基于区域的图像信息隐藏算法

提出一种空间域信息隐藏算法。该算法结合了LSB和MSB的优点,将灰度值划分成一个个等长度区间,在每个区间都嵌入信息。信息嵌入是通过修改灰度值,而灰度值的变化是在区间范围内的,由于区间的范围较小,从而能够保证引起的图像失真是不可觉察的。同时考虑人类视觉系统的相关特性,选择出可用像素位置来嵌入信息,放弃不可用像素位置,进一步提高不可觉察性这一技术指标。实验结果表明,该算法隐藏容量较大,有较好的鲁棒性且易于实现。     

基于区域的图像信息隐藏算法

提出一种空间域信息隐藏算法。该算法结合了LSB和MSB的优点，将灰度值划分成一个个等长度区间，在每个区间都嵌入信息。信息嵌入是通过修改灰度值，而灰度值的变化是在区间范围内的，由于区间的范围较小，从而能够保证引起的图像失真是不可觉察的。同时考虑人类视觉系统的相关特性，选择出可用像素位置来嵌入信息，放弃不可用像素位置，进一步提高不可觉察性这一技术指标。实验结果表明，该算法隐藏容量较大，有较好的鲁棒性且易于实现。     

基于块参照像素的无损信息隐藏算法

提出一种具有高嵌入容量的图像无损信息隐藏算法。首先将载体图像分成互不重叠的子块,然后在每块中选定一个参照像素,并计算参照像素与块内其它像素的差。在像素差直方图移位产生冗余空间之后,机密信息就可以无损地嵌入到这些冗余空间中。该方法在机密信息提取后可完全恢复载体图像,而且提取机密信息和恢复载体图像不需要除机密信息长度之外的任何信息。实验结果表明了该算法的有效性。     

A novel adaptive steganography based on local complexity and human vision sensitivity

This paper presents a novel adaptive steganographic scheme that is capable of both preventing visual degradation and providing a large embedding capacity. The embedding capacity of each pixel is dynamically determined by the local complexity of the cover image, allowing us to maintain good visual quality as well as embedding a large amount of secret messages. We classify pixels into three levels based on the variance of the local complexity of the cover image. When determining which level of local complexity a pixel should belong to, we take human vision sensitivity into consideration. This ensures that the visual artifacts appeared in the stego image are imperceptible, and the difference between the original and stego image is indistinguishable by the human visual system. The pixel classification assures that the embedding capacity offered by a cover image is bounded by the embedding capacity imposed on three levels that are distinguished by two boundary thresholds values. This allows us to derive a combination ratio of the maximal embedding capacity encountered with at each level. Consequently, our scheme is capable of determining two threshold values according to the desired demand of the embedding capacity requested by the user. Experimental results demonstrated that our adaptive steganographic algorithm produces insignificant visual distortion due to the hidden message. It provides high embedding capacity superior to that offered by a number of existing schemes. Our algorithm can resist the RS steganalysis attack, and it is statistically invisible for the attack of histogram comparison. The proposed scheme is simple, efficient and feasible for adaptive steganographic applications.     

Combining LSB embedding with modified Octa-PVD embedding

This paper proposes a new image steganographic method that effectively combines LSB embedding with Octa-PVD embedding. A cover image is divided into non-overlapping 3?×?3 sub-blocks, the n least significant bits of the center pixel of each sub-block is first substituted by secret data (n-LSB substitution). Then, the differences between the center pixel and its eight neighbors are calculated. For each direction, if the difference is equal or larger than a threshold (predefined by users or automatically determined by image analysis), secret data is embedded into the neighbor pixel by n-LSB substitution. Otherwise, secret data is embedded by PVD embedding, but into the neighbor pixel only. Consequently, depending on the conditions of each sub-block, a single embedding method can be used to the whole sub-block, or two embedding methods can be used alternately within a sub-block. Comparisons with existing LSB or multi-directional PVD embedding methods demonstrate that the proposed method has more optimized and higher embedding capacity and PSNR.

     

A TRIBUTE TO ALF MONGÉ

Abstract

A data hiding method using three-directional pixel-value differencing for gray images is presented in this article. The cover image is divided into non-overlapping 2 × 2 sub-blocks, and the basis pixel is selected to calculate three different values of a sub-block. Difference values are replaced by embedding the number of secret bits that are referenced by the range table. For three pixel pairs in the sub-block, the optimal pixel adjustment is preceded to reduce the distortion of visual quality. The experimental results demonstrate that the proposed method provides a high capacity and good visual quality.     

基于小波对比度和模函数的安全密写算法

针对图像隐写中大容量、高保真度和安全性问题,依据人眼对变换剧烈及较暗区域均不敏感的视觉特点,结合模函数周期性运算,提出一种基于小波对比度和模函数运算的高保真图像隐写算法。该方法首先将载体图像按固定大小分块并计算其小波对比度,然后依据小波对比度确定各块嵌入深度,最后采用模函数运算嵌入秘密信息。实验结果表明,该方法能嵌入较多信息和保持良好的载密图像质量。     

An adaptive steganographic method based on the measurement of just noticeable distortion profile

This paper presents an adaptive steganographic method based on just noticeable distortion (JND) profile measurement. According to the input requirements, our method can produce a higher quality or higher embedding capacity stego-image. In the embedding secret data bits into a target pixel process, four different impact factors are utilized to compute how much information can be embedded and what the stego-pixel value will be. These are difference values that represent the correlation between neighboring pixels, the JND value of the target pixel, a predefined embedding capacity control factor, and the contents of various lengths secret data bits. The proposed method embeds more secret data bits within complex areas and less data bits in smooth areas. The difference between the target pixel and the stego-pixel values is controlled, as far as possible, to less than or equal to the JND value of the target pixel. Thus, the stego-image maintains good imperceptible property. In the extraction phase, the embedded secret data can be extracted from the stego-image without referencing the original image and the JND profile. The experimental results show that our method improves stego-image quality and conspicuously increases the embedding capacity at the same time.     

A high capacity reversible data hiding scheme with edge prediction and difference expansion

To enhance the embedding capacity of a reversible data hiding system, in this paper, a novel multiple-base lossless scheme based on JPEG-LS pixel value prediction and reversible difference expansion will be presented. The proposed scheme employs a pixel value prediction mechanism to decrease the distortion caused by the hiding of the secret data. In general, the prediction error value tends to be much smaller in smooth areas than in edge areas, and more secret data embedded in smooth areas still meets better stego-image quality. The multiple-base notational system, on the other hand, is applied to increase the payload of the image. With the system, the payload of each pixel, determined by the complexity of its neighboring pixels, can be very different. In addition, the cover image processed by the proposed scheme can be fully recovered without any distortion. Experimental results, as shown in this paper, have demonstrated that the proposed method is capable of hiding more secret data while keeping the stego-image quality degradation imperceptible.     

Separable reversible data hiding in encrypted images based on scalable blocks

This paper proposes a new separable reversible data hiding method for encrypted images. Proposed scheme employs the pixel redundancy of natural images to construct embedding space. First, cover image is divided into multiple blocks with different scales. According to the pixel average value of each block, the lowest two bits of every pixel are vacated as reserved rooms. Subsequently, the whole image is encrypted by using stream cipher and the secret messages are finally embedded into the reserved rooms by the embedding key. Proposed scheme is separable in the sense that the recipient can achieve different function by the following ways: (a) If the recipient has only decryption key, an approximation plaintext image containing the embedded information can be obtained. (b) If the recipient has only embedded key, secret messages can be extracted correctly. (c) If the recipient has both decryption key and embedded key, he can not only extract the secret messages, but recover the original cover image perfectly. Extensive experiments are performed to show that our proposed schemes outperform existing reversible data hiding schemes in terms of visual quality, embedding capacity and security performance, even if a large-scale image database is used.