CONCEAL: A robust dual-color image watermarking scheme. (1st December 2022)
- Record Type:
- Journal Article
- Title:
- CONCEAL: A robust dual-color image watermarking scheme. (1st December 2022)
- Main Title:
- CONCEAL: A robust dual-color image watermarking scheme
- Authors:
- Luo, Yuling
Wang, Fangxiao
Xu, Shanshan
Zhang, Shunsheng
Li, Liangjia
Su, Min
Liu, Junxiu - Abstract:
- Highlights: A dual-color watermarking based on inter-block matrix decomposition is proposed. A novel diagonal relationship is developed to embed the watermark. The amount of data for color watermark is reduced by combining compressive sensing. Matrix decomposition is used for the first time between surrounding inter-block. Results show a large embedding capacity, excellent imperceptibility and robustness. Abstract: Compared with binary and grayscale watermark, the color watermark has a larger amount of information, which makes color blind watermarking algorithms more challenging in terms of robustness, watermark capacity and computational complexity under the limitation of distortion. To better meet these challenges, a robust dual-COlor image watermarking scheme exploiting COmpressive seNsing and inter-bloCk approximatE mAximum eigenvaLue, namely CONCEAL, is proposed in this work. Specifically, the Compressive Sensing (CS) is first executed on a watermark, which can effectively compress the watermark information to one-half of the original. Secondly, the carrier image is separated into 4 × 4 non-overlapping pixel blocks, and the standard deviation of each pixel block is calculated. Then, the pixel blocks with smaller standard deviations are subdivided into four 2 × 2 non-overlapping pixel sub-blocks (the upper-left, lower-left, upper-right, and lower-right pixel sub-blocks), and the Approximate Maximum Eigenvalue (AME) of four sub-pixel blocks are directly calculated in theHighlights: A dual-color watermarking based on inter-block matrix decomposition is proposed. A novel diagonal relationship is developed to embed the watermark. The amount of data for color watermark is reduced by combining compressive sensing. Matrix decomposition is used for the first time between surrounding inter-block. Results show a large embedding capacity, excellent imperceptibility and robustness. Abstract: Compared with binary and grayscale watermark, the color watermark has a larger amount of information, which makes color blind watermarking algorithms more challenging in terms of robustness, watermark capacity and computational complexity under the limitation of distortion. To better meet these challenges, a robust dual-COlor image watermarking scheme exploiting COmpressive seNsing and inter-bloCk approximatE mAximum eigenvaLue, namely CONCEAL, is proposed in this work. Specifically, the Compressive Sensing (CS) is first executed on a watermark, which can effectively compress the watermark information to one-half of the original. Secondly, the carrier image is separated into 4 × 4 non-overlapping pixel blocks, and the standard deviation of each pixel block is calculated. Then, the pixel blocks with smaller standard deviations are subdivided into four 2 × 2 non-overlapping pixel sub-blocks (the upper-left, lower-left, upper-right, and lower-right pixel sub-blocks), and the Approximate Maximum Eigenvalue (AME) of four sub-pixel blocks are directly calculated in the spatial-domain at the same time. Finally, every 3-bit watermark data is embedded in a 4 × 4 pixel block using the AME of the upper-left pixel sub-block and the other three pixel sub-blocks. The imperceptibility and robustness of CONCEAL are assessed experimentally. The experimental results show that all Peak Signal-to-Noise Ratios (PSNRs) are above 47 dB, Structural Similarity Index Measures (SSIMs) are above 0.98, and Normalized Correlations (NCs) are above 0.9. Compared with the state-of-the-art schemes, the proposed CONCEAL possesses large capacity, high imperceptibility, comparable robustness. … (more)
- Is Part Of:
- Expert systems with applications. Volume 208(2022)
- Journal:
- Expert systems with applications
- Issue:
- Volume 208(2022)
- Issue Display:
- Volume 208, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 208
- Issue:
- 2022
- Issue Sort Value:
- 2022-0208-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12-01
- Subjects:
- Dual-color image -- Compressive sensing -- Inter-block -- Approximate maximum eigenvalue
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2022.118133 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23385.xml