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).     

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.     

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.     

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.     

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.     

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.     

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.     

Matrix encoding for data hiding using multilayer video coding and transcoding solutions

This paper proposes a multitier data hiding solution in MPEG video using matrix encoding. In the first tier of the proposed solution, raw video is encoded into two layers using multilayer Signal to Noise Ratio (SNR) encoding. During the multilayer encoding process, the quantization scales and coding parameters are stored. In the second tier, message bits are embedded in the stored quantization scales using matrix encoding. In the third and last tier, the raw video is encoded again into two layers using the modulated quantization scales and coding parameters of the first encoder. The proposed multitier solution is extended by replacing the multilayer encoder with a multilayer transcoder to accommodate situations in which the video exists in pre-coded format only. By the use of multilayer encoder or transcoding, we show that the message payload can be doubled without adversely affecting the coding quality or bitrate of the host video. We also show that message embedding using matrix encoding can be extended to modulate motion vectors. The paper also proposes two solutions for motion vector modulation based on the availability of the raw video. In comparison to existing work, the proposed solutions have higher message payloads, lower degradation in video quality and result in reduced excessive bitrate.     

Reversible data hiding scheme using reference pixel and multi-layer embedding

This paper presents a lossless data hiding scheme. The proposed scheme is based on the pixel difference histogram shifting to spare space for data hiding. Pixel differences are generated between a reference pixel and its neighbors in a pre-assigned block. After the difference histogram shifting, a large number of data can be embedded into the cover image, and multi-layer embedding is used to improve the hiding capacity. Different from previous works based on histogram shifting the proposed scheme can extract the hidden data and recover the exact original cover image with no extra information except the length of hidden data and the stego-image itself. Experimental results show that the average pure payload among eight commonly used grayscale images is up to 1.08 bits per pixel (bpp) while keeping low distortion.     

An adaptive coding scheme for time-varying channels

An adaptive coding scheme for digital communication over time-varying channels is presented. The scheme is based on a finite-state Markov channel model. Emphasis is on the adaptation of the error protection to the actual channel state. The throughput gains that are achieved by the adaptive scheme relative to the conventional nonadaptive coding methods are demonstrated by several examples. Of special interest is the use of punctured convolutional codes with maximum-likelihood Viterbi algorithm to enable adaptive encoding and decoding without modifying the basic structure of the encoder and the decoder     

Efficient reversible data hiding in encrypted images

This paper proposes a novel scheme of reversible data hiding in encrypted images based on lossless compression of encrypted data. In encryption phase, a stream cipher is used to mask the original content. Then, a data hider compresses a part of encrypted data in the cipher-text image using LDPC code, and inserts the compressed data as well as the additional data into the part of encrypted data itself using efficient embedding method. Since the majority of encrypted data are kept unchanged, the quality of directly decrypted image is satisfactory. A receiver with the data-hiding key can successfully extract the additional data and the compressed data. By exploiting the compressed data and the side information provided by the unchanged data, the receiver can further recover the original plaintext image without any error. Experimental result shows that the proposed scheme significantly outperforms the previous approaches.     

基于可伸缩视频编码的自适应误码隐藏方案

文中提出一种基于SVC的动态自适应误码隐藏方案。针对SVC码流增强层部分条带丢失情况,该方案结合散乱型灵活宏块排序功能,在宏块级别采用二阶差分边界匹配准则动态选择基本层和相邻条带信息恢复图像。实验表明,相对SVC标准参考平台JSVM的误码隐藏方案,文中提出方案在不同序列及丢包条件下,重建视频峰值信噪比均得到了一定提升。     

A Markov-based reversible data hiding method based on histogram shifting

Applying information theory, this work considers an image as a stream of symbols emitted by a Markov information source. With the Markov model, a reversible data-hiding scheme based on the histogram modification technique is proposed to provide an efficient tradeoff between hiding capacity and quality of a marked image by changing the order of the Markov model. The larger the order is, the higher the capacity is but the lower the quality is, and vice versa. The experimental results show that the proposed scheme yields not only much larger hiding capacity but also smaller image distortion than other reversible data-hiding schemes reported in the literature. This work also proposes two feasible approaches to reduce the overhead yielded during the data embedding.