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03888nam a2200553 4500 |
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978-3-030-15726-5 |
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20191027033102.0 |
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190423s2019 gw | s |||| 0|eng d |
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|a 9783030157265
|9 978-3-030-15726-5
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|a 10.1007/978-3-030-15726-5
|2 doi
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|d GrThAP
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|a 621.382
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|a Dhar, Pranab Kumar.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Advances in Audio Watermarking Based on Matrix Decomposition
|h [electronic resource] /
|c by Pranab Kumar Dhar, Tetsuya Shimamura.
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|a 1st ed. 2019.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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|a XI, 56 p. 25 illus., 16 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
|x 2191-737X
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|a Chapter1: Introduction -- Chapter2: LWT-Based Audio Watermarking Using FWHT and SVD -- Chapter3: Audio Watermarking Based on LWT and QRD -- Chapter4: Audio Watermarking Based on FWHT and LUD -- Chapter5: Audio Watermarking Based on LWT and SD -- Chapter6: Conclusions and Future Work.
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|a This book introduces audio watermarking methods in transform domain based on matrix decomposition for copyright protection. Chapter 1 discusses the application and properties of digital watermarking. Chapter 2 proposes a blind lifting wavelet transform (LWT) based watermarking method using fast Walsh Hadamard transform (FWHT) and singular value decomposition (SVD) for audio copyright protection. Chapter 3 presents a blind audio watermarking method based on LWT and QR decomposition (QRD) for audio copyright protection. Chapter 4 introduces an audio watermarking algorithm based on FWHT and LU decomposition (LUD). Chapter 5 proposes an audio watermarking method based on LWT and Schur decomposition (SD). Chapter 6 explains in details on the challenges and future trends of audio watermarking in various application areas. Introduces audio watermarking methods for copyright protection and ownership protection; Describes watermarking methods with encryption and decryption that provide excellent performance in terms of imperceptibility, robustness, and data payload; Discusses in details on the challenges and future research direction of audio watermarking in various application areas.
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|a Signal processing.
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|a Image processing.
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|a Speech processing systems.
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|a Computational linguistics.
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|a Algorithms.
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|a Signal, Image and Speech Processing.
|0 http://scigraph.springernature.com/things/product-market-codes/T24051
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|a Computational Linguistics.
|0 http://scigraph.springernature.com/things/product-market-codes/N22000
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|a Algorithm Analysis and Problem Complexity.
|0 http://scigraph.springernature.com/things/product-market-codes/I16021
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|a Shimamura, Tetsuya.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783030157258
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|i Printed edition:
|z 9783030157272
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830 |
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|a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
|x 2191-737X
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856 |
4 |
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|u https://doi.org/10.1007/978-3-030-15726-5
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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|a Engineering (Springer-11647)
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