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Committee Date Time Place Paper Title / Authors Abstract Paper #
IMQ, IE, MVE, CQ
(Joint) [detail]		 2019-03-14
13:55		 Kagoshima Kagoshima University Multi Frame Super-Resolution Magnification method using TV Regularization and Learning-based Method
Taiki Kondo, Hiroto Kizuna, Hiromasa Takeda, Hiroyuki Sato (Iwate Pref. Univ.) IMQ2018-38 IE2018-122 MVE2018-69		 A method combining a Based learning method and ShockFilter for Total Variation (TV) regularization, which is one of supe... [more] IMQ2018-38 IE2018-122 MVE2018-69
pp.91-96
CQ, MVE, IE, IMQ, CEA
(Joint) [detail]		 2014-03-07
10:00		 Oita Beppu International Convention Center Image Super-Resolution based on Shock Filter
Taichi Yoshida, Masaaki Ikehara (Keio Univ.) IMQ2013-58 IE2013-167 MVE2013-96		 In this paper,we propose an image super-resolution method based on the shock filter for high frequency components.Compar... [more] IMQ2013-58 IE2013-167 MVE2013-96
pp.165-168
RCS, SIP 2014-01-23
13:25		 Fukuoka Kyushu Univ. Shock Filter Based on Non-Local Means for Image Super-Resolution
Taichi Yoshida, Masaaki Ikehara (Keio Univ.) SIP2013-101 RCS2013-271		 In this paper,we propose a shock filter based on the non-local means algorithm for image super-resolution.The super-reso... [more] SIP2013-101 RCS2013-271
pp.95-99
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