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Scalar costa scheme for information embedding

Eggers, J.J., Bauml, R., Tzschoppe, R., Girod, B.·2003·IEEE Transactions on Signal Processing

Abstract

Research on information embedding, particularly information hiding techniques, has received considerable attention within the last years due to its potential application in multimedia security. Digital watermarking, which is an information hiding technique where the embedded information is robust against malicious or accidental attacks, might offer new possibilities to enforce the copyrights of multimedia data. In this paper, the specific case of information embedding into independent identically distributed (IID) data and attacks by additive white Gaussian noise (AWGN) is considered. The original data is not available to the decoder. For Gaussian data, in 1983, Costa proposed a scheme that theoretically achieves the capacity of this communication scenario. However, Costa's scheme is not practical. Thus, several research groups have proposed suboptimal practical communication schemes based on Costa's idea. The goal of this paper is to give a complete performance analysis of the scalar Costa scheme (SCS), which is a suboptimal technique using scalar embedding and reception functions. Information theoretic bounds and simulation results with state-of-the-art coding techniques are compared. Further, reception after amplitude scaling attacks and the invertibility of SCS embedding are investigated.

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Metadata

Authors
Eggers, J. J., Bauml, R., Tzschoppe, R., & Girod, B.
Venue
IEEE Transactions on Signal Processing
Published
2003-04
Volume
51
Issue
4
Pages
1003-1019
ISSN
1053-587X (ISSN-L)
OpenAlex
W2139490206
Cited by
357
References
24
FWCI
38.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Scalar costa scheme for information embedding. https://app.cochat.ai/papers/10.1109/tsp.2003.809366
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Eggers, J. J., Bauml, R., Tzschoppe, R., & Girod, B. (2003). Scalar costa scheme for information embedding. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2003.809366

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