Lossless data hiding for absolute moment block truncation coding using histogram modification

This paper presents a lossless data hiding method for an absolute moment block truncation coding (AMBTC) images, which is a compressed grayscale image. It is not easy to hide secret data in an AMBTC-compressed image because it is composed of bit planes. Thus, it is very sensitive to change some pixels. Nevertheless, to improve the hiding capacity, we present an efficient extension of the histogram modification technique by counting the coefficients of the bit planes in each 4 × 4 block. In addition, our proposed scheme has low complexity and achieves a high embedding capacity with the good perceptual quality compared to the prior arts. In an experiment, we verified our proposed data hiding scheme through the comparison with previous methods.     

A data embedding scheme for color images based on genetic algorithm and absolute moment block truncation coding

Recently, embedding a large amount of secret data into gray-level and color images with low distortion has become an important research issue in steganography. In this paper, we propose a data embedding scheme by using a well-known genetic algorithm, block truncation code and modification direction techniques to embed secret data into compression codes of color images to expand the variety of cover media. In the scheme, the common bitmap generation procedure of GA-AMBTC has been modified to speed up the hiding procedure. Two embedding strategies are proposed to hide secret data into the common bitmap and the quantization values in each block of the cover image. Experimental results confirm that the proposed scheme can provide high data capacity with acceptable image quality of the stego-images. Moreover, the compression ratio of the scheme is exactly the same as that of GA-AMBTC so that attackers cannot detect any trace of hidden data from the size of the modified compressed result.     

Adaptive lossless steganographic scheme with centralized difference expansion

In this paper, a novel adaptive lossless data hiding scheme is presented that is capable of offering greater embedding capacity than the existing schemes. Unlike the fixed hiding capacity each block provides in most of the currently available lossless data hiding approaches, the proposed method utilizes a block-based lossless data embedding algorithm where the quantity of the hidden information each block bears is variable. To both reduce the image distortion and increase the hiding capacity, the payload of each block depends on its cover image complexity. Due to the fact that schemes with difference expansion tend to damage the image quality seriously in the edge areas, in the proposed scheme, smoother areas are chosen to conceal more secret bits. This way, a better balance can be reached between the embedding ratio and the stego-image quality. In addition, when recovered the cover image can came back to its old self to the last bit without any distortion at all. Experimental results, as this paper will show, have demonstrated that the proposed method is capable of hiding more secret data while maintaining imperceptible stego-image quality degradation.     

选择排序的DCT系数对JPEG图像的可逆数据隐藏

JPEG图像压缩算法可以为使用者提供良好的压缩性能,改善图像文件重建质量,在图像和视频处理领域有着广泛的应用价值。 提出了一种可行且有效的对JPEG图像进行可逆信息隐藏的算法。在该算法中,JPEG图像中所有的8×8块中量化的DCT系数重新排列成新的矩阵,纵列为每个块的系数值,横列为同频率下的系数值。对相同频率下的系数进行模拟嵌入比特位,优先选择失真小的频率下的系数嵌入信息,直到嵌入完秘密比特流信息,同时在嵌入秘密信息时根据解码矩阵减少了无效的比特流扩展。实验结果表明,该算法在嵌入同等数量的比特流的情形下能够得到更好的JPEG图像视觉质量和更少的图像比特流扩展。     

A multiple-level visual secret-sharing scheme without image size expansion

In traditional VSS schemes, the size of the share image is substantially expanded since each pixel of the secret image is mapped onto a block consisting of several pixels. In addition, the quality of the reconstructed secret image is normally degraded in contrast, especially for halftone images. This study proposes a VSS scheme that maps a block in a secret image onto one corresponding equal-sized block in each share image without image size expansion. Two types of techniques, including histogram width-equalization and histogram depth-equalization, are proposed to generate the corresponding share blocks containing multiple levels rather than two levels based on the density of black pixels on the blocks for a secret block. In the former technique, the gray-scale image histogram is obtained by uniformly splitting the range of the pixel gray levels in the secret image, while in the latter the buckets are created so that the area of each bucket is roughly constant by containing approximately the same number of pixels. The proposed schemes significantly improve the quality of the reconstructed secret image compared to several previous investigations.     

基于相关性的图像隐写术

根据图像间的相关性,提出一种新的隐写方法。将秘密图像和载体图像进行小波分解,并将秘密图像的小波域分块,对每一块采用多尺度块匹配机制在载体图像的小波域中寻找与其相似的块。根据相似块计算秘密图像小波域的替换图。用零树小波编码方法对替换图编码。将编码信息以及相似块的映射规则等嵌入载体图像的最低有效位。实验结果表明该方法优于相关文献方法。当以典型的F-16飞机图为秘密图像时,用该方法所提取的秘密图像质量至少提高3dB。     

Development of a data hiding scheme based on combination theory for lowering the visual noise in binary images

In order to raise the embedding capacity and simultaneously reduce the artifact effect caused by embedding secret messages into binary images, a novel data hiding method based on the combination theory is proposed. In the proposed scheme, a secret position matrix is designed to improve the hiding capacity which is capable of preventing the least distortion based on the combination theory. Our new scheme enables users to conceal more than one bit of secret data by changing at most one pixel in one subimage. We have derived a formula for computing the payload and the possible modification pixels of a block. Compared with the existing schemes in terms of the hiding capacity and the visual artifacts, as our experimental results show, the proposed scheme is capable of providing a better image quality protector even with a more efficient secret data hider.     

Reversible data hiding based on block median preservation

This paper proposes a reversible data hiding scheme for gray level images. It exploits the high correlation among image block pixels to produce a difference histogram. Secret data is embedded based on a multi-level histogram shifting mechanism with reference to the integer median of each block. The image blocks are divided into four categories due to four corresponding embedding strategies, aiming at preserving the medians during data embedding. In decoder, the median pixels are retrieved first followed by the hidden data extraction, and the host image can be accurately recovered via an inverse histogram shifting mechanism after removing the secret data from the marked image. Experimental results validate the effectiveness of our scheme and demonstrate that it outperforms several previous methods in terms of capacity and marked image’s quality.     

High capacity reversible data hiding scheme based upon discrete cosine transformation

In this paper, we propose a reversible data hiding scheme based on the varieties of coefficients of discrete cosine transformation of an image. Cover images are decomposed into several different frequencies, and the high-frequency parts are embedded with secret data. We use integer mapping to implement our 2-dimensional discrete cosine transformation. Thus, the image recovered from the modified coefficients can be transformed back to the correct data-hidden coefficients. Since the distribution of 2-dimensional DCT coefficients looks close to Gaussian distribution centralized at zero, it is a natural candidate for embedding secret data using the histogram shifting approach. Thus, our approach shifts the positive coefficients around zero to the right and the negative coefficients around zero to the left in order to leave a space to hide the secret data. The experimental comparisons show that, compared to Chang et al. and Lin et al.'s method, the embedding capacity and quality of the stego-image of the proposed method is a great improvement.     

A high quality and small shadow size visual secret sharing scheme based on hybrid strategy for grayscale images

Many secret sharing schemes for digital images have been developed in recent decades. Traditional schemes typically must deal with the problem of computational complexity, and other visual secret sharing schemes come with a higher transmission cost and storage cost; that is, each shadow size is m times as big as the original secret image. The new (2,n) secret sharing scheme for grayscale images proposed in this paper is based a combination of acceptable image quality using block truncation coding (BTC), high compression ratio discrete wavelet transform (DWT) and good subjective performance of the vector quantization (VQ) technique. Experimental results confirm that our proposed scheme not only generates a high quality reconstructed original image but also generates small, random-like grayscale shadows.