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Paper Abstract and Keywords
Presentation 2024-01-24 10:00
Hierarchical lossless compression of high dynamic range images using predictors based on cellular neural networks
Seiya Kushi, Kazuki Nakashima, Hideharu Toda (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) NLP2023-85 MICT2023-40 MBE2023-31
Abstract (in Japanese) (See Japanese page) 
(in English) We have been developing a scalable lossless coding method using cellular neural networks (CNN) as predictors. This method uses five types of CNN predictors to predict images split by the quincunx lattice. The prediction errors are adaptively arithmetically encoded using multiple probabilistic models. Although high dynamic range (HDR) image utilization has been increasing in recent years, this method can only compress standard 8-bit/pel images. This study proposes a lossless compression scheme for 10-bit/pel HDR images using CNN predictors. In our method, 20 probabilistic models with different shapes are prepared for adaptive selection to enable efficient lossless coding of HDR images.
Keyword (in Japanese) (See Japanese page) 
(in English) Cellular Neural Network / Hierarchical Lossless Image Coding / Adaptive Arithmetic Coding / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 354, NLP2023-85, pp. 12-15, Jan. 2024.
Paper # NLP2023-85 
Date of Issue 2024-01-17 (NLP, MICT, MBE) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
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 NLP2023-85 MICT2023-40 MBE2023-31

Conference Information
Committee NC MBE NLP MICT  
Conference Date 2024-01-24 - 2024-01-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Naruto University of Education 
Topics (in Japanese) (See Japanese page) 
Topics (in English) NC, MBE, MICT, NLP, etc. 
Paper Information
Registration To NLP 
Conference Code 2024-01-NC-MBE-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Hierarchical lossless compression of high dynamic range images using predictors based on cellular neural networks 
Sub Title (in English)  
Keyword(1) Cellular Neural Network  
Keyword(2) Hierarchical Lossless Image Coding  
Keyword(3) Adaptive Arithmetic Coding  
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1st Author's Name Seiya Kushi  
1st Author's Affiliation Chukyo University (Chukyo Univ.)
2nd Author's Name Kazuki Nakashima  
2nd Author's Affiliation Chukyo University (Chukyo Univ.)
3rd Author's Name Hideharu Toda  
3rd Author's Affiliation Chukyo University (Chukyo Univ.)
4th Author's Name Tsuyoshi Otake  
4th Author's Affiliation Tamagawa University (Tamagawa Univ.)
5th Author's Name Hisashi Aomori  
5th Author's Affiliation Chukyo University (Chukyo Univ.)
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Speaker Author-1 
Date Time 2024-01-24 10:00:00 
Presentation Time 20 minutes 
Registration for NLP 
Paper # NLP2023-85, MICT2023-40, MBE2023-31 
Volume (vol) vol.123 
Number (no) no.354(NLP), no.355(MICT), no.356(MBE) 
Page pp.12-15 
#Pages 4 
Date of Issue 2024-01-17 (NLP, MICT, MBE) 

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