Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Compressive Sampling with Multiple Bits Spread Spectrum-Based Data Hiding

Version 1 : Received: 9 May 2020 / Approved: 10 May 2020 / Online: 10 May 2020 (16:07:21 CEST)

A peer-reviewed article of this Preprint also exists.

Budiman, G.; Suksmono, A.B.; Danudirdjo, D. Compressive Sampling with Multiple Bit Spread Spectrum-Based Data Hiding. Appl. Sci. 2020, 10, 4338. Budiman, G.; Suksmono, A.B.; Danudirdjo, D. Compressive Sampling with Multiple Bit Spread Spectrum-Based Data Hiding. Appl. Sci. 2020, 10, 4338.

Abstract

We propose a novel data hiding method in an audio host with a compressive sampling technique. An over-complete dictionary represents a group of the watermark. Each row of the dictionary is a Hadamard sequence representing multiple bits of the watermark. Then, the singular values of segment-based host audio in a diagonal matrix multiply 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 a 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 range 729-5292 bps with compression ratio 1.47-4.84 and perfect detected watermark.

Keywords

compressive sampling; compressed sensing; watermark; data hiding; spread spectrum; singular value decomposition; Hadamard

Subject

Engineering, Electrical and Electronic Engineering

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