Shaowei Weng

Reversible Watermarking Based on Invariability and Adjustment on Pixel Pairs

A novel reversible data hiding scheme based on invariability of the sum of pixel pairs and pairwise difference adjustment (PDA) is presented in this letter. For each pixel pair, if a certain value is added to one pixel while the same value is subtracted from the other, then the sum of these two pixels will remain unchanged. How to properly select this value is the key issue for the balance between reversibility and distortion. In this letter, half the difference of a pixel pair plus 1-bit watermark has been elaborately selected to satisfy this purpose. In addition, PDA is proposed to significantly reduce the capacity consumed by overhead information. A series of experiments is conducted to verify the effectiveness and advantages of the proposed approach.

A Novel Reversible Watermarking Based on an Integer Transform

A novel reversible data hiding scheme based on an integer transform is presented in this paper. The invertible integer transform exploits the correlations among four pixels in a quad. Data embedding is carried out by expanding the differences between one pixel and each of its three neighboring pixels. However, the high hiding capacity can not be achieved only by difference expansion, so the companding technique is introduced into the embedding process so as to further increase hiding capacity. A series of experiments are conducted to verify the feasibility and effectiveness of the proposed approach.

Reversible watermarking based on multiple prediction modes and adaptive watermark embedding

A new reversible watermark scheme based on multiple prediction modes and adaptive watermark embedding is presented. Six prediction modes fully exploiting strong correlation between any pixel and its surrounding pixels, are designed in this paper. Under any prediction mode, each to-be-predicted pixel must be surrounded by several pixels (they constitute a local neighborhood, and any modification to this neighborhood is not allowed in the embedding process). This neighborhood has three main applications. The first one is that when it is exploited to interpolate some to-be-predicted pixel, the noticeable improvement in prediction accuracy is obtained. The second one is that its variance is employed to determine which classification (i.e., smooth or complex set) its surrounded pixel belongs to. For any to-be-predicted pixel, the number of embedded bits is adaptively determined according to this pixel’s belonging. The last one is that we can accurately evaluate the classification of watermarked pixels by analyzing the local complexity of their corresponding neighborhoods on the decoding side. Therefore, the payload can be largely increased as each to-be-predicted pixel in the smooth set can possibly carry more than 1 bit. Meanwhile, the embedding distortion is greatly controlled by embedding more bits into pixels belonging to smooth set and fewer bits into the others in complex set. Experimental results reveal the proposed method is effective.

Lossless data hiding based on prediction-error adjustment

A novel lossless data hiding scheme based on a combination of prediction and the prediction-error adjustment (PEA) is presented in this paper. For one pixel, its four surrounding neighboring pixels are used to predict it and 1-bit watermark information is embedded into the prediction-error. In traditional approaches, for the purpose of controlling embedding distortion, only pixels with small prediction-errors are used for embedding. However, when the threshold is small, it is difficult to efficiently compress the location map which is used to identify embedding locations. Thus, PEA is introduced to make large prediction-error available for embedding while causing low embedding distortions, and accordingly, the location map can be compressed well. As a result, the hiding capacity is largely increased. A series of experiments are conducted to verify the effectiveness and advantages of the proposed approach.

Adaptive reversible data hiding based on a local smoothness estimator

A novel reversible watermarking (RW) scheme based on a local smoothness estimator and multi-step embedding strategy is proposed in this paper. All the pixels are divided into four equal parts. Correspondingly, the watermark embedding process is separated into four independent steps. Thus each step is performed to embed watermark information into its corresponding image part. In each step, for each to-be-embedded pixel, a local smoothness estimator defined as the variance of its total neighbors is presented to estimate its local smoothness. An obvious advantage of introducing this estimator is that it can determine those pixels in smooth regions accurately. In fact, accurate determination means the decrease in embedding distortion. At the low embedding rate (ER), modifications induced by difference expansion (DE) are done only to those pixels located in smooth regions. Hence, the proposed method can obtain high embedding capacity while maintaining good visual quality. With ER gradually increased, adaptive embedding is employed. In adaptive embedding, for one to-be-embedded pixel, 1 or 2 bits are adaptively embedded according to the strength of relationship among all the pixels surrounding it. The experimental results demonstrate that the proposed method is effective.

Reversible data hiding based on the local smoothness estimator and optional embedding strategy in four prediction modes

Four new prediction modes are proposed in this paper, each of which is a three-step process for all to-be-embedded pixels (nearly three-fourths of all the pixels). By designing each mode reasonably, all to-be-embedded pixels can be predicted with high accuracy, and thus, the number of embeddable pixels can be increased largely. In each step, a local smoothness estimator is utilized to determine if one embeddable pixel is located in a smooth or complex region, which is defined as the variance of the total neighbors of this pixel. In fact, the correlation evaluated by using the total neighbors, instead of a part, can reflect the complexity of the region more accurately. In this paper, an optional embedding strategy is introduced so as to select a low-distortion reversible data hiding (RDH) method according to the desired embedding rate (ER). Specifically, when the required ER is low, difference expansion (DE) is used to process those pixels in smooth regions while leaving the rest unaltered. With ER largely increased, adaptive embedding is used to embed 2-bit into these pixels with low local variance by DE while 1-bit into the remaining ones. The experimental results also demonstrate the proposed method is effective.

Reversible watermarking based on two embedding Schemes

Two different embedding schemes are presented in this paper. One aims to increase rate-distortion performance at low embedding rates. It will increase performance at low embedding rates from the following three main aspects: 1) a local variance-controlled mechanism, 2) a better predictor and 3) a new embedding scheme which can decrease the number of the pixels to be modified on the basis of providing a certain embedding capacity. Since the first scheme is only to provide low embedding rate with high visual quality, another scheme is designed to achieve higher embedding rate with good visual quality. In the second scheme, the center pixel of a three-pixel set is the prediction of a pixel, and thus any modification to it is meaningless. Each three-pixel set contains two differences. Based on the fact that the center pixel can not be modified, the remaining two pixels must be modified so that both of difference are shifted by 1. For instance, if both of pixels can carry 1-bit watermark and to-be-embedded bits are both 1, then two pixels must be shifted left or right by 1. Since we can not shift two difference by modifying only the center pixel, the distortion is high. To decrease distortion, the possibility that two bits are both equal to 1 is discarded in this paper. Experimental results also demonstrate the proposed method is effective.

A Novel High-Capacity Reversiblewatermarking Scheme

A novel reversible data hiding scheme is proposed in this article. Each pixel is predicted by its right neighboring pixel in scan order to get its prediction-error. Then, a companding technique is introduced so as to largely increase the number of prediction-errors available for embedding. Accordingly, a location map recording available positions can be compressed into a short bitstream. By largely decreasing the capacity consumed by the compressed location map, the high hiding capacity is achieved. A series of experiments are conducted to verify the feasibility and effectiveness of the proposed approach.

Pairwise IPVO-based reversible data hiding

Recently, Peng et al. proposed a reversible data hiding method based on improved pixel-value-ordering (PVO) and prediction-error expansion. In this paper, a novel method is proposed by extending Peng et al.’s work. In our method, three largest (or smallest) pixels in a block are utilized to generate two differences, and a new pixel modification strategy is proposed so that the PVO remains unchanged after data embedding. Taking three largest pixels for example, we utilize the third largest pixel to predict the second largest one, and meanwhile use the second largest one to predict the maximum. In this way, two differences are obtained. They are modified jointly so as to be embedded with log 23 bits instead of 2 bits in the traditional RDH methods. The advantage of doing so is to exclude situations where PVO is changed. Moreover, two embedding layers are utilized together to further decrease the embedding distortion. Extensive experiments verify that the proposed method outperforms Peng et al. ’s and some other state-of-the-art works.

Reversible watermarking based on PMO of triplets

A reversible watermarking algorithm based on piecewise modification operation(PMO) of triplets is proposed in this paper. PMO is designed to embed a bit into any two pixels while remaining the intensity sum of pixels unchanged. Two bits are embedded into a triplet by repeatedly using PMO on every two neighboring pixels. Another advantage of using PMO is that the capacity consumed by the additional information can be largely decreased. As a result, the embedding capacity is considerably increased. A series of experiments is conducted to verify effectiveness and advantages of the proposed approach.