scholarly journals A Robust and Improved Visual Quality Data Hiding Method for HEVC

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 53984-53997 ◽  
Author(s):  
Yunxia Liu ◽  
Hongguo Zhao ◽  
Shuyang Liu ◽  
Cong Feng ◽  
Si Liu
Keyword(s):  
Data Hiding ◽  
Visual Quality ◽  
Quality Data

Fuzzy Proximity based Robust Data Hiding Scheme with Interval Threshold

2022 ◽  
Author(s):  
Prabhas Kumar Singh ◽  
Biswapati Jana ◽  
Kakali Datta
Keyword(s):  
Fuzzy Logic ◽  
Data Hiding ◽  
Processing System ◽  
Visual Quality ◽  
Structural Similarity ◽  
Secret Message ◽  
Secret Key ◽  
Post Processing ◽  
Coincidence Problem ◽  
Shared Secret

Abstract In 2020, Ashraf et al. proposed an interval type-2 fuzzy logic based block similarity calculation using color proximity relations of neighboring pixels in a steganographic scheme. Their method works well for detecting similarity, but it has drawbacks in terms of visual quality, imperceptibility, security, and robustness. Using Mamdani fuzzy logic to identify color proximity at the block level, as well as a shared secret key and post-processing system, this paper attempts to develop a robust data hiding scheme with similarity measure to ensure good visual quality, robustness, imperceptibility, and enhance the security. Further, the block color proximity is graded using an interval threshold. Accordingly, data embedding is processed in the sequence generated by the shared secret keys. In order to increase the quality and accuracy of the recovered secret message, the tampering coincidence problem is solved through a post-processing approach. The experimental analysis, steganalysis and comparisons clearly illustrate the effectiveness of the proposed scheme in terms of visual quality, structural similarity, recoverability and robustness.

scholarly journals Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Chunqiang Yu ◽  
Xianquan Zhang ◽  
Zhenjun Tang ◽  
Yan Chen ◽  
Jingyu Huang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Visual Quality ◽  
Input Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Encrypted Image ◽  
High Embedding Capacity ◽  
Additive Homomorphism

Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.

Visibility Control and Quality Assessment of Watermarking and Data Hiding Algorithms

2011 ◽  
pp. 163-192 ◽  
Author(s):  
Patrick Le Callet ◽  
Florent Autrusseau ◽  
Patrizio Campisi
Keyword(s):  
Quality Assessment ◽  
Data Hiding ◽  
Visual Quality ◽  
Visual Quality Assessment ◽  
Objective Quality ◽  
Objective Quality Assessment ◽  
Extended Review

In watermarking and data hiding context, it may be very useful to have methods checking the invisibility of the inserted data or at least, checking the objective quality after the mark embedding or after an attack on the watermarked media. Many works exist in the literature dealing with quality assessment mainly focused on compression application. Nevertheless, visual quality assessment should include special requirements that depend on the application context. This chapter presents an extended review of both subjective and objective quality assessment of images and video in the field of watermarking and data hiding applications.

scholarly journals High Capacity Reversible Data Hiding Based on the Compression of Pixel Differences

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1435
Author(s):  
Kai-Meng Chen
Keyword(s):  
Spatial Correlation ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Visual Quality ◽  
Small Range ◽  
Encryption Scheme ◽  
Secret Data ◽  
Encrypted Image ◽  
Block Level

In this paper, we proposed a novel reversible data hiding method in encrypted image (RDHEI), which is based on the compression of pixel differences. In the proposed method, at the content owner’ side the image is divided into non-overlapping blocks, and a block-level image encryption scheme is used to generate the encrypted image, which partially retains spatial correlation in the blocks. Due to the spatial correlation, in each block the pixels are highly likely to be similar. Therefore, the pixel differences in all blocks are concentrated in a small range and can be compressed. By the compression of pixel differences, the data hider can vacate the room to accommodate secret data in the encrypted image without losing information. At the receiver’s side, the receiver can obtain secret data or retrieve the original image using different keys with no error. The experimental results demonstrate that, compared with existing methods, the proposed method can achieve a higher capacity and visual quality.

HSV model based data hiding in video for watermark applications

2021 ◽  
pp. 1-12
Author(s):  
J. Jerisha Liby ◽  
T Jaya
Keyword(s):  
Data Hiding ◽  
Cross Correlation ◽  
Similarity Index ◽  
Visual Quality ◽  
Structural Similarity ◽  
Noise Filtering ◽  
Structural Similarity Index ◽  
Index Measurement ◽  
Embedding Rate ◽  
Better Than

This manuscript proposes a new data hiding approach that is used in watermark applications in video by transforming the RGB model to HSV model. This method initially estimates the number of frames needed to embed the data (watermark). Then two sets of RGB (Red, Green, Blue) coefficients (R1, G1, B1), (R2, G2, B2) are converted to HSV (Hue, saturation, values) Coefficients (H1, S1, V1) and (H2, S2, V2). The ‘Value’ Coefficients V1 and V2 are used to embed the watermark, since there exists a strong correlation between the adjacent ‘Value’ Coefficients. The same process is repeated on adjacent HSV coefficients till the watermark is fully embedded. After embedding the data HSV coefficients are again converted back to RGB coefficients. During the extraction phase, the data is extracted by transforming the RGB coefficient to HSV coefficients. One bit of information can be extracted from two adjacent HSV coefficients. Experimental outcomes show that the proposed watermarking approach is efficiently against attacks, viz noise, filtering, etc. Also, the proposed method performs better than traditional watermarking methods with the help of embedding rate (bpp), Structural similarity index measurement (SSIM), Visual quality (PSNR), Normalized cross-correlation (NC).

scholarly journals Reversible Data Hiding in Encrypted Color Halftone Images with High Capacity

2019 ◽  
Vol 9 (24) ◽  
pp. 5311 ◽  
Author(s):  
Yu-Xia Sun ◽  
Bin Yan ◽  
Jeng-Shyang Pan ◽  
Hong-Mei Yang ◽  
Na Chen
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Visual Quality ◽  
Cover Image ◽  
Embedding Capacity ◽  
Watermark Embedding ◽  
Continuous Tone ◽  
High Embedding Capacity ◽  
Halftone Images

In recent years, reversible data hiding (RDH) has become a research hotspot in the field of multimedia security that has aroused more and more researchers’ attention. Most of the existing RDH algorithms are aiming at continuous-tone images. For RDH in encrypted halftone images (RDH-EH), the original cover image cannot be recovered losslessly after the watermark is extracted. For some application scenarios such as medical or military images sharing, reversibility is critical. In this paper, a reversible data hiding scheme in encrypted color halftone images (RDH-ECH) is proposed. In the watermark embedding procedure, the cover image is copied into two identical images to increase redundancy. We use wet paper code to embed the watermark into the image blocks. Thus, the receiver only needs to process the image blocks by the check matrices in order to extract the watermarks. To increase embedding capacity, we embed three layers in the embedding procedure and combine the resulting images into one image for convenience of transmission. From the experimental results, it can be concluded that the original image can be restored entirely after the watermarks are extracted. Besides, for marked color halftone images, our algorithm can implement high embedding capacity and moderate visual quality.

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