Super-resolution image reconstruction with edge adaptive weight in video sequence

Kwon, Ji Yong; Yoo, Dae San; Park, Jong Hyun; Park, Se Hyeok; Kang, Moon Gi

doi:10.1117/12.905368

Cited by 1 publication

(1 citation statement)

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“…In order to speed up image upscaling, hardware implementation becomes an essential work, but however, not all upscaling methods can be implemented on hardware. [14] shows an super-resolution image reconstruction method, it utilizes the related information of adjacent images for upscaling and edge enhancement. [15] works on the backprojection and carries out a local self-similarity to reconstruct the high frequency data in high resolution images.…”

Section: Related Workmentioning

confidence: 99%

The Implementation of Texture-Based Video Up-Scaling on Coarse-Grained Reconfigurable Architecture

Shi

Yin

Liu

et al. 2015

IEICE Trans. Inf. & Syst.

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SUMMARYVideo Up-scaling is a hotspot in TV display area; as an important brunch of Video Up-scaling, Texture-Based Video Upscaling (TBVU) method shows great potential of hardware implementation. Coarse-grained Reconfigurable Architecture (CGRA) is a very promising processor; it is a parallel computing platform which provides high performance of hardware, high flexibility of software, and dynamical reconfiguration ability. In this paper we propose an implementation of TBVU on CGRA. We fully exploit the characters of TBVU and utilize several techniques to reduce memory I/O operation and total execution time. Experimental results show that our work can greatly reduce the I/O operation and the execution time compared with the non-optimized ones. We also compare our work with other platforms and find great advantage in execution time and resource utilization rate.

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Section: Related Workmentioning

confidence: 99%