Lifting-based lossless image coding using cellular neural network predictors and context estimators optimized by adaptive differential evolution-Reference-Cited by-同舟云学术

Lifting-based lossless image coding using cellular neural network predictors and context estimators optimized by adaptive differential evolution

Published:2023 Issue:3 Volume:14 Page:609-627
ISSN:2185-4106
Container-title:Nonlinear Theory and Its Applications, IEICE
language:en
Short-container-title:NOLTA

Author:

Nakashima Kazuki¹^ORCID,Kawai Yuki²^ORCID,Nakazawa Ryo¹^ORCID,Toda Hideharu¹^ORCID,Aomori Hisashi¹^ORCID,Otake Tsuyoshi³^ORCID,Matsuda Ichiro⁴^ORCID,Itoh Susumu⁴^ORCID

Affiliation:

1. Faculty of Engineering, Chukyo University

2. Development & Production Division, Hagiwara Electronics Co., Ltd.

3. College of Engineering, Tamagawa University

4. Department of Electrical Engineering, Tokyo University of Science

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Link

https://www.jstage.jst.go.jp/article/nolta/14/3/14_609/_pdf

Reference38 articles.

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2. [2] K.S. Gunasheela and H.S. Prasantha, “Satellite image compression-detailed survey of the algorithms,” Proc. International Conference on Cognition and Recognition, pp. 187-198, 2018.

3. [3] A.D. Wilson, “Fast lossless depth image compression,” Proc. 2017 ACM International Conference on Interactive Surfaces and Spaces, pp. 100-105, 2017.

4. [4] T. Sakurai and U. Inoue, “Lossless image set compression using animated FLIF,” Proc. 8th International Virtual Conference on Applied Computing & Information Technology, pp. 99-104, 2021.

5. [5] W. Xiaolin and N. Memon, “CALIC - a context based adaptive lossless image codec,” Proc. 1996 IEEE International Conference Acoust Speech Signal Processing (ICASSP), vol. 4, pp. 1890-1893, May 1996.

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