A Source and Channel Coding Approach to Data Hiding with Application to Hiding Speech in Video

Digital data hiding is a technology being developed for multimedia services, where non-trivial amounts of signature data is invisibly hidden inside a host data source by the owner before the latter is freely distributed. Only those authorized can recover the hidden data from the host, even after the latter has undergone standard transformations such as compression. In this work we adopt a quantitative source and channel coding approach to hiding large amounts of compressible signature data inside the raw host. The signature data is source coded by vector quantization, and the indices are embedded in the host by perturbing it using orthogonal transform domain vector perturbations. The transform coefficients of the parent data are grouped into vectors, and the vectors are perturbed using noise-resilient channel codes derived from multidimensional lattices. The perturbations are constrained by a maximum allowable mean-squared error that can be introduced in the host. The generic approach is readily adapted to make retrieval possible even for applications where the original host is not available to the retriever. In this work, the scheme is applied to hiding speech in video. The host video is wavelet transformed frame by frame, and vectors of coefficients are perturbed using lattice channel codes to represent hidden vector quantized speech. The embedded video is subjected to H.263 compression before retrieving the hidden speech from it. The retrieved speech is intelligible even with large compression ratios of the host video.