Robust Data Hiding Scheme for Compressively Sensed Signals

We consider the problem of linear data hiding or watermark embedding directly onto compressively sensed measurements (CSMs). In our encoding and decoding scheme, we seek exact recovery of concealed data and a small reconstruction error for a sparse signal under the additive noise model. We propose an efficient Alternating Direction of Methods of Multiplier (ADMM) based decoding algorithm and we show through experimental results that proposed decoding scheme is more robust against additive noise compared to competing algorithms in the literature.