A High Visual Quality Color Image Reversible Data Hiding Scheme Based on B-R-G Embedding Principle and CIEDE2000 Assessment Metric

Yang, Yang; Zou, Tianrui; Huang, Genyan; Zhang, Weiming

doi:10.1109/tcsvt.2021.3084676

Cited by 26 publications

(8 citation statements)

References 40 publications

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“…The quality assessment, is a practical multi-distortion metric for three host sub sequences for the R, G and B channels is well-defined as mentioned in (8).…”

Section: Proposed Methodsmentioning

confidence: 99%

“…Due to its great embedding capacity and usage of double layers in data embedding, this technique inherits from histogram shifting its reversibility characteristic. Yang et al [8] proposed double-layer least square prediction to satisfy the sorting requirement and maintain prediction accuracy, and then the blue-red-green embedded principle is proposed to enhance the visual quality of the marked colour images for diverse visual perceptions.…”

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confidence: 99%

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Colour image steganography through channel transformation approach

Neginal

Fatima²

2023

IJ-AI

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The interest in information security strategies is expanding due the quick expansion in the use of media content and transmission over the web employments. Accordingly, there is a need of special embedding procedure for steganography. The creator presents an original reversible data hiding (RDH) algorithm for colour pictures that further develops the inserting execution by applying a channel transformation function and a versatile expectation blunder extension prediction error expansion structure. The proposed calculation will bring the first colour picture with no information misfortune from the inserted picture (which is unique in addition to target picture). The evaluation is done here at the zero for the given base place for the histogram that marginally changes the pixel esteems for inserting the information. It can insert more information when contrasted with the majority of the current data hiding calculations. A hypothetical confirmation and various examinations state that the embedding capability of the proposed model which consistently is further noteworthy in comparison with other reversible data hiding techniques. The calculation has been applied to a wide scope of various colour pictures effectively. Some exploratory outcomes are introduced to show the legitimacy of the calculation.

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“…The quality assessment, is a practical multi-distortion metric for three host sub sequences for the R, G and B channels is well-defined as mentioned in (8).…”

Section: Proposed Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Colour image steganography through channel transformation approach

Neginal

Fatima²

2023

IJ-AI

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show abstract

“…The color perception differences Δ L ′,Δ H ′ and Δ C ′ are calculated in the same way as Equations (10), (11), and (12). S L , S C , and S H are the luminance, chromaticity, and hue weighting factors, and R T is the rotation factor used to correct for chromaticity differences to match visual perception ( Yang et al, 2022 ). The smaller values of

and Δ E 00 indicate the smaller color perception differences of the samples.…”

Section: Methodsmentioning

confidence: 99%

An improved spectral estimation method based on color perception features of mobile phone camera

Liu

Wu²,

Liang³

et al. 2022

Front. Neurosci.

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We use the mobile phone camera as a new spectral imaging device to obtain raw responses of samples for spectral estimation and propose an improved sequential adaptive weighted spectral estimation method. First, we verify the linearity of the raw response of the cell phone camera and investigate its feasibility for spectral estimation experiments. Then, we propose a sequential adaptive spectral estimation method based on the CIE1976 L*a*b* (CIELAB) uniform color space color perception feature. The first stage of the method is to weight the training samples and perform the first spectral reflectance estimation by considering the Lab color space color perception features differences between samples, and the second stage is to adaptively select the locally optimal training samples and weight them by the first estimated root mean square error (RMSE), and perform the second spectral reconstruction. The novelty of the method is to weight the samples by using the sample in CIELAB uniform color space perception features to more accurately characterize the color difference. By comparing with several existing methods, the results show that the method has the best performance in both spectral error and chromaticity error. Finally, we apply this weighting strategy based on the CIELAB color space color perception feature to the existing method, and the spectral estimation performance is greatly improved compared with that before the application, which proves the effectiveness of this weighting method.

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“…The proposed HIDEmarks algorithm revealed little colour difference in combination with high capacity for embedding. The CIEDE2000 [33] was used to measure…”

Section: Subjective Performancementioning

confidence: 99%

HIDEmarks: hiding multiple marks for robust medical data sharing using IWT-LSB

Singh

Baranwal

et al. 2023

Multimed Tools Appl

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With the increasing popularity of digital data in the healthcare domain, data hiding has become a hot research topic for covert communication and privacy protection. Existing data-hiding methods often tend to results in increased imperceptibility and robustness, which are also needed to simultaneously improve the system's security and embedding capacity. To solve this problem, a robust and high-capacity data hiding technique, called HIDEmarks, our study proposed a combination of integer wavelet transform (IWT) and least significant bit (LSB) for healthcare. Specifically, the IWT-LSB was used to embed multiple marks into the medical colour image. The technique first transformed cover images into three channels, and then each channel was transformed using IWT. After this, multiple marks were concealed into the cover media with the help of the LSB scheme. Meanwhile, a lossless soft method was adopted to compress the image mark prior to embedding, thereby reducing storage and transmission overhead and improving the embedding capacity of the marked colour image. Experimental results show that the proposed HIDEmarks achieved superior perceptual quality, robustness and capacity compared with the state-of-the-art schemes.

show abstract

A High Visual Quality Color Image Reversible Data Hiding Scheme Based on B-R-G Embedding Principle and CIEDE2000 Assessment Metric

Cited by 26 publications

References 40 publications

Colour image steganography through channel transformation approach

Colour image steganography through channel transformation approach

An improved spectral estimation method based on color perception features of mobile phone camera

HIDEmarks: hiding multiple marks for robust medical data sharing using IWT-LSB

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