A Dual Domain Robust Reversible Watermarking Algorithm for Frame Grouping Videos Using Scene Smoothness

The proposed robust reversible watermarking algorithm addresses the compatibility challenges between robustness and reversibility in existing video watermarking techniques by leveraging scene smoothness for frame grouping videos.Grounded in the H.264 video coding standard,the algorithm first employs traditional robust watermark stitching technology to embed watermark information in the low-frequency coefficient domain of the U channel.Subsequently,it utilizes histogram migration techniques in the high-frequency coefficient domain of the U channel to embed auxiliary information,enabling successful watermark extraction and lossless recovery of the original video content.Experimental results demonstrate the algorithm’s strong imperceptibility,with each embedded frame in the experimental videos achieving a mean peak signal-to-noise ratio of 49.3830 dB and a mean structural similarity of 0.9996.Compared with the three comparison algorithms,the performance of the two experimental indexes is improved by 7.59%and 0.4%on average.At the same time,the proposed algorithm has strong robustness to both offline and online attacks:In the face of offline attacks,the average normalized correlation coefficient between the extracted watermark and the original watermark is 0.9989,and the average bit error rate is 0.0089.In the face of online attacks,the normalized correlation coefficient between the extracted watermark and the original watermark is 0.8840,and the mean bit error rate is 0.2269.Compared with the three comparison algorithms,the performance of the two experimental indexes is improved by 1.27%and 18.16%on average,highlighting the algorithm’s robustness.Furthermore,the algorithm exhibits low computational complexity,with the mean encoding and the mean decoding time differentials during experimental video processing being 3.934 and 2.273 s,respectively,underscoring its practical utility.

Reversible Watermarking Method with Low Distortion for the Secure Transmission of Medical Images

In telemedicine,the realization of reversible watermarking through information security is an emerging research field.However,adding watermarks hinders the distribution of pixels in the cover image because it creates distortions(which lead to an increase in the detection probability).In this article,we introduce a reversible watermarking method that can transmit medical images with minimal distortion and high security.The proposed method selects two adjacent gray pixels whose least significant bit(LSB)is different from the relevant message bit and then calculates the distortion degree.We use the LSB pairing method to embed the secret matrix of patient record into the cover image and exchange pixel values.Experimental results show that the designed method is robust to different attacks and has a high PSNR(peak signal-to-noise ratio)value.The MRI image quality and imperceptibility are verified by embedding a secret matrix of up to 262,688 bits to achieve an average PSNR of 51.657 dB.In addition,the proposed algorithm is tested against the latest technology on standard images,and it is found that the average PSNR of our proposed reversible watermarking technology is higher(i.e.,51.71 dB).Numerical results show that the algorithm can be extended to normal images and medical images.

Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

Few previous Reversible Visible Watermarking(RVW)schemes have both good transparency and watermark visibility.An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding(BTC)compressed domain,called TVB-RVW is proposed in this paper.A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation.Then,a visual perception factor computation model is devised by fusing texture and luminance characteristics.An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC domain.Moreover,a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark removal.The visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark embedding.Extensive experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility,and it can achieve a good balance between transparency and watermark visibility.

Robust Reversible Audio Watermarking Scheme for Telemedicine and Privacy Protection

The leakage of medical audio data in telemedicine seriously violates the privacy of patients.In order to avoid the leakage of patient information in telemedicine,a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data.The scheme decomposes the medical audio into two independent embedding domains,embeds the robust watermark and the reversible watermark into the two domains respectively.In order to ensure the audio quality,the Hurst exponent is used to find a suitable position for watermark embedding.Due to the independence of the two embedding domains,the embedding of the second-stage reversible watermark will not affect the first-stage watermark,so the robustness of the first-stage watermark can be well maintained.In the second stage,the correlation between the sampling points in the medical audio is used to modify the hidden bits of the histogram to reduce the modification of the medical audio and reduce the distortion caused by reversible embedding.Simulation experiments show that this scheme has strong robustness against signal processing operations such as MP3 compression of 48 db,additive white Gaussian noise(AWGN)of 20 db,low-pass filtering,resampling,re-quantization and other attacks,and has good imperceptibility.

Reversible Natural Language Watermarking Using Synonym Substitution and Arithmetic Coding

For protecting the copyright of a text and recovering its original content harmlessly,this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution operations.By analyzing relative frequencies of synonymous words,synonyms employed for carrying payload are quantized into an unbalanced and redundant binary sequence.The quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional data.Then,the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible manner.On the receiver side,the watermark and compressed data can be extracted by decoding the values of synonyms in the watermarked text,as a result of which the original context can be perfectly recovered by decompressing the extracted compressed data and substituting the replaced synonyms with their original synonyms.Experimental results demonstrate that the proposed method can extract the watermark successfully and achieve a lossless recovery of the original text.Additionally,it achieves a high embedding capacity.

Reversible Watermarking in JPEG Images Based on Modified RZL Codes and Histogram Shift

Reversible watermarking has extensive applications in fields such as medical data management and forensic enforcement. In this article, we propose a modified reverse zero-run length （RZL） coding method for reversible watermarking, which intro- duces fewer modifications to cover than previous ones under the same embedding rate. By combining the coding method with his- togram shift and quantization table modification strategy, we pro- pose a novel reversible data hiding algorithm for JPEG images. Compared with previous art, when embedding the same payload, our method has an improvement of at least 2 dB in stego image＇s quality, which proves the effectiveness and advantage of our algo- rithm.

Threshold Controlled Scheme of Difference Expansion Techniques for Reversible Watermarking

Since Tian Jun proposed the difference expansion embedding technique,based on which,many reversible watermarking techniques were proposed.However,these methods do not perform well when the payload is high.In this paper,we proposed an expandable difference threshold controlled scheme for these three methods.Experiments show that our scheme improves the performance of these three methods for heavy payload.

Reversible Audio Watermarking Algorithm Using Non-Causal Prediction

Reversible watermarking technique enables to extract embedded information without any loss of the host signal. For the reduction of the embedding distortion, a desirable reversible watermarking approach should exploit efficient prediction way to generate prediction errors with a smaller magnitude for expansion embedding. In this paper, we present a reversible audio watermarking scheme based on a new non-causal prediction method and embedding strategy. The proposed non-causal prediction method provides non-integer prediction errors and the proposed expansion embedding strategy can proceed them for a lower embedding distortion. Experimental results have shown that the proposed reversible technique has a lower embedding distortion for the same embedding payload in comparison with the existing state-of-the-art works.

A Dual-Chaining Watermark Scheme for Data Integrity Protection in Internet of Things

Chaining watermark is an effective way to verify the integrity of streaming data in wireless network environment,especially in resource-constrained sensor networks,such as the perception layer of Internet of Things applications.However,in all existing single chaining watermark schemes,how to ensure the synchronization between the data sender and the receiver is still an unsolved problem.Once the synchronization points are attacked by the adversary,existing data integrity authentication schemes are difficult to work properly,and the false negative rate might be up to 50 percent.And the additional fixed group delimiters not only increase the data size,but are also easily detected by adversaries.In this paper,we propose an effective dual-chaining watermark scheme,called DCW,for data integrity protection in smart campus IoT applications.The proposed DCW scheme has the following three characteristics:(1)In order to authenticate the integrity of the data,fragile watermarks are generated and embedded into the data in a chaining way using dynamic grouping;(2)Instead of additional fixed group delimiters,chained watermark delimiters are proposed to synchronize the both transmission sides in case of the synchronization points are tampered;(3)To achieve lossless integrity authentication,a reversible watermarking technique is applied.The experimental results and security analysis can prove that the proposed DCW scheme is able to effectively authenticate the integrity of the data with free distortion at low cost in our smart meteorological Internet of Things system.

Lossless data hiding based on prediction-error adjustment

A novel Iossless 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 predictionerrors 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.