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Paper Abstract and Keywords
Presentation 2022-02-21 12:45
Quality Assessment for 3D CG Image Colorization Using Visible Digital Watermarking after Noise Removal Based on Sparse Dictionary Learning Coding
Norifumi Kawabata (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Thus far, we discussed to represent image data whether it is possible or not to represent meaning image how requirement is satisfied from a view of image quality by preparing dictionary in advance, and then using sparse coding that represent a part or all of image data by combination as few as possible from these components. As past our study, we try to experiment for noise removal objectively using six types of noise, sparse dictionary learning. However, in this case, it was not enough to consider color component. Therefore, there is a problem at least from the view of practicality. On the other hand, it is difficult for 3D CG images included multidimensional information to restore color. Therefore, in this paper, first we add noise for 3D CG images, and then we remove noise from noise addition images based on sparse coding. After that, we try to experiment whether it is possible or not to restore processed images after noise removal as color image by carrying out the colorization using visible digital watermarking. Finally, we carried out the image quality assessment including color component before and after image processing, and then we discussed these results.
Keyword (in Japanese) (See Japanese page) 
(in English) Sparse Coding / Dictionary Learning / Noise Removal / Wavelet / Digital Watermarking / Colorization / Image Quality Assessment /  
Reference Info. ITE Tech. Rep., vol. 46, no. 6, ME2022-31, pp. 31-36, Feb. 2022.
Paper # ME2022-31 
Date of Issue 2022-02-14 (MMS, ME, AIT) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Committee AIT ME MMS IEICE-IE IEICE-ITS  
Conference Date 2022-02-21 - 2022-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2022-02-AIT-ME-MMS-IE-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Quality Assessment for 3D CG Image Colorization Using Visible Digital Watermarking after Noise Removal Based on Sparse Dictionary Learning Coding 
Sub Title (in English)  
Keyword(1) Sparse Coding  
Keyword(2) Dictionary Learning  
Keyword(3) Noise Removal  
Keyword(4) Wavelet  
Keyword(5) Digital Watermarking  
Keyword(6) Colorization  
Keyword(7) Image Quality Assessment  
Keyword(8)  
1st Author's Name Norifumi Kawabata  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2022-02-21 12:45:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # MMS2022-6, ME2022-31, AIT2022-6 
Volume (vol) vol.46 
Number (no) no.6 
Page pp.31-36 
#Pages
Date of Issue 2022-02-14 (MMS, ME, AIT) 


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