目的 像素置换作为一种可逆信息隐藏方式具有良好的抗灰度直方图隐写分析能力，但嵌入容量偏小一直是其缺陷。针对这一问题，提出了一种基于像素置换的自适应可逆信息隐藏算法。方法 首先，与传统2×2像素块结构相比构造了尺寸更小的像素对结构，使得载体图像可以被更稠密地分割，为嵌入容量的提升提供了基数条件。其次，提出适用于该新像素结构的可嵌像素对（EPP）筛选条件，避免嵌入过程引起图像质量大幅下降。之后，根据EPP的灰度趋势差异对其进行自适应预编码，提高Huffman编码压缩比，进一步提升算法嵌入容量。最终，通过像素置换嵌入信息。结果 与2×2像素块结构的非自适应图像隐写算法相比，在同样保证灰度直方图稳定性的情况下该算法的PSNR提高了32%左右，嵌入容量提高了95%以上。其中自适应性对嵌入容量提升的贡献极大。结论 本文算法同时具有抗灰度直方图隐写分析能力与高嵌入容量性的可逆信息隐藏。算法构造了更高效的可嵌单位，并且针对不同载体图像的特点对其可嵌区域进行差异化编码。实验结果表明，本文算法在具有更好的不可见性的同时，嵌入容量得到大幅提升。

Objective Data hiding is a well-known method used to protect secret information or provide authentication. Thus, we can embed secret data into carriers, such as images and videos. After the embedding, the carriers can still perform as they were. Data hiding has many advantages over traditional encryption methods. Encryption algorithm can be regarded as a function used to transform secret data into cipher texts, and secret data and keys are parameters. However, making cipher texts understandable remains a challenge. If cipher texts are captured by an attacker, the attacker can easily notice that the texts must be processed, although he plain texts cannot be generated immediately. This situation may cause security issues. Such issues cannot happen in data hiding because the data-hiding process does not influence carrier readability. Humans also hardly notice the difference between cover and stego carriers. As a way of reversible data hiding, pixel permutation has a good ability of anti-gray histogram steganalysis but with low payload capacity. An adaptive reversible data-hiding algorithm based on pixel permutation is accordingly proposed. Method First, a more efficient embedding unit structure than the conventional 2×2 pixel block structure is proposed. A cover image can be densely segmented, which provides a condition for improving payload capacity. For every embedded bit, the proposed triangular embedded pixel pair consists of 3 pixels. The specific shape and position of all embeddable pixel pairs (EPPs) are determined by the keys shared between sender and receiver. Second, EPPs are screened from all pixel pairs to avoid embedding secret bits in the pixel pairs that may cause a significant decline in image quality. Adaptive precoding is conducted according to the characteristic of gray trend of EPPs, such that the 0, 1 distribution in the binary sequence that represents all EPPs is as asymmetrical as possible. This adaptive precoding process effectively improves Huffman coding compression ratio to enhance payload capacity. Huffman coding is a method of compressing a sequence using the frequencies of different arrays. This method spends a minimal storage on arrays with a high frequency and adopts long code words to represent arrays that seldom occur. Finally, data are embedded into the cover image by permuting the two end pixels of the corresponding EPP bit by bit. Data extraction is the inverse process of data embedding. Receivers can obtain all correct EPPs according to the keys and two pixel pair embedding conditions, and secret data can be easily extracted by using a location map. Eight different gray-scale images are randomly selected from a standard gray-scale test image data set for the experiments. A key is created by a pseudo random number generator. For every cover image, we test the payload capacity and PSNR of a full-load stego image. The histograms of cover and stego images are shown to prove the histogram robustness of the proposed scheme. Result Experimental results demonstrate that the PSNR of the proposed scheme is improved by approximately 32% and its payload capacity is increased by more than 95% compared with those of a non-adaptive data-hiding algorithm with a 2×2 pixel block structure. The proposed scheme also keeps the robustness of gray-scale histograms before and after the data-hiding process. Notably, adaptability plays a decisive role in capacity improvement. Conclusion This study presents a reversible information-hiding algorithm with high embedding capacity and a capability of anti-gray-scale histogram steganalysis. We construct an efficient embedding unit and differentiate embeddable regions for the characteristics of different cover images. The confidentiality of all embedding units is guaranteed by a key. The experimental results show that the proposed algorithm greatly improves payload capacity by adaptive precoding process and a special triangular pixel structure. Moreover, imperceptibility is kept in a high level by using appropriate EPP-filtering criteria. The proposed scheme considers the visual and statistical invisibilities of the data-hiding process. Consequently, the scheme provides a high security level for secret information when providing large embedding capacity of cover images. For practical applications, the proposed scheme can be utilized in secret information transmission, storage, and privacy protection. Although the payload capacity of the proposed scheme has been greatly enhanced compared with that of the same type of reversible data hiding methods, it remains lower than that of the methods without providing histogram robustness. Therefore, improving capacity while keeping confidentiality in a high level is worth of further research.