© 2020 by the authors.We propose a novel data hiding method in an audio host with a compressive sampling technique. An over-complete dictionary represents a group of watermarks. Each row of the dictionary is a Hadamard sequence representing multiple bits of the watermark. Then, the singular values of the segment-based host audio in a diagonal matrix are multiplied by the over-complete dictionary, producing a lower size matrix. At the same time, we embed the watermark into the compressed audio. In the detector, we detect the watermark and reconstruct the audio. This proposed method offers not only hiding the information, but also compressing the audio host. The application of the proposed method is broadcast monitoring and biomedical signal recording. We can mark and secure the signal content by hiding the watermark inside the signal while we compress the signal for memory efficiency. We evaluate the performance in terms of payload, compression ratio, audio quality, and watermark quality. The proposed method can hide the data imperceptibly, in the range of 729-5292 bps, with a compression ratio 1.47-4.84, and a perfectly detected watermark.

Compressed sensing,Compressive sampling,Data hiding,Hadamard,Singular value decomposition,Spread spectrum,Watermark

This research was funded by Institut Technology Bandung and the Ministry of Research, Technology and Higher Education of Indonesia in 2020. This research is supported by Institut Teknologi Bandung and Telkom University.

https://doi.org/10.3390/app10124338