Reversible Watermarking Algorithm Using Sorting and Prediction

TLDR

The paper proposes a reversible image watermarking algorithm that largely avoids using a location map. The method embeds data by sorting prediction errors according to local variance magnitude and, when necessary, employing a small location map to increase payload while minimizing distortion. Experiments show the scheme achieves higher payloads with lower distortion than four existing reversible watermarking methods.

Abstract

This paper presents a reversible or lossless watermarking algorithm for images without using a location map in most cases. This algorithm employs prediction errors to embed data into an image. A sorting technique is used to record the prediction errors based on magnitude of its local variance. Using sorted prediction errors and, if needed, though rarely, a reduced size location map allows us to embed more data into the image with less distortion. The performance of the proposed reversible watermarking scheme is evaluated using different images and compared with four methods: those of Kamstra and Heijmans, Thodi and Rodriguez, and Lee et al. The results clearly indicate that the proposed scheme can embed more data with less distortion.