Adaptive reversible video watermarking based on motion-compensated prediction error expansion with pixel selection

In this study, a motion-compensated prediction error expansion-based adaptive reversible video watermarking algorithm is proposed. Blocks of motion-compensated frames are classified as smooth and non-smooth according to their prediction errors. Unlike the current reversible video watermarking methods that apply a single watermarking strategy to all blocks, the proposed method uses two different strategies for smooth and non-smooth blocks. This adaptive strategy is shown to increase watermarking capacity. In addition, an approach is suggested to detect those pixels causing high distortion in the watermarked video and they are not used in watermarking to limit the distortion occurring in the original video. Simulations show that the proposed method is superior to existing methods in terms of capacity and distortion.