Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction
Reversible data hiding (RDH) is a technique that embeds secret data into digital media while preserving the integrity of the original media and the secret data. RDH has a wide range of application scenarios in industrial image processing, such as intellectual property protection and data integrity v...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/12/4/517 |
| _version_ | 1827343264908312576 |
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| author | Dan He Zhanchuan Cai |
| author_facet | Dan He Zhanchuan Cai |
| author_sort | Dan He |
| collection | DOAJ |
| description | Reversible data hiding (RDH) is a technique that embeds secret data into digital media while preserving the integrity of the original media and the secret data. RDH has a wide range of application scenarios in industrial image processing, such as intellectual property protection and data integrity verification. However, with the increasing prevalence of color images in industrial applications, traditional RDH methods for grayscale images are inadequate to meet the requirements of image fidelity. This paper proposes an RDH method for color images based on channel reference mapping (CRM) and adaptive pixel prediction. Initially, the CRM mode for a color image is established based on the pixel variation correlation between the RGB channels. Then, the pixel local complexity context is adaptively selected using the CRM mode. Next, each pixel value is adaptively predicted based on the features and characteristics of adjacent pixels and reference channels, and then data is embedded by expanding the prediction error. Finally, we compare seven existing RDH algorithms on the standard image dataset and the Kodak dataset to validate the advantages of our method. The experimental results demonstrate that our approach achieves average peak signal-to-noise ratio (PSNR) values of 63.61 and 60.53 dB when embedding 20,000 and 40,000 bits of data, respectively. These PSNR values surpass those of other RDH methods. These findings indicate that our method can effectively preserve the visual quality of images even under high embedding capacities. |
| first_indexed | 2024-03-07T22:22:45Z |
| format | Article |
| id | doaj.art-511dde0d9cdb4cedb7af3bd3afb906ac |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-07T22:22:45Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-511dde0d9cdb4cedb7af3bd3afb906ac2024-02-23T15:26:02ZengMDPI AGMathematics2227-73902024-02-0112451710.3390/math12040517Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel PredictionDan He0Zhanchuan Cai1School of Computer Science and Engineering, Macau University of Science and Technology, Macau 999078, ChinaSchool of Computer Science and Engineering, Macau University of Science and Technology, Macau 999078, ChinaReversible data hiding (RDH) is a technique that embeds secret data into digital media while preserving the integrity of the original media and the secret data. RDH has a wide range of application scenarios in industrial image processing, such as intellectual property protection and data integrity verification. However, with the increasing prevalence of color images in industrial applications, traditional RDH methods for grayscale images are inadequate to meet the requirements of image fidelity. This paper proposes an RDH method for color images based on channel reference mapping (CRM) and adaptive pixel prediction. Initially, the CRM mode for a color image is established based on the pixel variation correlation between the RGB channels. Then, the pixel local complexity context is adaptively selected using the CRM mode. Next, each pixel value is adaptively predicted based on the features and characteristics of adjacent pixels and reference channels, and then data is embedded by expanding the prediction error. Finally, we compare seven existing RDH algorithms on the standard image dataset and the Kodak dataset to validate the advantages of our method. The experimental results demonstrate that our approach achieves average peak signal-to-noise ratio (PSNR) values of 63.61 and 60.53 dB when embedding 20,000 and 40,000 bits of data, respectively. These PSNR values surpass those of other RDH methods. These findings indicate that our method can effectively preserve the visual quality of images even under high embedding capacities.https://www.mdpi.com/2227-7390/12/4/517reversible data hidingindustrial color imagechannel reference mappinginformation security |
| spellingShingle | Dan He Zhanchuan Cai Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction Mathematics reversible data hiding industrial color image channel reference mapping information security |
| title | Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction |
| title_full | Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction |
| title_fullStr | Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction |
| title_full_unstemmed | Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction |
| title_short | Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction |
| title_sort | reversible data hiding for color images using channel reference mapping and adaptive pixel prediction |
| topic | reversible data hiding industrial color image channel reference mapping information security |
| url | https://www.mdpi.com/2227-7390/12/4/517 |
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