Wien Hong

An Improved Reversible Data Hiding in Encrypted Images Using Side Match

This letter proposes an improved version of Zhangs reversible data hiding method in encrypted images. The original work partitions an encrypted image into blocks, and each block carries one bit by flipping three LSBs of a set of pre-defined pixels. The data extraction and image recovery can be achieved by examining the block smoothness. Zhangs work did not fully exploit the pixels in calculating the smoothness of each block and did not consider the pixel correlations in the border of neighboring blocks. These two issues could reduce the correctness of data extraction. This letter adopts a better scheme for measuring the smoothness of blocks, and uses the side-match scheme to further decrease the error rate of extracted-bits. The experimental results reveal that the proposed method offers better performance over Zhangs work. For example, when the block size is set to 8 8, the error rate of the Lena image of the proposed method is 0. 34%, which is significantly lower than 1.21% of Zhangs work.

Reversible data hiding for high quality images using modification of prediction errors

In this paper, a reversible data hiding scheme based on modification of prediction errors (MPE) is proposed. For the existing histogram-shifting based reversible data hiding techniques, though the distortion caused by embedding is low, the embedding capacity is limited by the frequency of the most frequent pixel. To remedy this problem, the proposed method modifies the histogram of prediction errors to prepare vacant positions for data embedding. The PSNR of the stego image produced by MPE is guaranteed to be above 48dB, while the embedding capacity is, on average, almost five times higher than that of the well-known Ni et al. techniques with the same PSNR. Besides, MPE not only has the capability to control the capacity-PSNR, where fewer data bits need less error modification, but also can be applied to images with flat histogram. Experimental results indicate that MPE, which innovatively exploits the modification of prediction errors, outperforms the prior works not only in terms of larger payload, but also in terms of stego image quality.

A Novel Data Embedding Method Using Adaptive Pixel Pair Matching

This paper proposes a new data-hiding method based on pixel pair matching (PPM). The basic idea of PPM is to use the values of pixel pair as a reference coordinate, and search a coordinate in the neighborhood set of this pixel pair according to a given message digit. The pixel pair is then replaced by the searched coordinate to conceal the digit. Exploiting modification direction (EMD) and diamond encoding (DE) are two data-hiding methods proposed recently based on PPM. The maximum capacity of EMD is 1.161 bpp and DE extends the payload of EMD by embedding digits in a larger notational system. The proposed method offers lower distortion than DE by providing more compact neighborhood sets and allowing embedded digits in any notational system. Compared with the optimal pixel adjustment process (OPAP) method, the proposed method always has lower distortion for various payloads. Experimental results reveal that the proposed method not only provides better performance than those of OPAP and DE, but also is secure under the detection of some well-known steganalysis techniques.

Reversible data embedding for high quality images using interpolation and reference pixel distribution mechanism

This paper proposes a reversible data hiding method based on image interpolation and the detection of smooth and complex regions in the cover images. A binary image that represents the locations of reference pixels is constructed according the local image activity. In complex regions, more reference pixels are chosen and, thus, fewer pixels are used for embedding, which reduces the image degradation. On the other hand, in smooth regions, less reference pixels are chosen, which increases the embedding capacity without introducing significant distortion. Pixels are interpolated according to the constructed binary image, and the interpolation errors are then used to embed data through histogram shifting. The pixel values in the cover image are modified one grayscale unit at most to ensure that a high quality stego image can be produced. The experimental results show that the proposed method provides better image quality and embedding capacity compared with prior works.

A high capacity reversible data hiding scheme using orthogonal projection and prediction error modification

The payload of a histogram-shifting based reversible data hiding technique is primarily determined by the peak height of the corresponding image histogram. It is known that the peak height of the prediction error histogram is usually higher than that of image histogram itself. In 2009, Tsai et al. adopted the idea of histogram-shifting technique and embedded message by modifying the prediction errors to achieve a higher payload. They used a block-based approach and leaved some pixel values unmodified to predict other pixel values in a block. However, the unmodified pixels took up some embeddable space, causing a reduction in payload. In this paper, a new reversible data hiding technique based on prediction error modification is proposed. The orthogonal projection technique is employed to estimate the optimal weights of a linear predictor to increase the prediction accuracy and the embedding capacity. The experimental results revealed that the proposed method outperformed the existing histogram-shifting based reversible data hiding technique in terms of payload and image quality.

Adaptive image data hiding in edges using patched reference table and pair-wise embedding technique

Reference table (RT) based embedding method embeds secret digits into pixel pairs under the guidance of a reference table. Most of the existing RT-based methods either require elaborate conversions among different bases, or have limited embedding capacity. In this paper, we use a patched reference table (PRT) as a guide and propose a PRT method to provide a better image quality and extendable embedding capacity. We also exploit the concept of pixel value differencing (PVD) and propose another method PRT-PVD. In the traditional PVD-based methods, the shape of the difference histograms of the stego images is significantly altered and, thus, vulnerable to some steganalyzers. PRT-PVD adopts the PRT method and uses a specially designed embedding sequence to preserve the difference histogram shape. Experimental results reveal that the proposed PRT and PRT-PVD methods not only have better embedding efficiency over the existing methods, but also are robust to detection by modern steganalysis tools.

A local variance-controlled reversible data hiding method using prediction and histogram-shifting

The stego image quality produced by the histogram-shifting based reversible data hiding technique is high; however, it often suffers from lower embedding capacity compared to other types of reversible data hiding techniques. In 2009, Tsai et al. solved this problem by exploiting the similarity of neighboring pixels to construct a histogram of prediction errors; data embedding is done by shifting the error histogram. However, Tsai et al.s method does not fully exploit the correlation of the neighboring pixels. In this paper, a set of basic pixels is employed to improve the prediction accuracy, thereby increasing the payload. To further improve the image quality, a threshold is used to select only low-variance blocks to join the embedding process. According to the experimental results, the proposed method provides a better or comparable stego image quality than Tsai et al.s method and other existing reversible data hiding methods under the same payload.

An efficient prediction-and-shifting embedding technique for high quality reversible data hiding

The embedding capacity of a histogram-based reversible data hiding technique is primarily determined by the peak height of the histogram. Recently, some studies have tried to embed data in the histogram of prediction errors by modifying the error values and have better embedding efficiency. However, these methods offer no selective embedment mechanism to exclude the positions where the modification in the embedding operation contributes no capacity but merely degrade the image quality. In this paper, a novel coding method for reversible data hiding is presented. A two-stage prediction algorithm that fully exploits the pixel correlations is employed to create more embeddable spaces, and a selective embedment mechanism is used to enhance the image quality. According to the experimental results, the proposed method achieved the highest payload while maintaining the lowest distortion for most standard test images, comparing to other existing histogram-shifting-based reversible data hiding techniques.

Data embedding using pixel value differencing and diamond encoding with multiple-base notational system

We propose a new data hiding method that adaptively embeds data into pixel pairs using the diamond encoding (DE) technique. Because the human eyes tolerate more changes in edge and texture areas than in smooth areas, and pixel pairs in these areas often possess larger differences, the method exploits pixel value differences (PVD) to estimate the base of digits to be embedded into pixel pairs. Pixel pairs with larger differences are embedded with digits in larger base than those pixel pairs with smaller differences to maximize the payload and image quality. Two sophisticated pixel pair adjustment processes are provided to maintain the division consistency and to eliminate the overflow/underflow problem. Experimental results reveal that the proposed method offers better embedding performance compared to prior PVD-based works in terms of payload and image quality.

A Minimal Euclidean Distance Searching Technique for Sudoku Steganography

Sudoku, a simple and fun game of logic, has been used for steganography to conceal messages into a digital image recently. Chang et al. adapted the idea of smallest Manhattan distance, embedding secret messages into the neighbors of the located element according to a given Sudoku solution. Hong et al. improved Chang et al.psilas technique by introducing additional set of candidate elements to reduce distortions. However, the aforementioned methods suffer from undesirable distortions because the Manhattan distance architectures are used in their method. The proposed method suggests a new scheme for searching embedding positions based on the nearest Euclidean distance, so that minimal distortions can be reached. The experimental results show that, in average, the visual quality of stego image is 1.70 dB higher than that of Chang et al.psilas method, and 0.72 dB higher than that of Hong et al.psilas method under the same embedding capacity.