Reversible Data Hiding for Audio Based on Prediction Error Expansion

Yan, Diqun; Wang, Rangding

doi:10.1109/iih-msp.2008.27

Cited by 28 publications

(31 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The previous expansion methods always expand the integer variable, such as amplitude [1], prediction errors [2], [6], or spectral coefficient [3], two-fold. A variable expansion method expands an integer variable α-fold.…”

Section: Variable Expansion Methodsmentioning

confidence: 99%

“…If α = 2, the proposed method is identical to the previous two-fold expansion method, with the exception of inverting subtraction and the addition of a payload bit [6]. Equation (2) demonstrates how the payload data q ∈ {0, 1} are embedded into the integer host data h to obtain the stego data s. Equation (1) is an expansion and rounding function G(. ).…”

Section: Variable Expansion Methodsmentioning

confidence: 99%

“…Several methods have been proposed for the reversible data hiding of audio data. These methods can be classified into three categories according to the domain of the embedded data: waveform domain [1], [2], spectral domain [3], [4], and compressed data domain [5].…”

Section: Introductionmentioning

confidence: 99%

“…However, the concealment of payload data is imperfect using this method because payload data are always represented by the least significant bit (LSB) data in the stego waveform. Yan and Wang [2] proposed a prediction error expansion method using linear prediction. In this method, the difference between the current and predicted amplitude is doubled, and the result is summed with the payload.…”

Section: Introductionmentioning

confidence: 99%

“…Because a location map, which is employed to prevent amplitude overflow, is not embedded, the improved method also achieves a storage capacity of nearly 1 bit per sample as the payload. However, the conventional method [2] and the author's improved method [6] can only be applied to the entire host signal. Dividing the host signal into the framed signals of equal length and applying these methods to the framed signals to get the concatenated stego signal are possible, but payload extraction and recovery of the host signal from the unmodified part of a partially mod-ified stego signal is not possible, because locating the initial sample of the frame in the corresponding stego signal is required.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Reversible Audio Data Hiding Based on Variable Error-Expansion of Linear Prediction for Segmental Audio and G.711 Speech

Nishimura

2016

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARY Reversible data hiding is a technique in which hidden data are embedded in host data such that the consistency of the host is perfectly preserved and its data are restored during extraction of the hidden data. In this paper, a linear prediction technique for reversible data hiding of audio waveforms is improved. The proposed variable expansion method is able to control the payload size through varying the expansion factor. The proposed technique is combined with the prediction error expansion method. Reversible embedding, perfect payload detection, and perfect recovery of the host signal are achieved for a framed audio signal. A smaller expansion factor results in a smaller payload size and less degradation in the stego audio quality. Computer simulations reveal that embedding a random-bit payload of less than 0.4 bits per sample into CD-format music signals provide stego audio with acceptable objective quality. The method is also applied to G.711 µ-law-coded speech signals. Computer simulations reveal that embedding a random-bit payload of less than 0.1 bits per sample into speech signals provide stego speech with good objective quality.

show abstract

Section: Variable Expansion Methodsmentioning

confidence: 99%

Section: Variable Expansion Methodsmentioning

confidence: 99%