Efficient adaptive prediction based reversible image watermarking

A coding layer robust reversible watermarking algorithm for digital image in multi-antenna system

Reversible watermarking technique can be used to protect the copyright of digital video and restore it without any distortion while extracting the watermarking information. However, for H.264/AVC streams, reversible watermarking scheme has the bottleneck for practical applications due to the intra error propagation phenomenon induced by watermark embedding. In this paper a novel decoder-based reversible watermarking algorithm with an error-drift elimination module for H.264/AVC is proposed for eliminating the error propagation, in which the watermark is embedded into some paired-coefficients of 4×4 quantized DCT block. Our experimental results have demonstrated that a good quality of watermarked video with a small increase in bit-rate while keeping high embedding capacity can be achieved in the proposed scheme.

Reversible watermarking is one of the main methods to authenticate and secure digital media security and revert to its original state without any losses. There are multiple reversible watermarking schemes proposed over the years. Often the proposed reversible watermarking scheme was focused on general grey-scale images. Their performance on medical images is not often evaluated. This study compares the performance of various general reversible watermarking schemes using multi-frame medical images and general grey-scale images in terms of 3 main factors, (1) computational complexity, (2) imperceptibility, and (3) embedding capacity. The result has shown that the Least Significant bits have the highest imperceptibility and embedding capacity. However, it is the least secure where outside can modify the watermarked images as long as they have the essential information.

Reversible image watermarking schemes are used to protect ownership and copyrights of digital images. This paper proposes a novel reversible image watermarking scheme based on adaptive image interpolation, segmentation and additive prediction error expansion (PEE). Proposed interpolation comprises of weighted average of neighboring pixels by allocating higher and lower weights to less and more distant neighboring pixel values respectively. The proposed adaptive image interpolation focuses on detection of edges thus minimizing artifacts imposed by interpolation. The idea of embedding varying amount of watermark bits in different image segments has been explored. Simple linear iterative clustering (SLIC) based image segmentation is performed to separate very sharp, sharp, smooth and very smooth regions in image. Higher number of watermark bits are embedded in sharp regions by using additive prediction error expansion embedding technique. Simulations of proposed and existing techniques were performed on different images and compared using embedding capacity (EC), peak signal to noise ratio (PSNR), computational efficiency, image quality, mean square error (MSE), normalized cross correlation (NCC) and structural similarity index (SSIM). The experimental results show that proposed scheme achieves better results in terms of EC, PSNR, computational efficiency, image quality, MSE, NCC and SSIM as compared to existing techniques.

Overflow problem is essential to reversible watermarking algorithms, as it would lead to great distortion or irreversibility if not properly handled. In general, the existing algorithms handle overflow problem with methods that take a lot changes to pixels, which consequently brings a possibly poor quality or a high complexity. In order to solve the overflow problem specifically with a higher quality and a lower complexity, and improve the security of watermark, we put forward a new reversible watermarking scheme. We take the strategy of twice embedding-first, the proposed scheme uses wavelet histogram shifting to embed the watermark information; second, a proposed low-distortion overflow processing algorithm (LDOPA) is implemented to process the overflow problem occurred during the first step, which iteratively scans the pixels, modifies the overflow pixels one by one, and embeds the modification record with its authentication information on the image. In addition, we apply logistic mapping, torus mapping, and CRC to improve the security of the watermark, allowing users to extract watermark only when they hold the correct password. The experimental results prove that the scheme realizes the complete reversibility of watermark and carrier image. Especially, the proposed LDOPA can be easily combined with the existing watermarking methods to further improve their performance.

Reversible watermarking has drawn extensive attentions in recent years due to its broad applications of digital forensics and data security. This paper proposes a novel reversible watermarking approach, which has the perfect reversibility of the embedded data and the original image. In order to increase the embedding capacity, the proposed approach utilizes the enhanced local prediction to reduce the prediction error of every pixel value. Different from traditional reversible watermarking algorithms considering all the image pixels equivalently before prediction, an enhanced image is first computed by multiplying the original image with its saliency map. By linearly formulating each pixel value in an original image as a weighted sum of the enhanced pixel values in its local neighborhood, the correlation coefficients as learned weights are then solved as a least squares solution. Based on two state-of-the-art datasets, the experimental results show that the proposed approach achieves large embedding capacity with relatively low visual distortion.

Now high-capacity reversible watermarking has been a popular research topic in image watermarking. Existing algorithms only focus on the control of additional information, but ignore the process of original host image and watermark, so the embedding capacity is not fully utilized. In this paper, a high capacity reversible watermarking algorithm based on image segmentation and difference expansion is proposed, firstly original host image is segmented by image segmentation, secondly watermark is preprocessed using lossless compression in order to increase the number of expansible difference values and improve the compressed ability of the location map. Experiments show the proposed algorithm is better than traditional difference expansion based algorithms in respects of embedding capacity, compressed ability of location map and distortion of watermarked image.

Reversible watermarking inserts watermarks into digital media in such a way that visual transparency is preserved, which enables the restoration of the original media from the watermarked one without any loss of media quality. It has various applications where high capacity and high visual quality are major requirements for reversible watermarking. This work presents a new reversible watermarking algorithm that embeds message bits by modifying the differential histogram of adjacent pixels. To satisfy both high embedding capacity and visual quality, the proposed technique exploits the fact that the adjacent pixels are highly correlated. Also, we prevent overflow and underflow problems by designing a predicted error compensation scheme. Through experiments using multiple kinds of test images, we prove that the presented algorithm provides 100% reversibility, higher capacity, and higher visual quality than any previous method, while maintaining low induced distortion.

In the literature, robust reversible watermarking schemes (RWSs) allow the extraction of watermarks after the images have suffered attacks; however, the modified images are compromised. On the other hand, self-recovery schemes will restore the compromised regions of the images, but no secret messages are inserted in these schemes. A framework for robust reversible watermarking with signal restoration capabilities was previously proposed in the literature. This study selects four fragile reversible watermarking techniques and two self-recovery schemes to design different framework configurations. These configurations are evaluated to test the framework’s performance and determine the structure that yields better results in terms of perceptual transparency using a well-known image database as the signal input. It was found that fragile reversible watermarking schemes hold low perceptual distortion, while self-recovery schemes produce high perceptual distortion levels. The inherent characteristics of each algorithm determine, a priori, the behavior of the framework, which is approximated by a proposed equation.

A novel image scaling based reversible watermarking scheme for secure medical image transmission

Watermarking is a very important technique for protecting the authorization of digital content, such as still images, video streams, audio streams, and 3-D models. Most fragile watermarking schemes for 3-D models are not reversible. Published reversible or irreversible fragile watermarking schemes for 3-D models have many drawbacks, such as the causality problem, not being blind, or being unable to locate changed regions. To overcome these drawbacks, a reversible fragile watermarking scheme for 3-D models in spatial domain is proposed. Principal component analysis (PCA) is employed to produce the PCA coordinate system and make the system robust against similarity transformation attacks. PCA, together with a novel interval embedding technique, provide the blind reversibility of the proposed scheme. Intervals larger than a threshold and smaller than another threshold are adopted as legitimate to avoid large distortion. Moreover, experimental results show that the proposed scheme can overcome the causality, convergence, and confusion problems; provide both tampering detection and better embedding rate and requiring a small key size.

The classical threshold control of difference expansion reversible watermarking does not ensure a fine tuning of the embedding capacity and the simple partial embedding can introduce artifacts. The newly proposed two-thresholds embedding capacity control splits the image into two parts and marks them with consecutive threshold values. Intermediate capacity values between the ones provided by the thresholds are obtained by varying the ratio between the two parts. The method ensures a fine control of the capacity without introducing artifacts. This paper proposes a lower distortion version of the two-thresholds embedding reversible watermarking scheme. Experimental results are provided.

Image steganography aims to conceal confidential information within digital images in an undetectable manner. However, many existing techniques face a trade‐off between embedding capacity, imperceptibility, and computational efficiency, especially transform‐domain approaches based on floating‐point operations. This paper proposes a novel image steganographic method based on an enhanced Pyramid Integer Wavelet Transform (PIWT) combined with a Modified Optimal Pixel Adjustment Process (MOPAP). The PIWT enables integer‐to‐integer transformation, avoiding floating‐point computations and improving its suitability for efficient implementation. Secret data are embedded into transform coefficients using a linear feedback shift register (LFSR) to introduce randomness in the embedding locations, while the proposed MOPAP is employed to reduce embedding distortion and enhance imperceptibility. Experimental results demonstrate that the proposed method achieves an average Peak Signal to Noise Ratio (PSNR) of 50.1 dB at an embedding capacity of 1 bpp, outperforming conventional Least Significant Bit (LSB) and Lifting Wavelet Transform (LWT) steganographic methods in terms of imperceptibility and embedding capacity. In addition, statistical evaluation indicates improved resistance against classical steganalysis compared to baseline approaches. These results confirm that the proposed method provides an effective balance between embedding capacity, imperceptibility, and computational efficiency, making it a promising solution for secure image‐based data hiding applications.

This paper presents a secure and large capacity reversible watermarking scheme based on modified integer-to-integer discrete wavelet transform (iDWT) and code division multiple access (CDMA) algorithms. In this scheme, the watermark data are spread by orthogonal spreading sequence and then embedded into wavelet domain, which can only be extracted with same spreading codes and be removed after extraction to recover the original image exactly. The iDWT is modified with the method of exchanging the positions of nearby pixels to generate positive wavelet coefficients, through which the length of the spreading sequence is cut down and the embedding capacity enhanced effectively. The influence of the length of different spreading sequences on watermark capacity is discussed and optimal length of orthogonal spreading sequence is obtained to achieve balance between the watermark capacity and image distortion. Performance comparison with some state-of-art reversible watermarking schemes shows that the proposed scheme achieves higher embedding capacity while maintaining image distortion at lower level.

In this paper, a reversible data hiding scheme based on histogram-shifting of prediction errors (HSPE) is proposed. Two-stage structures, the prediction stage and the error modification stage, are employed in our scheme. In the prediction stage, value of each pixel is predicted, and the error of the predicted value is obtained. In the error modification stage, histogram-shifting technique is used to prepare vacant positions for embedding data. The peak signal-to-noise ratio (PSNR) of the stego image produced by HSPE is guaranteed to be above 48 dB, while the embedding capacity is, in average, 4.74 times higher than that of the well known Ni et al.psilas technique with the same PSNR. Besides, the stego image quality produced by HSPE gains 7.99 dB higher than that of Ni et al.psilas method under the same embedding capacity. Experimental results indicate that the proposed data hiding scheme outperforms the prior works not only in terms of larger payload, but also in terms of stego image quality.