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Paper Abstract and Keywords
Presentation 2026-02-19 17:45
Fast Approximate Computation of Local Image Entropy Maps by Haar Hierarchical Binary Tree
Yota Momose (NITech), Yoshihiro Maeda (SIT), Norishige Fukushima (NITech) ITS2025-63 IE2025-78
Abstract (in Japanese) (See Japanese page) 
(in English) Image entropy is a fundamental metric that quantifies the information content of an image based on pixel value distributions, and local image entropy maps are useful as task-independent preprocessing.
However, they face the challenge of high computational cost due to the need for histogram construction within sliding windows and computations proportional to the number of grayscale levels.
This paper proposes an approximate fast computation method that hierarchically decomposes Shannon entropy as the sum of conditional binary entropies and evaluates them sequentially based on a structure named the Haar binary tree structure.
In the proposed method, the contribution at each level is expressed as a non-negative term, so truncation directly corresponds to entropy approximation.
Furthermore, the required coefficients can be computed directly from the image as Haar coefficients of the histogram, enabling implementation without explicitly constructing the histogram.
This demonstrates that computational load can be reduced while controlling approximation accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) Image Entropy Map / Haar Wavelet Transform / Binary Entropy / Haar Hierarchical Binary Tree / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 356, IE2025-78, pp. 135-140, Feb. 2026.
Paper # IE2025-78 
Date of Issue 2026-02-12 (ITS, IE) 
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 ITS2025-63 IE2025-78

Conference Information
Committee IE ITS ITE-MMS ITE-ME ITE-AIT ITE-SIP  
Conference Date 2026-02-19 - 2026-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2026-02-IE-ITS-MMS-ME-AIT-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fast Approximate Computation of Local Image Entropy Maps by Haar Hierarchical Binary Tree 
Sub Title (in English)  
Keyword(1) Image Entropy Map  
Keyword(2) Haar Wavelet Transform  
Keyword(3) Binary Entropy  
Keyword(4) Haar Hierarchical Binary Tree  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yota Momose  
1st Author's Affiliation Nagoya Institute of Technology (NITech)
2nd Author's Name Yoshihiro Maeda  
2nd Author's Affiliation Shibaura Institute of Technology (SIT)
3rd Author's Name Norishige Fukushima  
3rd Author's Affiliation Nagoya Institute of Technology (NITech)
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Speaker Author-1 
Date Time 2026-02-19 17:45:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2025-63, IE2025-78 
Volume (vol) vol.125 
Number (no) no.355(ITS), no.356(IE) 
Page pp.135-140 
#Pages 6 
Date of Issue 2026-02-12 (ITS, IE) 

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