This paper describes high data-rate audio data hiding using the IntMDCT. The IntMDCT is an integer approximation of the MDCT with perfect reconstruction. Based on this transform, we describe a straight-forward way to embed data and extract it in a bit-exact manner while perceptual transparency is maintained. Since the IntMDCT spectrum can be used to obtain a closer approximation of the masking threshold compared to time domain approaches, it is possible to achieve higher data rates. In a simple experimental implementation, we found we could embed data at rates up to about 140 kb/s without introducing audible distortions

In this paper, lossless audio coding using the integer modified discrete cosine transform (IntMDCT) is discussed. The IntMDCT is constructed as an integer approximation of the MDCT using the lifting scheme and is reversible. The rounding error shape of the IntMDCT is derived. When the spectral energy of the input audio signal is concentrated at the low frequencies, the rounding error spectrum limits the lossless coding performance. A method for shaping the rounding error in the transform domain is presented. This rounding error shaping scheme manipulates the error so that it is below the spectral envelope of the signal at the high frequencies in order to improve the lossless coding performance for the signal. Examples of an error shaping filter design are presented and verified by simulations. An IntMDCT-based lossless coding implementation is carried out to illustrate the use of the error shaping filters

The integer modified discrete cosine transform (IntMDCT), an integer approximation of the MDCT, is a reversible transform realized by the lifting scheme and thus is a useful transform for lossless audio coding. Because of the integer approximation, however, the approximation error appears as a "noise floor" in the transform domain and limits the lossless coding efficiency. In this paper, a theoretical analysis of the approximation error of the IntMDCT is discussed. The result is then used to design a simple test filter applied to each rounding operation of the IntMDCT in such a way that the error spectrum is shaped towards the low frequencies. As a result, especially when the spectral energy of an input signal is concentrated in the low frequency domain, the lossless coding efficiency is improved.

Recently lifting-based integer transforms have received much attention, especially in the area of lossless audio and image coding. The usual approach is to apply the lifting scheme to each Givens rotation. Especially in the case of long transform sizes in audio coding applications, this leads to a considerable approximation error in the frequency domain. This paper presents a multidimensional lifting approach for reducing this approximation error. In this approach, large parts of the transform are calculated without rounding operations, only the output is rounded and added. The new approach is applied and evaluated for both the integer modified discrete cosine transform (IntMDCT) and the integer fast Fourier transform (IntFFT).