Reversibility of image with balanced fidelity and capacity upon pixels differencing expansion

Reversible data hiding has attracted considerable attention in recent years. Being reversible, the decoder can extract hidden data and recover the original image completely, and the difference expansion (DE) scheme can lead to a lossless pixel after secret data exacting. Furthermore, despite achieving pixel reversibility based on the concept of expanded differencing, the difference expansion scheme can cause enormous image distortion because of the size of the difference. The proposed scheme in this paper describes a novel prediction for achieving predictive error based reversible data hiding by considering the relation between a pixel and its neighboring pixel and using the predictor to identify the projected difference in pixel value. Experimental results show that the proposed scheme is capable of providing great embedding capacity without causing noticeable distortion by selecting the minimal predictor based on pixel expansion. In multilevel cases, this proposed method performs better than other existing methods. Moreover, the proposed scheme is able to pass the Chi-square test, a test used to find whether an image utilizes LSB for data hiding.     

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.     

Multilevel reversible data hiding based on histogram modification of difference images

Reversible data hiding has drawn considerable attention in recent years. Reversibility allows original media to be completely recovered from marked media without distortion after embedded message has been extracted. In this paper we propose a multilevel reversible data hiding scheme based on the difference image histogram modification that uses the peak point to hide messages. Through a joint imperceptibility and hiding capacity evaluation, we show that our proposed scheme uses a multilevel hiding strategy to achieve large hiding capacity and keep distortion low. Performance comparisons with other existing reversible hiding schemes are provided to demonstrate the validity of our proposed scheme.     

Image reversibility in data embedding on the basis of blocking-predictions

The popularity of peer-to-peer (P2P) multimedia file sharing applications such as voice, files, images, video, texts have created a flurry of recent research activity into P2P architectures. Reversible data hiding has drawn considerable attention in recent years. Being reversible, the decoder can extract the hidden data and recover the cover image completely. In this paper we used the block prediction to achieve histogram-based reversible data hiding. The histogram is created by exploiting all difference values between pixels and their predictive values. Experimental results show that our scheme is capable of providing great embedding capacity without making noticeable distortion. In the one-level data hiding, our scheme preserves image quality larger than 48 dB and has the best capacity. Moreover, in the multilevel cases, our scheme performs better than other existing schemes. Our scheme can successfully increase the embedding capacity from histogram-based data hiding and preserve image quality well.     

Reversible data hiding for high quality images exploiting interpolation and direction order mechanism

Reversible data hiding can restore the original image from the stego image without any distortion after the embedded secret message is exactly extracted. In this paper, a novel, reversible, data hiding scheme for high quality images is proposed in spatial domain. To increase embedding capacity and enhance image quality, the proposed scheme classifies all pixels as wall pixels and non-wall pixels. For wall pixel, the interpolation error is used to embed secret data over the interpolation prediction method. In contrast, the difference value between the non-wall pixel and its parent pixel, which is defined by the direction order, is computed to hide secret data based on the histogram shifting. The experimental results demonstrate that our scheme provides a larger payload and a better image quality than some existing schemes. Moreover, the performance of the proposed scheme is more stable for different images.     

Issues and solution on distortion drift in reversible video data hiding

Different from reversible image data hiding, most reversible video data hiding schemes have the particular problem that the distortion due to hidden data will spread and accumulate. In this paper, the problem of distortion drift caused by reversible data hiding in compressed video is analyzed, and a lossless drift compensation scheme is proposed to restrain the distortion for the first time. In order to ensure the reversibility, drift compensation signals are merged in the quantized DCT (Discrete Cosine Transform) coefficients of P-frames and the corresponding recovery mechanism is presented as well. Experimental results demonstrate that the proposed lossless drift compensation scheme significantly improves the video quality, and the original compressed video can be recovered exactly after the hidden data and compensation signals are removed. In addition, the proposed scheme does not depend on specific reversible data hiding method.     

Quadruple Difference Expansion-Based Reversible Data Hiding Method for Digital Images

ABSTRACT

Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but also the ability of cover media to be reconstructed without any distortion. A latest lossless data hiding technique is proposed by Hong Lin Jin's that is based on hiding only one data bit in the spatial domain in gray-level image. However, this method uses double difference expansion to embed bits which results in a small embedding capacity. For this purpose, we propose an improved algorithm with the potential of increasing the payload capacity and maintaining good image quality. The proposed improved algorithm is characterized by two aspects. First, the proposed improved reversible data hiding scheme is enhanced to exhibit data hiding in color palette images. Second, the embedding level is improved by using quadruple difference expansion to guarantee the embedding of 2-bit data into color images. Experiments of the proposed improved method have been conducted over several well-known test images. The results show that the proposed improved method significantly improves the embedding capacity over Hong Lin Jin's scheme by the range of 15–35% for grayscale images and 20–46% for color images while still maintaining the quality of the stego-images.     

Reversible data hiding using side-match predictions on steganographic images

Information hiding is an important method to achieve multi-media security. Recently, many researchers have paid attention to the reversible data hiding scheme, which can completely recover original multi-media files after the embedded data are extracted. In this paper, a side-match approach is proposed to achieve more capacity in histogram-based reversible data hiding for grayscale images. The histogram is created by exploiting the difference in all the values between pixels and their predictedive values. Experimental results show that our method is capable of providing a great embedding capacity without causing noticeable distortion. In one-level hiding, where it has the best capacity, our method conserves image qualities larger than 48 dB. Furthermore, in multilevel hiding, a rotation strategy is proposed to further improve image qualities. Experimental results show that our method performs better than other existing methods in multilevel hiding cases.     

增强图像平滑度的可逆信息隐藏方案

随着互联网技术的发展和社交网络的普及,可逆信息隐藏技术因其具有无损恢复载体信息的特性而被广泛应用于医疗、军事等领域的隐蔽信息传输。传统的可逆信息隐藏方案大多聚焦于嵌入容量提升和载密图像失真率降低,并未过多关注人们对图像视觉细节的要求,难以抵抗隐藏信息检测方法。针对上述挑战,从增强图像视觉平滑度方面入手,提出了一种增强图像平滑度的可逆信息隐藏方案,在嵌入隐蔽信息的同时提升载密图像最终的视觉质量。具体来说,所提方案将目标图像分为参考区域与非参考区域,利用非参考区域的图像像素预测值与原始像素值的差值作为信息嵌入的判断依据,通过差值平移来嵌入信息;进而构造图像平滑机制,采用高斯滤波作为秘密信息嵌入时像素值修改的模板,对预测值进行滤波计算,将滤波差值无损地加入载体图像中,以达到图像平滑的效果;同时将参考区域的像素值作为边信息,用于实现信息提取方对原始载体图像和秘密信息的无损恢复和提取;并以高斯函数中的滤波系数作为预置秘密信息对嵌入信息进行加密处理以保证嵌入信息的机密性。大量经典图像数据集的测试与分析结果表明,所提方案处理过的载密图像视觉平滑度得到了显著增强,具有较低的失真率、较高的嵌入率和较高的嵌入提取效率。在典型环境下,其生成的载密图像与高斯滤波后的图像相似度可达0.996 3,且可获得37.346的峰值信噪比和0.328 9的嵌入容量。     

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.     

Multiple predictors hiding scheme using asymmetric histograms

In recent years, many data hiding techniques have been proposed, and they can be generally classified into two types according to the reversibility of the image; these two types are reversible and irreversible data hiding. This study focused on reversible data hiding, which makes recovering the cover image possible after the secret data has been extracted. In 2013, Chen et al. proposed an asymmetric-histogram reversible data hiding method. In their scheme, two prediction error histograms (maximum and minimum error histograms) were used to embed the secret message. Two histograms were shifted in opposite directions. Hence, some stego-pixels were shifted to their original values. The complementary embedding strategy is effective. However, the predictor in the method is rough. Only neighboring pixels were used to generate the prediction errors, thereby resulting in poor prediction efficiency. To enhance the prediction efficiency, this paper combines several well-known predictors such as gradient adjusted gap (GAP), median edge detect, and interpolation by neighboring pixel (INP) to generate prediction errors. Different predictors along with the asymmetric-histogram method can achieve better results. The predictor GAP used more neighboring pixels to obtain the prediction value; therefore, it is suitable for complex images. However, the predictor INP only considers that closer pixels can achieve great results for smooth images. Hence, the proposed scheme combines GAP and asymmetric histogram for complex images. However, the predictor INP along with asymmetric histogram is used for smooth images. Experimental results showed that the PSNR value of the proposed method is greater than that of the asymmetric-histogram shifting method and other recent approaches.     

An encoding method for both image compression and data lossless information hiding

Reversible image data hiding technology means the cover image can be totally recovered after the embedded secret data is extracted. In this paper, we propose a reversible image data hiding scheme based on vector quantization (VQ) compressed images. The secret bits are embedded into the VQ index table by modifying the index value according to the difference of neighboring indices. The data hiding capacity and the size of the final codestream (embedded result) are a trade-off, and it can be decided by users. In other words, the proposed scheme has flexible hiding capacity ability. To estimate the performance, the proposed scheme was compared with the scheme proposed by Wang and Lu (2009). The results of the comparison showed that our proposed scheme is superior to the scheme proposed by Wang and Lu in both data hiding capacity and bit rate.     

An improved lossless data hiding scheme based on image VQ-index residual value coding

Copyright protection and information security have become serious problems due to the ever growing amount of digital data over the Internet. Reversible data hiding is a special type of data hiding technique that guarantees not only the secret data but also the cover media can be reconstructed without any distortion. Traditional schemes are based on spatial, discrete cosine transformation (DCT) and discrete wavelet transformation (DWT) domains. Recently, some vector quantization (VQ) based reversible data hiding schemes have been proposed. This paper proposes an improved reversible data hiding scheme based on VQ-index residual value coding. Experimental results show that our scheme outperforms two recently proposed schemes, namely side-match vector quantization (SMVQ)-based data hiding and modified fast correlation vector quantization (MFCVQ)-based data hiding.     

High capacity reversible hiding scheme based on interpolation,difference expansion,and histogram shifting

Difference expansion and histogram shifting methods are two popular hiding strategies that have been widely used in many researches. For example, Hong and Chen developed a reversible hiding method based on interpolation and histogram shifting. The image quality of their scheme is exceptional; however, their scheme needs to keep and transmit two peak points for secret data extraction and pixel recovering. Moreover, the reference pixels in their scheme cannot be used to embed secret data that will decrease the hiding capacity. Therefore, this paper shall propose a reversible hiding method to enhance their scheme. The proposed method applies the difference expansion, histogram shifting and interpolation strategies to conceal secret data in the reference pixels for increasing the hiding payload. Experimental results indicate that the proposed method performs better in terms of hiding capacity than recently developed methods.     

Embedding capacity raising in reversible data hiding based on prediction of difference expansion

Most of the proposed methods of reversible data hiding based on difference expansion require location maps to recover cover images. Although the location map can be compressed by a lossless compression algorithm, this lowers embedding capacity and increases computational cost during the procedures of embedding and extracting. The study presents an adaptive reversible data scheme based on the prediction of difference expansion. Since each cover pixel generally resembles its surrounding pixels, most of the difference values between the cover pixels and their corresponding predictive pixels are small; therefore, the proposed scheme gains from embedding capacity by taking full advantage of the large quantities of smaller difference values where secret data can be embedded. The proposed scheme offers several advantages, namely, (1) the location map is no more required, (2) the embedding capacity can be adjusted depending on the practical applications, and (3) the high embedding capacity with minimal visual distortion can be achieved. Moreover, the experimental results demonstrate that the proposed scheme yields high embedding capacity by comparing the related schemes that are proposed recently.     

Reversible data hiding exploiting spatial correlation between sub-sampled images

Reversible data hiding enables host media to be restored from marked media without any loss of host information. Since this reversibility helps to make right decision during image analysis, it is highly desired in quality-sensitive imagery where even the minimal distortion introduced by embedding data is unacceptable. In this paper, we propose a reversible data hiding method that modifies the difference histogram between sub-sampled images. It exploits the high spatial correlation inherent in neighboring pixels to achieve high capacity and imperceptible embedding. On various test images including 16-bit images, we demonstrate the validity of our proposed method by comparing to other existing reversible data hiding algorithms. Experimental results support that our method provides high embedding capacity while keeping the distortions at a low level.     

A reversible data hiding scheme using complementary embedding strategy

Obtaining good visual quality and high hiding capacity with reversible data hiding systems is a technically challenging problem. In this paper, we propose a simple reversible data hiding scheme that uses a complementary hiding strategy. The proposed method embeds one secret bit horizontally and vertically into one cover pixel of a grayscale cover image by decreasing odd-valued pixels and increasing even-valued pixels by one. Experimental results show that the hiding capacity measured by bit per pixel (bpp) of the proposed scheme is at least 1.21 bpp with a PSNR (peak signal-to-noise ratio) value greater than 52 dB for all standard test images. Especially in the case of four-layer embedding, the PSNR value of the proposed method is still greater than 51 dB at a hiding capacity of about 5 bpp for all standard test images. In addition, the proposed method is quite simple because it primarily uses additions and subtractions. These results indicate that the proposed scheme is superior to many existing reversible data hiding schemes introduced in the literature.     

Reversible data hiding based compressible privacy preserving system for color image

In digital era, privacy preservation and data size reduction are important issues and many applications handle them simultaneously. In this paper, authors introduce a novel application of reversible data hiding to protect privacy sensitive region in a color image while reducing its file size. The proposed work introduces entropy as a new performance criterion along with distortion, capacity for reversible data hiding. Evaluation metric of the proposed method is a file size of watermarked and losslessly compressed image. The proposed method preserves privacy and controls rise in image entropy by reversible data hiding.

     

Adaptive real-time reversible data hiding for JPEG images

Data hiding used to embed data, such as copyright information, into various forms of media such as image, audio, or text with a minimum amount of perceivable degradation to the “host” signal. Therefore, in many cases, the cover media contain distortions even after the hidden data have been extracted. Thus, to extend the application of data hiding to some sensitive domains such as military, medical, and fine arts, which require the embedded cover images to be properly covered, reversible data hiding has become another new branch of this field. Our proposed scheme is inspired by Chang et al.’s idea. In this paper, we propose adaptive real-time reversible data hiding for JPEG images using successive zero coefficients in zigzag sequences of discrete cosine transformation blocks. The contribution of our proposed scheme successfully enhances the hiding capacity while the image quality of stego image and reversibility are maintained. The result of experiments conducted indicates that the proposed scheme enhances data hiding capacity, image quality, and improves performance.     

一种基于块中值整数变换的可逆数据隐藏

在基于可逆整数变换的数据隐藏算法中,传统的方法利用左上角像素值与块中其他像素值得到差值。提出的方法利用块中值与块中其他像素值得到差值,差值变小,从而使得藏密图像失真降低。同时该方法采用在平滑区域优先嵌入数据的策略,使藏密图像的信噪比显著提高。将该方法与类似的方法进行实验比较,结果表明提出方法在嵌入相同数据量时确实具有更好的隐蔽性,并且隐密数据和原宿主图像均能从隐藏图像无损恢复,验证了提出算法的有效性。