https://scholars.lib.ntu.edu.tw/handle/123456789/502353
Title: | A Real-Time FHD Learning-Based Super-Resolution System Without a Frame Buffer | Authors: | Yang, M.-C. Liu, K.-L. SHAO-YI CHIEN |
Keywords: | anchored neighborhood regression; FPGA; real-time; Super resolution | Issue Date: | 2017 | Journal Volume: | 64 | Journal Issue: | 12 | Start page/Pages: | 1407-1411 | Source: | IEEE Transactions on Circuits and Systems II: Express Briefs | Abstract: | 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 × 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. © 2004-2012 IEEE. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/502353 | DOI: | 10.1109/TCSII.2017.2749336 | SDG/Keyword: | Color photography; Field programmable gate arrays (FPGA); Interactive computer systems; Optical resolving power; Real time systems; Signal receivers; anchored neighborhood regression; Computational photography; Learning-based super-resolution; Low resolution images; Proposed architectures; Real time; Regression algorithms; Super resolution; Learning systems |
Appears in Collections: | 電機工程學系 |
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