Lossless Contrast Enhancement of Color Images with Reversible Data Hiding

Recently, lossless contrast enhancement (CE) has been proposed so that a contrast-changed image can be converted to its original version by maintaining information entropy in it. As most of the lossless CE methods are proposed for grayscale images, artifacts are probably introduced after directly applying them to color images. For instance, color distortions may be caused after CE is separately conducted in each channel of the RGB (red, green, and blue) model. To cope with this issue, a new scheme is proposed based on the HSV (hue, saturation, and value) color model. Specifically, both hue and saturation components are kept unchanged while only the value component is modified. More precisely, the ratios between the RGB components are maintained while a reversible data hiding method is applied to the value component to achieve CE effects. The experimental results clearly show CE effects obtained with the proposed scheme, while the original color images can be perfectly recovered. Several metrics including image entropy were adopted to measure the changes made in CE procedure, while the performances were compared with those of one existing scheme. The evaluation results demonstrate that better image quality and increased information entropy can be simultaneously achieved with our proposed scheme.

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A Location Map Reduced Reversible Data Hiding Method Using Prediction Error Modification

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.6-7.428 ◽

2012 ◽

Vol 6-7 ◽

pp. 428-433

Author(s):

Yan Wei Li ◽

Mei Chen Wu ◽

Tung Shou Chen ◽

Wien Hong

Keyword(s):

Image Quality ◽

Data Hiding ◽

Prediction Error ◽

Reversible Data Hiding ◽

Experimental Results ◽

Cover Image ◽

Prediction Errors ◽

Secret Data ◽

Location Map ◽

Comparable Image Quality

We propose a reversible data hiding technique to improve Hong and Chen’s (2010) method. Hong and Chen divide the cover image into pixel group, and use reference pixels to predict other pixel values. Data are then embedded by modifying the prediction errors. However, when solving the overflow and underflow problems, they employ a location map to record the position of saturated pixels, and these pixels will not be used to carry data. In their method, if the image has a plenty of saturated pixels, the payload is decreased significantly because a lot of saturated pixels will not joint the embedment. We improve Hong and Chen’s method such that the saturated pixels can be used to carry data. The positions of these saturated pixels are then recorded in a location map, and the location map is embedded together with the secret data. The experimental results illustrate that the proposed method has better payload, will providing a comparable image quality.

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An Improved Reversible Image Transformation Using K-Means Clustering and Block Patching

Information ◽

10.3390/info10010017 ◽

2019 ◽

Vol 10 (1) ◽

pp. 17 ◽

Cited By ~ 2

Author(s):

Haidong Zhong ◽

Xianyi Chen ◽

Qinglong Tian

Keyword(s):

Image Quality ◽

Data Hiding ◽

Privacy Protection ◽

Reversible Data Hiding ◽

Auxiliary Information ◽

Experimental Results ◽

Image Transformation ◽

Clustering Method ◽

Stego Image ◽

Encrypted Images

Recently, reversible image transformation (RIT) technology has attracted considerable attention because it is able not only to generate stego-images that look similar to target images of the same size, but also to recover the secret image losslessly. Therefore, it is very useful in image privacy protection and reversible data hiding in encrypted images. However, the amount of accessorial information, for recording the transformation parameters, is very large in the traditional RIT method, which results in an abrupt degradation of the stego-image quality. In this paper, an improved RIT method for reducing the auxiliary information is proposed. Firstly, we divide secret and target images into non-overlapping blocks, and classify these blocks into K classes by using the K-means clustering method. Secondly, we match blocks in the last (K-T)-classes using the traditional RIT method for a threshold T, in which the secret and target blocks are paired with the same compound index. Thirdly, the accessorial information (AI) produced by the matching can be represented as a secret segment, and the secret segment can be hided by patching blocks in the first T-classes. Experimental results show that the proposed strategy can reduce the AI and improve the stego-image quality effectively.

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Image Quality Assessment in Reversible Data Hiding with Contrast Enhancement

Digital Forensics and Watermarking - Lecture Notes in Computer Science ◽

10.1007/978-3-319-64185-0_22 ◽

2017 ◽

pp. 290-302 ◽

Cited By ~ 1

Author(s):

Hao-Tian Wu ◽

Shaohua Tang ◽

Yun-Qing Shi

Keyword(s):

Image Quality ◽

Quality Assessment ◽

Contrast Enhancement ◽

Data Hiding ◽

Reversible Data Hiding ◽

Image Quality Assessment

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Reversible Data Hiding Based on Statistical Correlation of Blocked Sub-Sampled Image

International Journal of Computer Vision and Image Processing ◽

10.4018/ijcvip.2012010103 ◽

2012 ◽

Vol 2 (1) ◽

pp. 42-59

Author(s):

Mona Nafari ◽

Mansour Nejati Jahromi ◽

Gholam Hosein Sheisi

Keyword(s):

Image Quality ◽

Data Hiding ◽

Reversible Data Hiding ◽

Statistical Correlation ◽

Experimental Results ◽

Data Embedding ◽

Embedding Capacity ◽

Stego Image

In this paper, a reversible data hiding scheme has been proposed which is based on correlation of subsample images. The proposed method modifies the blocks of sub-sampled image to prepare vacant positions for data embedding. The PSNR of the stego image produced by the proposed method is guaranteed to be above 47.5 dB, while the embedding capacity is at least, almost 6.5 times higher than that of the Kim et al. techniques with the same PSNR. This technique has the capability to control the capacity-PSNR. Experimental results support that the proposed method exploits the correlation of blocked sub-sampled image outperforms the prior works in terms of larger capacity and stego image quality. On various test images, the authors demonstrate the validity of the proposed method by comparing it with other existing reversible data hiding algorithms.

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REVERSIBLE DATA HIDING BASED ON PIXEL-BASED PIXEL VALUE ORDERING PREDICTOR AND EMD

Scientific Journal of Tra Vinh University ◽

10.35382/18594816.1.1.2019.82 ◽

2019 ◽

Vol 1 (1) ◽

pp. 14-19

Author(s):

Nam Hoang Tram ◽

Thanh Van Huynh ◽

C Thanh Vo ◽

Khanh Ngoc Van Duong ◽

Son Thai Nguyen

Keyword(s):

Image Quality ◽

Data Hiding ◽

Reversible Data Hiding ◽

Experimental Results ◽

Quality Changes ◽

Original Image ◽

Pixel Value

In this paper, we improved the reversible data hiding method of Qu’s et al. The original image is divided into overlapped equalsize blocks (2x2). Each of block is used to predict a pixel. Then a histogram is constructed from the different value between the original pixel and the prediction pixel. In order to increase thecapacity, the proposed method combination with EMD table to change the histogram. According to Qu’s method, each pixel satisfies only one bit of information is embedded. In our method, by using the EMD table, each pair of eligible pixels can embed three bits of information. Experimental results show that the proposed method increases 1.5 times the hidden performance while the image quality changes negligibly.

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Separable Patch wise Reversible Data Hiding for Encrypted Color Images

10.35625/am960127c ◽

2019 ◽

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Color Images

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Visible-Imperceptible Image Watermarking based on Reversible Data Hiding with Contrast Enhancement

2020 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE) ◽

10.1109/icmeae51770.2020.00013 ◽

2020 ◽

Author(s):

Jaime Sarabia-Lopez ◽

Diana Nunez-Ramirez ◽

David Mata-Mendoza ◽

Eduardo Fragoso-Navarro ◽

Manuel Cedillo-Hernandez ◽

...

Keyword(s):

Contrast Enhancement ◽

Data Hiding ◽

Reversible Data Hiding ◽

Image Watermarking

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Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Computers ◽

10.3390/computers10070086 ◽

2021 ◽

Vol 10 (7) ◽

pp. 86

Author(s):

Jijun Wang ◽

Soo Fun Tan

Keyword(s):

Image Quality ◽

Data Hiding ◽

Reversible Data Hiding ◽

High Order ◽

Coding Method ◽

Military Applications ◽

Social Cloud ◽

Carrier Image ◽

Security Surveillance ◽

Embedding Rate

Separable Reversible Data Hiding in Encryption Image (RDH-EI) has become widely used in clinical and military applications, social cloud and security surveillance in recent years, contributing significantly to preserving the privacy of digital images. Aiming to address the shortcomings of recent works that directed to achieve high embedding rate by compensating image quality, security, reversible and separable properties, we propose a two-tuples coding method by considering the intrinsic adjacent pixels characteristics of the carrier image, which have a high redundancy between high-order bits. Subsequently, we construct RDH-EI scheme by using high-order bits compression, low-order bits combination, vacancy filling, data embedding and pixel diffusion. Unlike the conventional RDH-EI practices, which have suffered from the deterioration of the original image while embedding additional data, the content owner in our scheme generates the embeddable space in advance, thus lessening the risk of image destruction on the data hider side. The experimental results indicate the effectiveness of our scheme. A ratio of 28.91% effectively compressed the carrier images, and the embedding rate increased to 1.753 bpp with a higher image quality, measured in the PSNR of 45.76 dB.

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