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Committee Date Time Place Paper Title / Authors Abstract Paper #
MICT, MI 2018-11-06
10:40		 Hyogo University of Hyogo Improvement of Laparoscopic Color Image Diagnosis for Automatic Detection of Coded Defect Region and Application of Effective Classifier Parameter
Norifumi Kawabata (Nagoya Univ.), Toshiya Nakaguchi (Chiba Univ.) MICT2018-42 MI2018-42		 In addition to judgment by human eyes up to the present, it is advanced for R&D of diagnostic imaging systems by using a... [more] MICT2018-42 MI2018-42
pp.21-26
IMQ 2016-05-27
13:40		 Chiba Chiba Univ. Multi-view 3D CG Image Quality Assessment by Using S-CIELAB Color Space Including Visible Digital Watermarking by Regions in case the Background Region is Gray Scale
Norifumi Kawabata, Masaru Miyao (Nagoya Univ.) IMQ2016-1		 Previously, we studied about multi-view 3D CG image quality evaluation including visible digital watermarking by regions... [more] IMQ2016-1
pp.1-6
IMQ 2015-05-22
15:25		 Toyama   3D CG Image Quality Metrics for the Contrast Enhancement of the Object Region Including S-CIELAB Color Space with 8 Viewpoints Parallax Barrier Method
Norifumi Kawabata, Masaru Miyao (Nagoya Univ.) IMQ2015-4		 Previously, there were many studies about the image quality evaluation based on S-CIELAB color space including the spati... [more] IMQ2015-4
pp.17-22
IE, MVE 2012-03-12
14:00		 Toyama Toyama University Objective assessment model of QoE for Audio-Visual contents by color information
Masaharu Sato, Shoutaro Tsuji, Keiji Shibata, Yasuhiro Inazumi, Yuukou Horita (Univ. of Toyama), Osamu Sugimoto, Sei Naito (KDDI R&D Labs.) IE2011-153 MVE2011-115		 In this paper, we discuss the performance improvement of the previously proposed objective quality evaluation model of A... [more] IE2011-153 MVE2011-115
pp.115-119
CQ, NS, ICM
(Joint)		 2006-11-17
15:10		 Tottori Tottori Univ. of Environmental Studies Full reference image quality evaluation model considering the property of S-CIELAB color space
Hiroshi Matsumoto, Keiji Shibata, Yuukou Horita (Univ. of Toyama) CQ2006-77		 Most of the proposed image quality evaluation models are generally based on only luminance information.
So, color infor... [more]		 CQ2006-77
pp.101-106
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