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Paper Abstract and Keywords
Presentation 2019-10-24 15:30
Image Regularization with Total Variation and Morphological Gradient Priors Using Optimization of Structuring Element for Each Pixel
Shoya Oohara, Hirotaka Oka, Mistuji Muneyasu, Soh Yoshida (Kansai Univ.), Makoto Nakashizuka (CIT) SIS2019-17
Abstract (in Japanese) (See Japanese page) 
(in English) As an image prior for image restoration, a method using the sum of morphological gradients has been proposed. Optimization of a structuring element (SE) used for this morphological gradient by a genetic algorithm (GA) has also been introduced. In this method, a single SE is selected for the entire image. However, since the whole image is processed with only one SE, it is difficult to deal with various edges and textures in the image. In this paper, we propose a method to optimize the SE for each pixel and to restore the image using its SE. For reducing the computational burden, simulated annealing is introduced, and the reduction of the computational cost in the evaluation of the SE is proposed. By optimizing the SE for each pixel, edges, and details in the image can be faithfully evaluated, and improvement in restoration accuracy can be expected. An experiment shows the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) morphology / morphological gradient / total variation / regularization / image restoration / simulated annealing / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 240, SIS2019-17, pp. 47-52, Oct. 2019.
Paper # SIS2019-17 
Date of Issue 2019-10-17 (SIS) 
ISSN Print edition: ISSN 0913-5685  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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SIS2019-17

Conference Information
Committee ITE-BCT SIS  
Conference Date 2019-10-24 - 2019-10-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Fukui International Activities Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English) System Implementation Technology, Short Range Wireless Systems, Smart Multimedia Systems, Broadcasting Technology, etc. 
Paper Information
Registration To SIS 
Conference Code 2019-10-BCT-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Image Regularization with Total Variation and Morphological Gradient Priors Using Optimization of Structuring Element for Each Pixel 
Sub Title (in English)  
Keyword(1) morphology  
Keyword(2) morphological gradient  
Keyword(3) total variation  
Keyword(4) regularization  
Keyword(5) image restoration  
Keyword(6) simulated annealing  
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Keyword(8)  
1st Author's Name Shoya Oohara  
1st Author's Affiliation Kansai University (Kansai Univ.)
2nd Author's Name Hirotaka Oka  
2nd Author's Affiliation Kansai University (Kansai Univ.)
3rd Author's Name Mistuji Muneyasu  
3rd Author's Affiliation Kansai University (Kansai Univ.)
4th Author's Name Soh Yoshida  
4th Author's Affiliation Kansai University (Kansai Univ.)
5th Author's Name Makoto Nakashizuka  
5th Author's Affiliation Chiba Institute of Technology (CIT)
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Speaker
Date Time 2019-10-24 15:30:00 
Presentation Time 20 
Registration for SIS 
Paper # IEICE-SIS2019-17 
Volume (vol) IEICE-119 
Number (no) no.240 
Page pp.47-52 
#Pages IEICE-6 
Date of Issue IEICE-SIS-2019-10-17 


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