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Paper Abstract and Keywords
Presentation 2024-02-20 12:45
3D CG Coded Image Noise Removal and Quality Assessment Based on Optimal Design of Total Variation Regularization
Norifumi Kawabata (Kanazawa Gakuin Univ.) ITS2023-67 IE2023-56
Abstract (in Japanese) (See Japanese page) 
(in English) Sparse coding techniques, which reproduce and represent images with as few combinations as possible from a small amount of image data, have been studies for application to image processing. The image media is needed that pre-processing must be performed based on a preliminary understanding of properties and characteristics. In our case, there are studies related on 3D CG images, and therefore, the goal is to optimize the sparse coding process for 3D CG. We have been studied the quality assessment of 3D CG image noise removal based on sparse dictionary learning coding. Sparse dictionary-based coding relies on dictionary learning, and there were differences in image reproduction depending on the type of denoising and learning conditions. Therefore, we considered the possibility of constructing a more accurate algorithm for image reproduction by considering total variation regularization, a type of mathematical optimization, and incorporating foresight information in order to minimize the difference between noises. In this study, we attempted to construct an efficient algorithm for denoising 3D CG images based on total variation regularization, which is foresight information, by designing optimal parameters. And then, we discussed the effectiveness of the algorithm by evaluating image quality before and after denoising.
Keyword (in Japanese) (See Japanese page) 
(in English) Computer Graphics / Total Variation Regularization / Lasso / Noise Removal / HEVC / Image Quality Assessment / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 381, IE2023-56, pp. 112-117, Feb. 2024.
Paper # IE2023-56 
Date of Issue 2024-02-12 (ITS, IE) 
ISSN Online edition: ISSN 2432-6380
Copyright
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reproduction
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)
Download PDF ITS2023-67 IE2023-56

Conference Information
Committee ITS IE ITE-MMS ITE-ME ITE-AIT  
Conference Date 2024-02-19 - 2024-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To IE 
Conference Code 2024-02-ITS-IE-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) 3D CG Coded Image Noise Removal and Quality Assessment Based on Optimal Design of Total Variation Regularization 
Sub Title (in English)  
Keyword(1) Computer Graphics  
Keyword(2) Total Variation Regularization  
Keyword(3) Lasso  
Keyword(4) Noise Removal  
Keyword(5) HEVC  
Keyword(6) Image Quality Assessment  
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Keyword(8)  
1st Author's Name Norifumi Kawabata  
1st Author's Affiliation Kanazawa Gakuin University (Kanazawa Gakuin Univ.)
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Speaker Author-1 
Date Time 2024-02-20 12:45:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2023-67, IE2023-56 
Volume (vol) vol.123 
Number (no) no.380(ITS), no.381(IE) 
Page pp.112-117 
#Pages
Date of Issue 2024-02-12 (ITS, IE) 


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