITECTURES AND PROCESSORS (ASAP) | 2018年
关键词：
Super-Resolution; Real-Time; FPGA;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a real-time super-resolution (SR) system. The proposed system performs a fast SR algorithm that generates a high-resolution image from a low-resolution image using direct regression functions. The system implemented on a Xilinx Virtex 7 field programmable gate array achieves output resolution of 3840 x 2160 (UHD) at 200 fps and 2000Mpixels/s throughput. Experimental results show that the proposed system provides high image quality for real-time applications.
引用
收藏
页码：77 / 80
页数：4
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