Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

Abstract

Few previous Reversible Visible Watermarking (RVW) schemes have both good transparency and watermark visibility. An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding (BTC) compressed domain, called TVB-RVW is proposed in this paper. A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation. Then, a visual perception factor computation model is devised by fusing texture and luminance characteristics. An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC domain. Moreover, a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark removal. The visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark embedding. Extensive experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility, and it can achieve a good balance between transparency and watermark visibility.