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Paper Abstract and Keywords
Presentation 2021-03-03 10:25
Remote Sensing Data Restoration by Constraining the Gradients of Stripe Noise
Kazuki Naganuma, Saori Takeyama, Shunsuke Ono (Titech) EA2020-60 SIP2020-91 SP2020-25
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes an effective and efficient restoration methods for remote-sensing data by constraining the gradient of stripe noise. Stripe noise removal of remote-sensing data is one of the essential restoration task because stripe noise affects not only the visual quality but also subsequent processing. For stripe noise removal, an optimization technique is often used. In this paper, we adopt the gradient constraints of stripe noise to the optimization problem because the stripe noise has the fact that the spatial and temporal gradients are equal to zero. Our method imposes strong constraints on stripe noise, and thus can fully capture stripe noise, leading to much effective stripe noise removal. Also, operations required for handling the constraints of gradient are simple, which enables us to develop an efficient algorithm for solving the problem by a primal-dual splitting method. We demonstrate the advantages of our method over existing methods on restoration experiments using remote-sensing data.
Keyword (in Japanese) (See Japanese page) 
(in English) gradient constraints / restoration / stripe noise removal / primal-dual splitting / remote sensing data / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 398, SIP2020-91, pp. 5-8, March 2021.
Paper # SIP2020-91 
Date of Issue 2021-02-24 (EA, SIP, SP) 
ISSN Print edition: ISSN 0913-5685  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 EA2020-60 SIP2020-91 SP2020-25

Conference Information
Committee EA US SP SIP IPSJ-SLP  
Conference Date 2021-03-03 - 2021-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech, Engineering/Electro Acoustics, Signal Processing, Ultrasonics, and Related Topics 
Paper Information
Registration To SIP 
Conference Code 2021-03-EA-US-SP-SIP-SLP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Remote Sensing Data Restoration by Constraining the Gradients of Stripe Noise 
Sub Title (in English)  
Keyword(1) gradient constraints  
Keyword(2) restoration  
Keyword(3) stripe noise removal  
Keyword(4) primal-dual splitting  
Keyword(5) remote sensing data  
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1st Author's Name Kazuki Naganuma  
1st Author's Affiliation Tokyo Institute of Technology (Titech)
2nd Author's Name Saori Takeyama  
2nd Author's Affiliation Tokyo Institute of Technology (Titech)
3rd Author's Name Shunsuke Ono  
3rd Author's Affiliation Tokyo Institute of Technology (Titech)
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Speaker
Date Time 2021-03-03 10:25:00 
Presentation Time 25 
Registration for SIP 
Paper # IEICE-EA2020-60,IEICE-SIP2020-91,IEICE-SP2020-25 
Volume (vol) IEICE-120 
Number (no) no.397(EA), no.398(SIP), no.399(SP) 
Page pp.5-8 
#Pages IEICE-4 
Date of Issue IEICE-EA-2021-02-24,IEICE-SIP-2021-02-24,IEICE-SP-2021-02-24 


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