Dual Video Watermarking Algorithm Based on SIFT and HVS in the Contourlet Domain

Abstract

We propose dual un-compressed video watermarking algorithms based on human visual system and scale invariant feature transform (SIFT) in the contourlet domain. First, every frame is decomposed by contourlet transform to obtain the low-frequency band and several high-frequency sub-bands in different directions. The energy value of every high-frequency sub-band is calculated. The low-frequency sub-band and the high-frequency sub-bands of the largest energy values are chosen to be embedded into watermarking signals. Second, the first watermarking algorithm is realized to embed watermarking signals by adjusting the size ratio between the coefficient histograms of low-frequency sub-band because the coefficient histogram of low-frequency sub-band possesses invariance to conventional geometric transform. Third, to the second watermarking algorithm, the human visual masking threshold based on contourlet domain is calculated as the maximum embedding tolerance, which is embedded in the largest energy value of the high-frequency sub-band as watermarking signals to guarantee the imperceptibility. Finally, when the watermarked video frame suffered from geometrically attacks, the SIFT and fine corrections are combined to effectively correct and restore the synchronization between geometrically attacked video frames and watermarking signals. The experimental results indicate that: 1) the visual masking based on video motion information in the contourlet domain can effectively improve the transparency and 2) combining the histogram mapping in low-frequency sub-band coefficients with SIFT and fine corrections can resist common geometric attacks and therefore improve the robustness of the watermarking algorithm.