Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11418)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Conference series link(s): CCIW: International Workshop on Computational Color Imaging
Conference proceedings info: CCIW 2019.
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Table of contents (25 papers)
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Front Matter
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Perceptual Model and Application
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Front Matter
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About this book
This book constitutes the refereed proceedings of the 7th Computational Color Imaging Workshop, CCIW 2019, held in Chiba, Japan, in March 2019.
The 22 full papers presented in this volume were carefully reviewed and selected from 34 submissions. The papers are organized in topical sections named: computational color imaging; multispectral imaging; perceptual model and application; color image evaluation; colot image filtering; color image applications; and color imaging for material appearance. In addition, the book contains 3 invited talks in full paper length.Editors and Affiliations
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Norwegian University of Science and Technology, Gjøvik, Norway
Shoji Tominaga
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University of Milano Bicocca, Milan, Italy
Raimondo Schettini
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University Jean Monnet, Saint-Etienne, France
Alain Trémeau
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Chiba University, Chiba, Japan
Takahiko Horiuchi
Bibliographic Information
Book Title: Computational Color Imaging
Book Subtitle: 7th International Workshop, CCIW 2019, Chiba, Japan, March 27-29, 2019, Proceedings
Editors: Shoji Tominaga, Raimondo Schettini, Alain Trémeau, Takahiko Horiuchi
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-13940-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-13939-1Published: 20 February 2019
eBook ISBN: 978-3-030-13940-7Published: 19 March 2019
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XI, 349
Number of Illustrations: 29 b/w illustrations, 186 illustrations in colour
Topics: Image Processing and Computer Vision, Models and Principles, Artificial Intelligence