@inproceedings{b23ae2cb2bce47e6ad8dd9208cf0c601,
title = "Epitomic image super-resolution",
abstract = "We propose Epitomic Image Super-Resolution (ESR) to enhance the current internal SR methods that exploit the selfsimilarities in the input. Instead of local nearest neighbor patch matching used in most existing internal SR methods, ESR employs epitomic patch matching that features robustness to noise, and both local and non-local patch matching. Extensive objective and subjective evaluation demonstrate the effectiveness and advantage of ESR on various images.",
author = "Yingzhen Yang and Zhangyang Wang and Zhaowen Wang and Shiyu Chang and Ding Liu and Honghui Shi and Huang, {Thomas S.}",
note = "Publisher Copyright: {\textcopyright} Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 30th AAAI Conference on Artificial Intelligence, AAAI 2016 ; Conference date: 12-02-2016 Through 17-02-2016",
year = "2016",
language = "English (US)",
series = "30th AAAI Conference on Artificial Intelligence, AAAI 2016",
publisher = "AAAI press",
pages = "4278--4279",
booktitle = "30th AAAI Conference on Artificial Intelligence, AAAI 2016",
}