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Improving Image Quality in Visual Cryptography - Bin Yan, Yong Xiang, Guang Hua

Improving Image Quality in Visual Cryptography (eBook)

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2019 | 1st ed. 2020
XVIII, 120 Seiten
Springer Singapore (Verlag)
978-981-13-8289-5 (ISBN)
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This book comprehensively covers the important efforts in improving the quality of images in visual cryptography (VC), with a focus on cases with gray scale images. It not only covers schemes in traditional VC and extended VC for binary secret images, but also the latest development in the analysis-by-synthesis approach.

This book distinguishes itself from the existing literature in three ways. First, it not only reviews traditional VC for binary secret images, but also covers recent efforts in improving visual quality for gray scale secret images. Second, not only traditional quality measures are reviewed, but also measures that were not used for measuring perceptual quality of decrypted secret images, such as Radially Averaged Power Spectrum Density (RAPSD) and residual variance, are employed for evaluating and guiding the design of VC algorithms. Third, unlike most VC books following a mathematical formal style, this book tries to make a balance between engineering intuition and mathematical reasoning. All the targeted problems and corresponding solutions are fully motivated by practical applications and evaluated by experimental tests, while important security issues are presented as mathematical proof. Furthermore, important algorithms are summarized as pseudocodes, thus enabling the readers to reproduce the results in the book. Therefore, this book serves as a tutorial for readers with an engineering background as well as for experts in related areas to understand the basics and research frontiers in visual cryptography.



This book comprehensively covers the important efforts in improving the quality of images in visual cryptography (VC), with a focus on cases with gray scale images. It not only covers schemes in traditional VC and extended VC for binary secret images, but also the latest development in the analysis-by-synthesis approach.This book distinguishes itself from the existing literature in three ways. First, it not only reviews traditional VC for binary secret images, but also covers recent efforts in improving visual quality for gray scale secret images. Second, not only traditional quality measures are reviewed, but also measures that were not used for measuring perceptual quality of decrypted secret images, such as Radially Averaged Power Spectrum Density (RAPSD) and residual variance, are employed for evaluating and guiding the design of VC algorithms. Third, unlike most VC books following a mathematical formal style, this book tries to make a balance between engineeringintuition and mathematical reasoning. All the targeted problems and corresponding solutions are fully motivated by practical applications and evaluated by experimental tests, while important security issues are presented as mathematical proof. Furthermore, important algorithms are summarized as pseudocodes, thus enabling the readers to reproduce the results in the book. Therefore, this book serves as a tutorial for readers with an engineering background as well as for experts in related areas to understand the basics and research frontiers in visual cryptography.
Erscheint lt. Verlag 8.6.2019
Reihe/Serie Signals and Communication Technology
Signals and Communication Technology
Zusatzinfo XVIII, 120 p. 74 illus., 13 illus. in color.
Sprache englisch
Themenwelt Informatik Netzwerke Sicherheit / Firewall
Informatik Software Entwicklung User Interfaces (HCI)
Informatik Theorie / Studium Kryptologie
Mathematik / Informatik Mathematik Graphentheorie
Naturwissenschaften
Technik Elektrotechnik / Energietechnik
Schlagworte Analysis-by-Synthesis (AbS) framework • Binary Secret Images • cryptosystem • Data Decryption • Digital Halftoning • Grayscale Secret Images • Privacy Protection • Radially Averaged Power Spectrum Density (RAPSD) • Vector Visual Cryptography • Visual Cryptography Algorithms
ISBN-10 981-13-8289-1 / 9811382891
ISBN-13 978-981-13-8289-5 / 9789811382895
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