为提高密文域可逆信息隐藏的嵌入容量，提出了一种基于自适应中值预测（adaptive median edge detection, AMED）和霍夫曼编码的密文域可逆信息隐藏算法。所提算法首先对载体图像进行块级扩展。然后，预测阶段引入自适应参数提出中值预测（median edge detection, MED）优化方案，参数会随着图像纹理特征而变化，进而提高像素预测准确度。最后，对像素高有效位信息（most significant bit, MSB）进行标记，采用霍夫曼编码对标记结果进行压缩，从而腾出空间进行秘密信息的嵌入。实验结果表明，本文算法可以在保证可逆恢复的基础上实现秘密信息的正确提取。同时，与现有算法相比，嵌入容量有所提高，平均嵌入率高达2.632 0 bpp。

In order to improve the embedding capacity of reversible data hiding in encrypted images, a reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and Huffman coding was proposed. In the proposed algorithm, the cover image was first subjected to block-level expansion. Subsequently, the adaptive parameters were introduced during the prediction phase to propose an optimization scheme for median edge detection (MED), where parameters vary with image texture features to enhance pixel prediction accuracy. Finally, the most significant bits (MSB) of pixels were marked, and the marked results were compressed using Huffman coding to free up space for embedding secret data. Experimental results demonstrated that the algorithm could accurately extract secret data while ensuring reversibility. Moreover, compared to existing algorithms, the embedding capacity had been increased, with an average embedding rate reaching as high as 2.632 0 bits per pixel (bpp).