A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness
Abstract
:1. Introduction
- (1)
- Some schemes are not completely reversible, especially those based on the transform domain. Because the mapping relationship between the spatial domain and the frequency domain is not considered, the watermarked image pixel values are not integers. This results in the image losing its reversible characteristics, as in [28]. Moreover, when the data set is large, reliability and stability remain problematic, resulting in some carrier images not being fully restored.
- (2)
- Robustness is not strong enough generally. Applying an integer wavelet transform to achieve reversibility while reducing the running time has been reported [23,32]. However, the experimental evaluations revealed the approaches are very sensitive to various attacks [41]. Thus, the watermark cannot be extracted correctly when attacked.
- (3)
- Most algorithms have limitations in balancing the contradiction between watermark embedding capacity and invisibility. For example, in [37] the PSNR is less than 45 dB after embedding 20,000 bits of watermark information. In other algorithms, the embedding capacity is sacrificed to reduce the image distortion [35,36].
- (4)
- At present, most of the reversible medical image watermarking schemes are performed on grayscale images [42,43], and there is little research on color medical images. However, black-and-white medical images can undergo pseudo-color processing for density segmentation technology [44] so that the observer can obtain more information. This presents broad application prospects.
- A robust reversible watermarking scheme for medical color images using image block information to represent watermarks is proposed. The watermark embedding flag (WEF) and the embedding status flag (ESF) are set for each block, as well as for representing the watermark. This reduces the modification of the original image as much as possible and improves the imperceptibility.
- The hierarchical embedding strategy is adopted for the different value ranges of the embedding status flag to maximize the imperceptibility.
- The order of the Zernike moment that is stable and suitable for correction is selected through experiments, which improves the accuracy of geometric correction.
2. Preliminaries
2.1. Reversibility of the Haar Wavelet Transform (HWT)
2.2. Zernike Moments
2.2.1. Rotation Detection
2.2.2. Scaling Detection
3. Proposed Watermarking Scheme
3.1. Watermark Detection
3.2. Watermark Embedding
3.3. Calculating Zernike Moments
3.4. Watermark Extraction
4. Experiment Results
4.1. Criteria and Database
4.2. Geometric Correction of Zernike Moments
4.2.1. Rotating Attack
4.2.2. Scale Attack
4.3. Imperceptibility and Capacity Results
4.4. Robust Scheme
4.5. Complexity Analysis
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Notation | Description | Notation | Description |
---|---|---|---|
Watermark sequence | The values of the red channel after three-level DWT of . | ||
The number of 1 in the watermark sequence | () | The values at the coordinates () of the red channel after two-level DWT of . | |
The number of 0 in the watermark sequence | The threshold used to classify ESF | ||
Host image | Classifying intensity | ||
The coordinates of each block | The k-th watermark bit to be embedded | ||
The size of the host image | Embedded intensity | ||
Watermark embedding flag (WEF) | ESF when the watermark is embedded | ||
Embedding status flag (ESF) | -th extracted watermark bit |
Scale Parameter | Scale 0.6 | Scale 0.8 | Scale 1.1 | Scale 1.3 | Scale 1.6 |
---|---|---|---|---|---|
Correct scale parameter | 0.60000 | 0.80338 | 1.10233 | 1.30853 | 1.60320 |
Capacity (Bits) | 4096 | 8192 | 12,288 | 16,384 | 20,480 | 24,576 |
BPP | 0.005208 | 0.010417 | 0.015625 | 0.020833 | 0.026042 | 0.03125 |
Brain | Hands | Spine | |
---|---|---|---|
Original Image | | | |
Watermarked Image | | | |
| | | | |
Median Filter 2 × 2 | BER = 0.0857 NC = 0.9872 | BER = 0.0920 NC = 0.9969 | BER = 0.0488 NC = 0.9957 | BER = 0.1025 NC = 0.9949 |
Median Filter 3 × 3 | BER = 0.0798 NC = 0.9937 | BER = 0.0833 NC = 0.9994 | BER = 0.0481 NC = 0.9984 | BER= 0.0938 NC = 0.9980 |
Median Filter 5 × 5 | BER = 0.0725 NC = 0.9839 | BER = 0.0872 NC = 0.9976 | BER = 0.0505 NC = 0.9944 | BER = 0.0896 NC = 0.9943 |
Average Filter 3 × 3 | BER = 0.0779 NC = 0.9876 | BER = 0.0854 NC = 0.9987 | BER = 0.0479 NC = 0.9977 | BER = 0.0874 NC = 0.9973 |
Average Filter 5 × 5 | BER = 0.0713 NC = 0.9811 | BER = 0.0823 NC = 0.9955 | BER = 0.0493 NC = 0.9925 | BER = 0.0808 NC = 0.9920 |
Motion Filter | BER = 0.0681 NC = 0.9819 | BER = 0.0884 NC = 0.9898 | BER = 0.0454 NC = 0.9878 | BER = 0.0999 NC = 0.9889 |
Original images | | | | |
Histogram Equalization | BER = 0.0671 NC = 0.7498 | BER = 0.0889 NC = 0.6014 | BER = 0.0476 NC = 0.5509 | BER = 0.0962 NC = 0.5418 |
Image Brighten | BER = 0.0713 NC = 0.7091 | BER = 0.0920 NC = 0.5673 | BER = 0.0591 NC = 0.5196 | BER = 0.1003 NC = 0.6017 |
Image Darken | BER = 0.0444 NC = 1.0000 | BER = 0.0461 NC = 1.0000 | BER = 0.0229 NC = 1.0000 | BER = 0.0898 NC = 1.0000 |
Contrast Increasing | BER = 0.0718 NC = 0.5417 | BER = 0.0920 NC = 0.8565 | BER = 0.3079 NC = 0.5415 | BER = 0.1055 NC = 0.7564 |
Contrast Decreasing | BER = 0.0662 NC = 0.7549 | BER = 0.0801 NC = 0.6291 | BER = 0.0415 NC = 0.5635 | BER = 0.1042 NC = 0.6610 |
Function Name | Calls | % of Time |
---|---|---|
dwt2 | 12,288 | 62.89% |
idwt2 | 6420 | 33.13% |
Function Name | Calls | % of Time |
---|---|---|
dwt2 | 12,288 | 61.11% |
idwt2 | 6420 | 35.89% |
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Zhou, X.; Ma, Y.; Zhang, Q.; Mohammed, M.A.; Damaševičius, R. A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness. Electronics 2021, 10, 1024. https://doi.org/10.3390/electronics10091024
Zhou X, Ma Y, Zhang Q, Mohammed MA, Damaševičius R. A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness. Electronics. 2021; 10(9):1024. https://doi.org/10.3390/electronics10091024
Chicago/Turabian StyleZhou, Xiaoyi, Yue Ma, Qingquan Zhang, Mazin Abed Mohammed, and Robertas Damaševičius. 2021. "A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness" Electronics 10, no. 9: 1024. https://doi.org/10.3390/electronics10091024