Improved block redundancy mining based reversible data hiding using multi-sub-blocking

In difference/prediction error expansion, an efficient capacity-distortion trade-off generally indicates excellence in embedding performance. From this point of view, existing schemes which generate difference/prediction error in block-by-block manner are far from efficient and uniform-blocking may be the main reason. To overcome this drawback, a novel multi-sub-blocking (MSB) strategy which enables three or even more various-sized blocks based embedding is proposed in this paper. After initial division, the dispersion of pixel values within block is predicted to identify exceptional block which may produce to-be-shifted pixels. Then further division would be inevitable for those blocks to obtain closer correlation of pixels within smaller block to achieve improved block redundancy mining. To verify the advantage of MSB, this work extends two existing RDH schemes by incorporating MSB. Experimental results demonstrate that the two proposed schemes both achieve improved embedding performance and outperform previous related state-of-the-art schemes.