Reversible Data Hiding for Block Truncation Coding Compressed Images Based on Prediction-Error Expansion

Abstract

In this paper, we propose a new reversible data hiding scheme for images compressed by Block Truncation Coding (BTC). The original image is divided into n × n sized non-overlapping blocks and encoded by BTC to obtain the BTC-compressed bitstream. Each block is presented by a low mean value, a high mean value and a binary bitmap. The proposed scheme exploits the correlation among adjacent blocks and embeds data into low mean value and high mean value by prediction-error expansion. Meanwhile, no additional overflow/underflow location map is required. For those blocks with the same low mean value and high mean value, data are embedded into the bitmaps. Experimental results show that the proposed scheme achieves high embedding capacity and great image quality.