├── Main.m ├── readme.txt ├── Embed_Data.m ├── Main_UCID.m ├── Map_Binary.m ├── 测试图像 ├── Man.tiff ├── Lena.tiff ├── Airplane.tiff ├── Baboon.tiff ├── Jetplane.tiff └── Tiffany.tiff ├── Category_Mark.m ├── Encrypt_Data.m ├── Encrypt_Embed.m ├── Encrypt_Image.m ├── Extract_Data.m ├── Huffman_Code.m ├── Main_BOSSbase.m ├── Recover_Image.m ├── Huffman_DeCode.m ├── Predictor_Value.m ├── 0-数据集-0 ├── bpp_UCID.mat ├── num_UCID.mat ├── bpp_BOSSbase.mat ├── num_BOSSbase.mat ├── Average_bpp_UCID.m ├── bpp_BOWS2OrigEp3.mat ├── num_BOWS2OrigEp3.mat ├── Average_bpp_BOSSbase.m └── Average_bpp_BOW2OrigEp3.m ├── Binary_Decimalism.m ├── Decimalism_Binary.m ├── Main_BOWS2OrigEp3.m └── README.md /Main.m: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/edu-yinzhaoxia/Reversible-Data-Hiding-in-Encrypted-Images-Based-on-multi-MSB-Prediction-and-Huffman-Coding/HEAD/Main.m 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original image can be restored losslessly. In this paper, a high-capacity RDHEI algorithm based on multi-MSB (most significant bit) prediction and Huffman coding is proposed. At first, multi-MSB of each pixel was predicted adaptively and marked by Huffman coding in the original image. Then, the image was encrypted by a stream cipher method. At last, the vacated space can be used to embed additional data by multi-MSB substitution. Experimental results show that our method achieved higher embedding capacity while comparing with the state-of-the-art methods. 10 | 11 | ## 摘要 12 | 随着云存储和隐私保护的发展，隐藏在加密图像中的可逆数据(RDHEI)作为一种可以:在图像加密域中嵌入额外的数据，确保嵌入的数据能够被无错误地提取，并且能够无损地恢复原始图像的技术越来越受到人们的关注。本文提出了一种基于多msb (most significant bit)预测和霍夫曼编码的大容量RDHEI算法。首先对原始图像中每个像素点的多msb进行自适应预测，并用霍夫曼编码进行标记。然后采用流密码方法对图像进行加密。最后，通过多msb替换，利用空出的空间嵌入额外的数据。实验结果表明，与现有的方法相比，我们的方法实现了更高的嵌入容量。 13 | 14 | ## How to cite our paper 15 | @article{yin2019reversible, 16 | title={Reversible data hiding in encrypted images based on multi-MSB prediction and Huffman coding}, 17 | author={Yin, Zhaoxia and Xiang, Youzhi and Zhang, Xinpeng}, 18 | journal={IEEE Transactions on Multimedia}, 19 | volume={22}, 20 | number={4}, 21 | pages={874--884}, 22 | year={2019}, 23 | publisher={IEEE} 24 | } 25 | --------------------------------------------------------------------------------