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Software Implementation Methodology of Intelligent Information Systems of Learning and Knowledge Control (IISLKC) Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Fuzzy Information Measure for Improving HDR Imaging

Authors : Annamária R. Várkonyi-Kóczy, Sándor Hancsicska, József Bukor

Published in: Recent Developments and New Direction in Soft-Computing Foundations and Applications

Publisher: Springer International Publishing

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Abstract

Digital image processing can often improve the quality of visual sensing of images and real-world scenes. Recently, high dynamic range (HDR) imaging techniques have become more and more popular in the field. Both classical and soft computing–based methods proved to be advantages in revealing the non-visible parts of images and realistic scenes. However, extracting as much details as possible is not always enough because the sensing capability of the human eye depends on many other factors and the visual quality is not always proportional to the rate of accurate reproduction of the scene. In this paper, a new fuzzy information measure is introduced by which the quality of HDR images can be improved and both the amount of visible details and the quality of sensing can be increased.

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previous chapter A Fuzzy Multiagent Approach for Integrated Product Life Cycle Environment
next chapter Optimization of Type-1 and Type-2 Fuzzy Systems Applied to Pattern Recognition
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Metadata
Title
Fuzzy Information Measure for Improving HDR Imaging
Authors
Annamária R. Várkonyi-Kóczy
Sándor Hancsicska
József Bukor
Copyright Year
2016
Book
Recent Developments and New Direction in Soft-Computing Foundations and Applications

Print ISBN: 978-3-319-32227-8

Electronic ISBN: 978-3-319-32229-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-32229-2_9

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