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Conference Paper Real-Time Texture Synthesis via Aggregation of Internal and External Patch Candidates
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Authors
Seok Bong Yoo, Mikyong Han
Issue Date
2019-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1446-1450
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939980
Abstract
In practical image display systems, the image quality of magnified videos is considered very critical. Although many image super-resolution algorithms based on deep learning using external database were proposed for the upscaling of low-resolution contents, they still do not provide excellent performance in high-resolution displays. This may be due to several troublesome issues such as the lack of analysis of high-frequency texture components, the adopted edge-oriented loss function, and the use of external database different from the test image. In this study, we focus on the difficult issues and propose a real-time texture synthesis algorithm, based on aggregation of internal and external patch candidates. Specifically, to improve the image fineness while keeping texture naturalness, merged and rearranged distant pixels in the input image are combined with external examples obtained from a hardware-friendly technique specially redesigned. Experimental results show the proposed texture synthesis algorithm outperforms existing state-of-the-art algorithms.
KSP Keywords
Display System, Edge-oriented, Hardware-friendly, High frequency(HF), High-resolution displays, Image display, Image super-resolution, Internal and external, Real-time, deep learning(DL), excellent performance