Information-theoretic analyses for data hiding prescribe embedding the hidden data in the choice of quantizer for the host data. In this paper, we propose practical realizations of this prescription for data hiding in images, with a view to hiding large volumes of data with low perceptual degradation. The hidden data can be recovered reliably under attacks, such as compression and limited amounts of image tampering and image resizing. The three main findings are as follows. 1) In order to limit perceivable distortion while hiding large amounts of data, hiding schemes must use image-adaptive criteria in addition to statistical criteria based on information theory. 2) The use of local criteria to choose where to hide data can potentially cause desynchronization of the encoder and decoder. This synchronization problem is solved by the use of powerful, but simple-to-implement, erasures and errors correcting codes, which also provide robustness against a variety of attacks. 3) For simplicity, scalar quantization-based hiding is employed, even though information-theoretic guidelines prescribe vector quantization-based methods. However, an information-theoretic analysis for an idealized model is provided to show that scalar quantization-based hiding incurs approximately only a 2-dB penalty in terms of resilience to attack.

No abstract

No abstract

We investigate wideband space-time communication on the uplink of an outdoor cellular system, in which the base station is equipped with N antennas and the mobile has a single antenna. We assume noncoherent reception at the base station, which incurs significantly less overhead than pilot-based estimation of the space-time channel from each mobile to the base station. Noncoherent communication techniques are particularly well suited to outdoor cellular systems for which channel time variations are significant due to mobility at vehicular speeds. As is common in outdoor cellular systems, we assume little or no scattering around the base station, so that, from the viewpoint of the base station antenna array, the incoming signal from a given mobile has a narrow power angle profile. Thus, the spatial channel covariance matrix is typically highly colored, having one or two dominant eigenmodes. We demonstrate that large beamforming gains are achievable without explicit estimation of the space-time channel, while only processing a relatively few number of dominant eigenmodes.Consider the received signal Y f at frequency bin f in an OFDM system (1). The N × 1 space-time channel H f for each subcarrier is well-modeled as identically distributed complex Gaussian random vectors that decorrelate across frequency [1].Thus, the spatial covariance matrix C = E[H f H † f ] can be obtained by averaging over subcarriers, without requiring any pilot overhead. A spectral decomposition of the channel co-variance matrix yields (2), where the eigenvector matrix U = [U1 . . . UN ] is unitary, and Λ is diagonal with eigenvalues {λ l } arranged in decreasing order. The eigenvalue λ l represents the strength of the channel on l th eigenmode U l . We propose an eigenbeamforming receiver that projects the received signal in each subcarrier along the L (typically much smaller than the number of receive elements N ) dominant eigenmodes of the estimated channel covariance matrix, {U l } L l=1 . Beamforming along the dominant eigenmodes of the channel creates parallel, independently fading channels for the same transmitted data. For each of the L eigenmodes, we employ noncoherent coded modulation strategies with turbo-like joint data and channel estimation, as in prior work on single antenna channels [2,3,4]. Thus, by appropriately leveraging the covariance estimate available in a wideband system, the noncoherent eigenbeamforming receiver provides many of the benefits of explicit space-time channel estimation without incurring its overhead. For example, beamforming gains in received SNR (relative to a single antenna system) are realized, 1 This work was supported by Motorola and the University of California Cooperative Research Program under a Communications Research (CoRe) grant.while incurring reasonable complexity by using a small number of dominant eigenmodes for demodulation and decoding.In addition to an SNR advantage from scaling up the number of receive elements, diversity gains are provided by the L parallel, independent fading channels...

No abstract

Information-theoretic analyses for data hiding prescribe em bedding the hidden data in the choice of quantizer for the host data. In this paper, we consider a suboptimal implementation of this prescription, with a view to hiding high volumes of data in images with low perceptual degradation. Our two main findings are as follows: (a) In order to limit perceptual distortion while hiding large amounts of data, the hiding scheme must use perceptual criteria in addition to information-theoretic guidelines. (b) By focusing on "benign" JPEG compression attacks, we are able to attain very high volumes of embedded data, comparable to information-theoretic capacity estimates for the more malicious Additive White Gaussian Noise (AWGN) attack channel, using relatively simple embedding techniques.

No abstract

No abstract