Secure sparse watermarking on DWT-SVD for digital images

Abstract

This paper suggests a sparse watermark image embedding scheme on the singular values of the pre-selected wavelet sub-band coefficients of the digital images. Dictionary learning (DL) method is used to make the watermark image sparse. Then a watermark decoder is designed based on the theory of compressed sensing (CS) in the framework of alternating direction method of multiplier (ADMM). The integration of DL and CS offers two benefits, firstly DL combined with singular value decomposition (SVD), enables protection against false positive detection (FPD) where the sparse watermark enhances embedding capacity at high imperceptibility of the hidden data. Simulation results show high visual quality for the watermarked images (PSNR = 60.45 dB, SSIM = 0.9997 and FSIM = 0.9979) and robustness (NCC value for the decoded watermark is ∼ 0.9) against various image processing operations including an unauthorized decoding - a typical value of 85% CS measurements lead to a watermarked image results in a FPD value of 0.42 that shows a visually indistinguishable watermark.