New high-performance reversible data hiding method for VQ indices based on improved locally adaptive coding scheme

In this paper, a new high-performance reversible data hiding method for vector quantization (VQ) indices is proposed. The codebook is firstly sorted using the unidirectional static distance-order technique to improve the correlation among the neighboring indices. The two-dimensional structure of image and the high correlation among the neighboring blocks are used to update the self-organized list L in the improved locally adaptive coding scheme (ILAS). Then a new embedding rule according to the complexity of the region at which the current block locates and the position of current block index in the list L is proposed to obtain a better embedding capacity. The experimental results demonstrate that our proposed method has a better performance in terms of compression rate, embedding capacity and embedding rate compared with the related data hiding methods.     

A reversible steganographic scheme for VQ indices based on locally adaptive coding

Achieving a high embedding capacity and low compression rate with a reversible data hiding method in the vector quantization (VQ) compressed domain is a technically challenging problem. This paper proposes a novel reversible steganographic scheme for VQ compressed images based on a locally adaptive data compression method. The proposed method embeds n secret bits into one VQ index of an index table in Hilbert-curve scan order. The experimental results show that the proposed method can achieve the different average embedding rates of 0.99, 1.68, 2.28, and 3.04 bit per index (bpi) and average compression rates of 0.45, 0.46, 0.5, and 0.56 bit per pixel (bpp) for n = 1, 2, 3, and 4, respectively. These results indicate that the proposed scheme is superior to Chang et al.’s scheme 1 [19], Yang and Lin’s scheme [21], and Chang et al.’s scheme 2 [24].     

Reversible information hiding for VQ indices based on locally adaptive coding

Steganography is one of protective methods for secret communications over public networks such as the Internet. This paper proposes a novel reversible information hiding method for vector quantization (VQ) compressed images based on locally adaptive coding method. The proposed steganographic method embeds a secret message into VQ indices in an index table during the process of compressing the index table in the block-by-block manner. The experimental results show that, in average, the proposed method achieves the best visual quality of reconstructed images and the best embedding rate compared to two related works. In terms of compression rate and encoding execution time, in average, Yang et al.’s method is the best, followed by our proposed method, and then Lin and Chang’s method.     

A novel high-performance reversible data hiding scheme using SMVQ and improved locally adaptive coding method

Reversible data hiding is a method that not only embeds secret data but also reconstructs the original cover image without distortion after the confidential data are extracted. In this paper, we propose novel reversible data hiding scheme that can embed high capacity of secret bits and recover image after data extraction. Our proposed scheme depends on the locally adaptive coding scheme (LAC) as Chang&Nguyen’s scheme and SMVQ scheme. Experimental results show that the compression rate of our proposed scheme is 0.33 bpp on average. To embed secret bits we propose the normal-hiding scheme and the over-hiding scheme which have an average embedding rate of 2.01 bpi and 3.01 bpi, more than that of Chang&Nguyen’s scheme (1.36 bpi). The normal-hiding scheme and the over-hiding scheme also has high embedding efficiency of 0.28 and 0.36 on average, which are better than that of Chang&Kieu’s scheme (0.12), Chang&Nguyen’s scheme (0.18) and Chang&Nguyen’s scheme (0.16).     

PVO-based reversible data hiding using adaptive multiple histogram generation and modification

A recently proposed pixel-value-ordering (PVO)–based reversible data hiding (RDH) method takes a sharp histogram derived from two skewed histograms, which realizes good performance through reducing the number of shifted pixels. However, in this recent work, since pixels with different local complexity are processed with the same modification manner based on a single histogram without considering their different local properties, the embedding performance is far from optimal. In this paper, to better exploit the pixel complexity and enhance the reversible embedding performance, a novel PVO-based RDH method using adaptive multiple histogram generation and modification is proposed. First, pixels with different local complexity are divided into several classes utilizing multiple thresholds. Then, a PVO-based predictor is used for prediction and multiple prediction-error histograms corresponding to the different pixel classes are obtained. Next, the generated histograms are modified to embed data according to their statistical characteristics. Here, based on the established capacity–distortion model, the histogram generation and modification are processed in an adaptive way to optimize the embedding performance. Moreover, by extending the proposed method to multiple two-dimensional prediction-error histograms, the embedding performance can be further improved. Experimental results verify that the proposed method outperforms certain state-of-the-art techniques with good marked-image quality.     

A ROI-based reversible data hiding scheme in encrypted medical images

A novel ROI-based reversible data hiding scheme in encrypted medical images is proposed. Firstly, a content owner partitions an original medical image into the region of interest (ROI) and the region of noninterest (RONI), and then encrypts the image using an encryption key. A data-hider concatenates the least significant bits (LSB) of the encrypted ROI and Electronic Patient Record (EPR), and then embeds the concatenated data into the encrypted image by LSB substitution algorithm. With the encrypted medical image containing the embedded data, the receiver can extract the embedded data with the data-hiding key; if the receiver has the encryption key, a medical image similar to the original image can be obtained by directly decrypting the encrypted medical image; if the receiver has both the data-hiding key and the encryption key, the embedded data can be extracted without any error and ROI can be losslessly recovered after extracting the embedded data.     

An efficient high-capacity reversible data hiding scheme for encrypted images

Reversible data hiding in encrypted images is an effective technique to embed information in encrypted domain, without knowing the original content of the image or the encryption key. In this paper, a high-capacity reversible data hiding scheme for encrypted images based on MSB (most significant bit) prediction is proposed. Since the prediction is not always accurate, it is necessary to identify the prediction error and store this information in the location map. The stream cipher is then used to encrypt the original image directly. During the data hiding phase, up to three MSBs of each available pixel in the encrypted image are substituted by the bits of the secret message. At the receiving end, the embedded data can be extracted without any errors and the original image can be perfectly reconstructed by utilizing MSB prediction. Experimental results show that the scheme can achieve higher embedding capacity than most related methods.     

Fractal curves to improve the reversible data embedding for VQ-indexes based on locally adaptive coding

The VQ reversible data embedding technology allows an original VQ coding to be completely restored after the extraction of embedded data. In this paper, we propose a new reversible scheme based on locally adaptive coding for VQ-compressed images. The fractal Hilbert curve is applied to replace the traditional trace of processing the VQ index table. The VQ index table is pre-processed to create a fractal Hilbert curve. Following the curve to process the VQ index table can get better compression rates in the data embedding procedure. Besides, compared to Chang et al.’s scheme, which compressed the inputted VQ index value only when the to-be-embedded bit b is 0, our method performs compressing operations in both cases that the to-be-embedded bits b are 0 and 1. The experimental results show that the proposed method has the best compression rate and the highest embedding capacity compared with other reversible VQ embedding methods.     

High performance reversible data hiding for block truncation coding compressed images

Reversible data hiding has been a hot research topic because it can recover both the host media and hidden data without distortion. Because most digital images are stored and transmitted in compressed forms, such as JPEG, vector quantization, and block truncation coding (BTC), the reversible data hiding schemes in compressed domains have been paid more and more attention. Compared with transform coding, BTC has a significantly low complexity and less memory requirement, it therefore becomes an ideal data hiding domain. Traditional data hiding schemes in the BTC domain modify the BTC encoding stage or BTC-compressed data according to the secret bits, and they have a relatively low efficiency and meanwhile may reduce the image quality. This paper presents a novel reversible data hiding scheme based on the joint neighbor coding technique for BTC-compressed images by further losslessly encoding the BTC-compressed data according to the secret bits. First, BTC is performed on the original image to obtain the BTC-compressed data that can be represented by a high mean table, a low mean table, and a bitplane sequence. Then, the secret data are losslessly embedded in both the high mean and low mean tables. Our hiding scheme is a lossless method based on the relation among the current value and the neighboring ones in mean tables. In addition, it can averagely embed 2 bits in each mean value, which increases the capacity and efficiency. Experimental results show that our scheme outperforms three existing BTC-based data hiding works, in terms of the bit rate, capacity, and efficiency.     

Adaptive reversible data hiding scheme based on integer transform

In this paper, we present a new reversible data hiding algorithm based on integer transform and adaptive embedding. According to the image block type determined by the pre-estimated distortion, the parameter in integer transform is adaptively selected in different blocks. This allows embedding more data bits into smooth blocks while avoiding large distortion generated by noisy ones, and thus enables very high capacity with good image quality. For instance, by the proposed method, we can embed as high as 2.17 bits per pixel into Lena image with a reasonable PSNR of 20.71 dB. Experimental results demonstrate that the proposed method outperforms some state-of-the-art algorithms, especially for high capacity case.     

An efficient reversible data hiding scheme using prediction and optimal side information selection

In this paper, we present an efficient histogram shifting (HS) based reversible data hiding scheme for copyright protection of multimedia. Firstly, an improved HS based multi-layer embedding process for rhombus prediction is employed by introducing a control parameter to explore the correlation of prediction errors. A rate-distortion model for HS embedding is then developed for optimal side information selection, which is especially suitable for low payload reversible data hiding when only a single layer embedding is required. Finally, a modified location map is constructed to facilitate the compression of location map and further increase the embedding capacity. Compared with similar schemes, experimental results demonstrate the superior performance of the proposed scheme in the terms of embedding capacity and stego-image quality.     

一种基于差值扩展大容量可逆信息隐藏新算法

在保证图像质量的前提下,为了提高可逆信息隐藏的容量,提出了一种基于差值扩展的可逆信息隐藏新算法。该方法通过差值直方图平移,将由阈值丁确定的特定区间外的一部分差值平移到该区问内,同时仅对属于该特定区间的差值进行定位图标注,从而不仅增大可嵌入信息的总量,而且得到远小于现有方法的定位图。特别是在阈值,较小的情况下,效果更加明显。实验表明,该算法在保持图像低失真的前提下,与其他算法相比较,取得了较大的信息嵌入量。     

A novel legitimacy preserving data hiding scheme based on LAS compressed code of VQ index tables

Data hiding is a technique for secret and secure data storing and transmission that embeds data into a media such as an image, audio, video and so on, with minimal quality degradation of the media. Some developed data hiding schemes are reversible. Reversibility property allows the media to be recovered completely after extraction of the embedded data. Vector Quantization (VQ)-based image data hiding is one of the most popular study areas in the literature. However, most VQ-based reversible data hiding schemes generate non-legitimate codes as output. In other words output codes generated by such schemes could not be decoded by the conventional VQ or VQ based decoders and may arouse the attention of interceptors. On the other hand, the existing VQ based reversible data hiding schemes that generate legitimate VQ codes as output, suffer from low capacity and poor quality of stego-image. In this paper a novel reversible data hiding scheme for VQ-compressed images based on locally adaptive data compression scheme (LAS) is proposed. Unlike other schemes, the proposed scheme doesn’t change the VQ indices; data is embedded by choosing one of the possible ways to encode each index. As a result, in comparison with the schemes that embed data by index replacement, in the proposed scheme no extra distortion is made by data embedding and the outputted codes are compatible with the conventional LAS decoder. These properties help to hide the existence of secret data and make the scheme suitable for steganography. Moreover, a framework to combine the proposed scheme with some other schemes to improve their capacity and embedding side information is proposed. Since LAS is a general data compression scheme, the proposed scheme could be used to embed data into any data formats. All existing LAS based data hiding schemes produce non-legitimate codes as their outputs and the proposed scheme is the first and only one that produces legitimate codes as output. Experimental results show that the proposed scheme outperforms the existing LAS based schemes and some other VQ based data hiding schemes. On average, the proposed scheme embeds 2.14 bits per index with almost the same bit-rate as the bit-rate of the VQ index table.     

An integer wavelet transform based scheme for reversible data hiding in encrypted images

In this paper, a novel reversible data hiding (RDH) scheme for encrypted digital images using integer wavelet transform, histogram shifting and orthogonal decomposition is presented. This scheme takes advantage of the Laplacian-like distribution of integer wavelet high-frequency coefficients in high frequency sub-bands and the independence of orthogonal coefficients to facilitate data hiding operation in encrypted domain, and to keep the reversibility. Experimental results has demonstrated that this scheme outperforms all of other existing RDH schemes in encrypted domain in terms of higher PSNR at the same amount of payload. Compared with the state-of-the-arts, the proposed scheme can be applied to all natural images with higher embedding rate.     

A secure data hiding scheme for binary images

This letter presents a novel steganography scheme capable of concealing a piece of critical information in a host message which is a binary image (e.g., a facsimile). A binary matrix and a weight matrix are used as secret keys to protect the hidden information. Given a host image of size m/spl times/n, the proposed scheme can conceal as many as /spl lfloor/log/sub 2/ (mn+1)/spl rfloor/ bits of data in the image by changing, at most, two bits in the host image. This scheme can provide a higher security, embed more information, and maintain a higher quality of the host image than available schemes.     

Adaptive data hiding based on VQ compressed images

Data hiding involves embedding secret data into various forms of digital media such as text, image, audio, and video. With the rapid growth of network communication, data-hiding techniques are widely used in protecting copyright, embedding captions and communicating secretly. The authors propose an adaptive algorithm to embed data into VQ compressed images. This method adaptively varies the embedding process according to the amount of hidden data. The proposed method provides more effective hiding and higher quality images than conventional methods. The results of experimental comparisons are also presented.     

High-capacity reversible data hiding in encrypted images based on adaptive block encoding

This paper proposes a new high-capacity reversible data hiding scheme in encrypted images. The content owner first divides the cover image into blocks. Then, the block permutation and the bitwise stream cipher processes are applied to encrypt the image. Upon receiving the encrypted image, the data hider analyzes the image blocks and adaptively decides an optimal block-type labeling strategy. Based on the adaptive block encoding, the image is compressed to vacate the spare room, and the secret data are encrypted and embedded into the spare space. According to the granted authority, the receiver can restore the cover image, extract the secret data, or do both. Experimental results show that the embedding capacity of the proposed scheme outperforms state-of-the-art schemes. In addition, security level and robustness of the proposed scheme are also investigated.     

一种大容量的图像可逆信息隐藏算法

提出了一种大容量的可逆信息隐藏算法的详细实现方案.利用图像直方图中的多个零点或者最小点,通过修改图像像素的灰度值来隐藏信息,并通过统计分析给出常用的信息隐藏的模型和算法.实验表明,该方法不仅可以进行大容量的信息隐藏,而且相对原始图像能够达到满意的峰值信噪比(PSNR),具有良好的性能.     

Hybrid prediction-based pixel-value-ordering method for reversible data hiding

Pixel-value-ordering (PVO) is an effective and promising method of reversible data hiding (RDH) and has received much attention in recent years. To improve performance, a pixel-based PVO (PPVO) method was recently introduced to predict the pixels to be embedded in a pixel-wise manner instead of the block-wise manner used by PVO. However, for PPVO, the surrounding neighbors of the predicted pixels are underutilized; moreover, its embedding does not adapt to the local complexity of the image to be embedded. To overcome the shortcomings of PPVO, this paper proposes a novel PVO method based on hybrid prediction for RDH. First, the surrounding neighbors of the pixel to be predicted are fully utilized by a hybrid prediction method, which combines rhombus prediction and pixel-wise prediction. Second, a modified embedding scheme based on multiple histograms is presented for adaptive embedding. Experimental results show the superior performance of the proposed method by comparing it with state-of-the-art RDH methods.     

Controlling hiding capacity using image characteristics with a 2D-DE data hiding scheme

Reversible data hiding techniques have gained much attention during the last few years because of the losslessness requirements of critical applications in military and medical fields. Among the various reversible data hiding techniques, difference expansion (DE) technique is one of the most popular techniques. The most common thing between DE-based schemes is their dependence on one or more thresholds. The threshold is used in order to control the hiding capacity aiming at keeping high visual quality of the embedded image. However, there is no such automatic way to predict or determine those thresholds as they are usually predefined. In this paper, we study the possibility of utilizing image characteristics as thresholds with a block based two-dimensional difference expansion scheme (2D-DE). The experimental results show that a threshold based on standard deviation may be used to control the hiding capacity and this leads to enhance the visual quality.