Paper Info
Title
Audio informed watermarking by means of dirty trellis codes
Abstract
We present a frequency-domain audio watermarking scheme based on dirty convolutional codes. In the scenario addressed by the paper, a masking threshold is properly defined to allow the identification of the inaudibility of the inserted data. In particular, the masking threshold defines the maximum modification which can applied to each frequency sample. This represents a major deviation from classical distortion models, in which inaudibility is defined in terms of Mean Square Error (MSE), thus making the direct application of the dirty coding paradigm, derived from a theoretical perspective, problematic. To get around this problem, we first define an informed watermarking scheme based on trellis codes, in which the same information is represented by several paths of the trellis. Then, we determine both the specific structure of the codes and the algorithm for information embedding. The proposed scheme is proved to be robust to D/A and A/D conversion, multipath, scaling, noise, and time misalignment.
Year
DOI
Venue
2013
10.1109/ITA.2013.6502924
ITA
Keywords
Field
DocType
time misalignment,a/d conversion,dirty trellis codes,analogue-digital conversion,noise,masking threshold,audio watermarking,audio informed watermarking,mean square error,scaling,multipath,dirty convolutional codes,mse,d/a conversion,inserted data,inaudibility identification,frequency-domain audio watermarking,information embedding,classical distortion,convolutional codes,digital-analogue conversion,mean square error methods,trellis codes
Multipath propagation,Digital watermarking,Convolutional code,Computer science,Mean squared error,Theoretical computer science,Masking threshold,Coding (social sciences),Distortion,Scaling
Conference
ISBN
Citations 
PageRank 
978-1-4673-4648-1
1
0.40
References 
Authors
12
3
Name
Order
Citations
PageRank
Andrea Abrardo137647.39
M. Barni23091246.21
Gianluigi Ferrari31690139.36