Abstract: Reversible data hiding in encrypted images (RDHEI) is essential for safeguarding sensitive information within the encrypted domain. In this study, we propose an intelligent pixel predictor based on a residual group block and a spatial attention module, showing superior pixel prediction performance compared to existing predictors. Additionally, we introduce an adaptive joint coding method that leverages bit-plane characteristics and intra-block pixel correlations to maximize embedding space, outperforming single coding approaches. The image owner employs the presented intelligent predictor to forecast the original image, followed by encryption through additive secret sharing before conveying the encrypted image to data hiders. Subsequently, data hiders encrypt secret data and embed them within the encrypted image before transmitting the image to the receiver. The receiver can extract secret data and recover the original image losslessly, with the processes of data extraction and image recovery being separable. Our innovative approach combines an intelligent predictor with additive secret sharing, achieving reversible data embedding and extraction while ensuring security and lossless recovery. Experimental results demonstrate that the predictor performs well and has a substantial embedding capacity. For the Lena image, the number of prediction errors within the range of [-5, 5] is as high as 242 500 and our predictor achieves an embedding capacity of 4.39 bpp.

基于加性秘密共享和智能预测器自适应联合编码的密文图像可逆信息隐藏

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