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Paper Abstract and Keywords
Presentation 2016-12-09 13:00
Hierarchical Clustering based Noise Cluster Prediction for an Image Quality Assessment
Seiji Inari, Yasuhiro Inazumi, Naho Ito, Yuukou Horita (Univ. of Toyama) CS2016-58 IE2016-94
Abstract (in Japanese) (See Japanese page) 
(in English) Image quality Assessment (IQA) is necessary for applications that deal with many of images and videos. The goal of the IQA algorithms is consistent with the human subjectivity and is to assess the quality of images or videos automatically. Over the years, many researchers have proposed IQA methods. The image database is used to evaluate the performance of them. TID2013 is the data set for the IQA with the 24 kind of noise. In this paper, We present a method to improve its performance by using noise clustering based on the assumption that accuracy of IQA methods is increasing by performing IQA for each type of noise.
The experimental result showed that the proposed method improves the performance using an IQA method called FSIMc.
Keyword (in Japanese) (See Japanese page) 
(in English) Image Quality Assessment / TID2013 / FSIMcolor / SVM / Hierarchical Clustering / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 347, IE2016-94, pp. 87-90, Dec. 2016.
Paper # IE2016-94 
Date of Issue 2016-12-01 (CS, IE) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Conference Date 2016-12-08 - 2016-12-09 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image coding, Communications and streaming technologies, etc. 
Paper Information
Registration To IE 
Conference Code 2016-12-IE-CS-AVM-BCT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Hierarchical Clustering based Noise Cluster Prediction for an Image Quality Assessment 
Sub Title (in English)  
Keyword(1) Image Quality Assessment  
Keyword(2) TID2013  
Keyword(3) FSIMcolor  
Keyword(4) SVM  
Keyword(5) Hierarchical Clustering  
1st Author's Name Seiji Inari  
1st Author's Affiliation University of Toyama (Univ. of Toyama)
2nd Author's Name Yasuhiro Inazumi  
2nd Author's Affiliation University of Toyama (Univ. of Toyama)
3rd Author's Name Naho Ito  
3rd Author's Affiliation University of Toyama (Univ. of Toyama)
4th Author's Name Yuukou Horita  
4th Author's Affiliation University of Toyama (Univ. of Toyama)
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Date Time 2016-12-09 13:00:00 
Presentation Time 25 
Registration for IE 
Paper # IEICE-CS2016-58,IEICE-IE2016-94 
Volume (vol) IEICE-116 
Number (no) no.346(CS), no.347(IE) 
Page pp.87-90 
#Pages IEICE-4 
Date of Issue IEICE-CS-2016-12-01,IEICE-IE-2016-12-01 

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