Efficient lossless watermarking algorithm using gradient sorting and selective embedding

Abstract

Prediction-error expansion based lossless watermarking techniques for images have received extensive attention due to versatile performance. In particular, the capacity-distortion control is one of the most important studies. This paper investigates that data-hiding distortion is mainly affected by the occurrence order of the prediction-error distribution, and capacity is affected by the occurrence number of the prediction errors. To make better control of the prediction-error distortion, we propose a novel scheme with three components: the gradient adjacent prediction (GAP), gradient sorting, and selective embedding. The capacity of the proposed scheme is high because GAP generates highly concentrated prediction-error histogram. Furthermore, the gradient sorting and selective embedding could avoid and reduce the unnecessary distortion. Experimental results show that the proposed scheme outperforms the competitors in terms of capacity enhancement and distortion reduction.