High Payload Reversible Watermarking for Securing Medical Images in a Cloud Environment
This paper proposes a high payload reversible data hiding technique in integer lifting transform domain, with a special application to medical images stored in a cloud-based medical enterprise archive. Owing to the nature of these image statistics, the neighbor pixel values are similar mostly, and hence, their differences are observed to be close or equal to zero. A histogram constructed out of this difference factor is exploited for reversible data embedding. Further, data are embedded at multiple levels, and hence, the proposed scheme facilitates higher payload capacity than the conventional single-level histogram-based techniques. The distortion introduced due to secret payload embedding is alleviated to the minimum, and hence, the perceptual quality of the stego images is exceptional, since the embedding is done in the integer lifting wavelet transform domain. The experimental results with medical images demonstrate that the proposed scheme provides a better security with larger payload and a better image quality than some advanced prior schemes.
KeywordsDifference-expansion-based schemes Histogram-shifting-based schemes Prediction-based schemes Interpolation-based schemes Robustness-based schemes HVS-based schemes