Advances in Audio Watermarking Based on Matrix Decomposition

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 Wals...

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Bibliographic Details
Main Authors: Dhar, Pranab Kumar (Author, http://id.loc.gov/vocabulary/relators/aut), Shimamura, Tetsuya (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edition:1st ed. 2019.
Series:SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
Subjects:
Online Access:Full Text via HEAL-Link
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245 1 0 |a Advances in Audio Watermarking Based on Matrix Decomposition  |h [electronic resource] /  |c by Pranab Kumar Dhar, Tetsuya Shimamura. 
250 |a 1st ed. 2019. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2019. 
300 |a XI, 56 p. 25 illus., 16 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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490 1 |a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,  |x 2191-737X 
505 0 |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. 
520 |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. 
650 0 |a Signal processing. 
650 0 |a Image processing. 
650 0 |a Speech processing systems. 
650 0 |a Computational linguistics. 
650 0 |a Algorithms. 
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650 2 4 |a Computational Linguistics.  |0 http://scigraph.springernature.com/things/product-market-codes/N22000 
650 2 4 |a Algorithm Analysis and Problem Complexity.  |0 http://scigraph.springernature.com/things/product-market-codes/I16021 
700 1 |a Shimamura, Tetsuya.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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