Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
<p>Production of vectors for four layers [<a href="#B3-processes-10-00858" class="html-bibr">3</a>]: (<b>a</b>) Layer-1; (<b>b</b>) Layer-2; (<b>c</b>) Layer-3; (<b>d</b>) Layer-4.</p> "> Figure 2
<p>Production of the matrices for three classes: (<b>a</b>) Class <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">C</mi> <mn>1</mn> </msub> </mrow> </semantics></math>; (<b>b</b>) Class <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">C</mi> <mn>2</mn> </msub> <mo>;</mo> </mrow> </semantics></math> (<b>c</b>) Class <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">C</mi> <mn>3</mn> </msub> </mrow> </semantics></math>.</p> "> Figure 3
<p>Production of the vector P.</p> "> Figure 4
<p>An example of quad-pixel reversible data embedding: (<b>a</b>) before embedding; (<b>b</b>) after embedding; (<b>c</b>) after extraction.</p> "> Figure 5
<p>Used host images in this paper: (<b>a</b>) Lena; (<b>b</b>) Peppers; (<b>c</b>) Airplane; (<b>d</b>) Baboon; (<b>e</b>) Ship; (<b>f</b>) Barbara; (<b>g</b>) Cameraman; (<b>h</b>) Lake; (<b>i</b>) Bridge.</p> "> Figure 6
<p>Comparison of image quality for single-layer capacity: (<b>a</b>) Airplane; (<b>b</b>) Baboon; (<b>c</b>) Barbara; (<b>d</b>) Ship; (<b>e</b>) Lena; (<b>f</b>) Peppers; (<b>g</b>) Lake; (<b>h</b>) Bridge [<a href="#B3-processes-10-00858" class="html-bibr">3</a>].</p> "> Figure 6 Cont.
<p>Comparison of image quality for single-layer capacity: (<b>a</b>) Airplane; (<b>b</b>) Baboon; (<b>c</b>) Barbara; (<b>d</b>) Ship; (<b>e</b>) Lena; (<b>f</b>) Peppers; (<b>g</b>) Lake; (<b>h</b>) Bridge [<a href="#B3-processes-10-00858" class="html-bibr">3</a>].</p> "> Figure 7
<p>Comparing the quality values for multilayer capacities in different images: (<b>a</b>) Airplane; (<b>b</b>) Baboon; (<b>c</b>) Barbara; (<b>d</b>) Ship; (<b>e</b>) Lena; (<b>f</b>) Peppers; (<b>g</b>) Lake; (<b>h</b>) Bridge [<a href="#B3-processes-10-00858" class="html-bibr">3</a>].</p> "> Figure 7 Cont.
<p>Comparing the quality values for multilayer capacities in different images: (<b>a</b>) Airplane; (<b>b</b>) Baboon; (<b>c</b>) Barbara; (<b>d</b>) Ship; (<b>e</b>) Lena; (<b>f</b>) Peppers; (<b>g</b>) Lake; (<b>h</b>) Bridge [<a href="#B3-processes-10-00858" class="html-bibr">3</a>].</p> ">
Abstract
:1. Introduction
2. Proposed Method
2.1. Multilevel Thresholding Using the Slime Mould Algorithm
2.2. Data Insertion Process
2.3. Data Extraction Process
3. Results
3.1. Evaluation Metrics
3.2. Comparison with the Other Methods
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Key Acronyms | Their Meanings |
---|---|
DH | Data hiding |
DWT | Discrete wavelet transform |
DCT | Discrete cosine transform |
RDH | Reversible data hiding |
DE | Difference expansion |
HS | Histogram shifting |
PEE | Prediction-error expansion |
PVG | Pixel value grouping |
PVO | Pixel value ordering |
DH | Difference histogram |
PEH | PE histogram |
GA | Genetic algorithm |
PPEE | Pairwise prediction-error expansion |
2D-PEH | Two-dimensional PEH |
RRDH | Robust reversible data hiding |
HSB | Higher significant bit |
LSB | Least important bit |
PEE | Prediction-error expansion |
RDHEI | RDH in encrypted images |
MSE | Mean squared error |
PSNR | Peak signal-to-noise ratio |
bpp | Bits per pixel |
SSIM | Structural similarity index measure |
Proposed | Insertion Capacity (bits) | Insertion Capacity (bpp) | ||||||
---|---|---|---|---|---|---|---|---|
Image | T1 | T2 | [3] | [24] | PM | [3] | [24] | PM |
Airplane | 111 | 182 | 194,250 | 210,000 | 215,000 | 0.7449 | 0.8010 | 0.8201 |
Baboon | 78 | 149 | 193,314 | 110,000 | 195,003 | 0.7374 | 0.4196 | 0.7438 |
Barbara | 55 | 131 | 191,466 | 158,000 | 192,232 | 0.7304 | 0.6027 | 0.7333 |
Ship | 79 | 156 | 194,583 | 160,000 | 196,144 | 0.7423 | 0.6103 | 0.7482 |
Lena | 85 | 152 | 196,768 | 200,000 | 209,000 | 0.7480 | 0.7629 | 0.7972 |
Lake | 76 | 145 | 191,854 | 111,000 | 193,458 | 0.7318 | 0.4234 | 0.7514 |
Bridge | 84 | 151 | 192,472 | 185,000 | 196,874 | 0.7342 | 0.7186 | 0.7379 |
Cameraman | 91 | 174 | 194,968 | 159,000 | 199,762 | 0.7437 | 0.6039 | 0.7510 |
Peppers | 61 | 136 | 195,414 | 178,000 | 196,985 | 0.7454 | 0.6790 | 0.7514 |
Proposed | Processing Time (s) | ||||
---|---|---|---|---|---|
Image | T1 | T2 | [3] | [24] | PM |
Airplane | 111 | 182 | 154.09 | 1.29 | 173.94 |
Baboon | 78 | 149 | 153.72 | 1.81 | 173.60 |
Barbara | 55 | 131 | 151.44 | 1.37 | 175.35 |
Ship | 79 | 156 | 138.11 | 1.44 | 160.99 |
Lena | 85 | 152 | 153.58 | 1.67 | 181.56 |
Lake | 76 | 145 | 152.41 | 1.37 | 174.56 |
Bridge | 84 | 151 | 153.25 | 1.41 | 175.92 |
Cameraman | 91 | 174 | 139.48 | 1.62 | 179.45 |
Peppers | 61 | 136 | 154.11 | 1.15 | 185.98 |
PSNR (dB) | ||||||||
---|---|---|---|---|---|---|---|---|
0.1 bpp | 0.2 bpp | 0.3 bpp | 0.4 bpp | 0.5 bpp | 0.6 bpp | 0.7 bpp | ||
Airplane | [3] | 54.35 | 51.88 | 48.85 | 44.36 | 42.45 | 41.44 | 40.92 |
Proposed | 55.17 | 52.73 | 49.99 | 45.40 | 44.07 | 43.11 | 41.86 | |
Baboon | [3] | 40.95 | 38.97 | 37.98 | 36.95 | 36.48 | 35.97 | 35.40 |
Proposed | 42.01 | 40.03 | 38.88 | 37.34 | 37.11 | 36.54 | 36.89 | |
Barbara | [3] | 49.29 | 46.73 | 43.84 | 41.12 | 38.98 | 37.50 | 36.57 |
Proposed | 50.74 | 47.43 | 44.45 | 42.31 | 39.12 | 38.61 | 37.63 | |
Ship | [3] | 50.71 | 46.86 | 43.85 | 41.95 | 40.92 | 40.46 | 40.19 |
Proposed | 51.85 | 48.46 | 45.48 | 43.01 | 42.15 | 41.64 | 41.78 | |
Lena | [3] | 54.70 | 50.31 | 47.74 | 45.77 | 44.19 | 43.03 | 42.16 |
Proposed | 55.18 | 52.12 | 48.61 | 46.17 | 45.46 | 44.61 | 43.44 | |
Lake | [3] | 48.32 | 44.16 | 40.35 | 38.36 | 36.56 | 34.79 | 33.21 |
Proposed | 49.97 | 45.98 | 41.68 | 39.86 | 37.15 | 35.96 | 34.56 | |
Bridge | [3] | 47.76 | 43.32 | 39.86 | 36.75 | 34.85 | 33.45 | 31.99 |
Proposed | 49.23 | 44.53 | 40.96 | 37.82 | 35.98 | 34.59 | 32.68 | |
Cameraman | [3] | 46.12 | 42.36 | 38.25 | 34.91 | 32.56 | 31.20 | 30.05 |
Proposed | 48.06 | 43.74 | 39.94 | 36.20 | 34.11 | 32.31 | 31.11 | |
Peppers | [3] | 49.66 | 47.12 | 45.37 | 43.92 | 43.15 | 42.61 | 42.05 |
Proposed | 51.11 | 48.94 | 46.33 | 44.61 | 45.20 | 43.45 | 43.11 |
PSNR (dB) | |||||||||
---|---|---|---|---|---|---|---|---|---|
0.7 bpp | 1.5 bpp | 2.2 bpp | 3 bpp | 3.7 bpp | 4.5 bpp | 5.2 bpp | 6 bpp | ||
Airplane | [3] | 40.5 | 36.59 | 35.1 | 34 | 32.5 | 31.9 | 31 | 30 |
Proposed | 41.12 | 38.02 | 36.25 | 35.01 | 33.84 | 32.56 | 32.97 | 31.01 | |
Baboon | [3] | 35.1 | 32 | 30 | 28.5 | 27.1 | 26.2 | 25.3 | 25 |
Proposed | 36.98 | 33.24 | 31.12 | 29.95 | 28.87 | 27.97 | 26.78 | 26.25 | |
Barbara | [3] | 36.2 | 33.9 | 32 | 30.7 | 29.1 | 28.83 | 27.8 | 27 |
Proposed | 37.45 | 34.25 | 33.12 | 31.99 | 30.47 | 30.02 | 28.11 | 28 | |
Ship | [3] | 40.58 | 36.9 | 35 | 33.2 | 32 | 31.57 | 30 | 29.1 |
Proposed | 42.01 | 37.2 | 36.11 | 34.42 | 33 | 33.03 | 31 | 30.25 | |
Lena | [3] | 42 | 38.2 | 37 | 35.1 | 34 | 33 | 32.1 | 31.1 |
Proposed | 43.52 | 39.44 | 38 | 36.55 | 35 | 34.11 | 33 | 32 | |
Lake | [3] | 37.26 | 34.73 | 32.82 | 31.74 | 30.82 | 29 | 27.76 | 26 |
Proposed | 38.99 | 35.47 | 34.15 | 33.26 | 32.42 | 30.76 | 29.12 | 27.22 | |
Bridge | [3] | 37.85 | 33.72 | 32.25 | 31.74 | 29.18 | 28 | 26.87 | 25.10 |
Proposed | 39.23 | 35.28 | 33.76 | 32.06 | 30.46 | 29 | 27.75 | 26 | |
Cameraman | [3] | 40.51 | 36.97 | 34.98 | 32.76 | 30.56 | 28.75 | 27 | 25.34 |
Proposed | 42.07 | 38.13 | 36.46 | 35.36 | 32.89 | 31.46 | 29.42 | 26.12 | |
Peppers | [3] | 41.9 | 38.3 | 36.3 | 35 | 34 | 33 | 32 | 31.1 |
Proposed | 43 | 39.85 | 37 | 36.55 | 35.89 | 34 | 33 | 32.34 |
Proposed | Insertion Capacity (bits) | SSIM | ||||||
---|---|---|---|---|---|---|---|---|
Image | T1 | T2 | [3] | [24] | PM | [3] | [24] | PM |
Airplane | 111 | 182 | 194,250 | 210,000 | 215,000 | 0.9128 | 0.9131 | 0.9261 |
Baboon | 78 | 149 | 193,314 | 110,000 | 195,003 | 0.9125 | 0.9155 | 0.9298 |
Barbara | 55 | 131 | 191,466 | 158,000 | 192,232 | 0.9135 | 0.9146 | 0.9283 |
Ship | 79 | 156 | 194,583 | 160,000 | 196,144 | 0.9134 | 0.9124 | 0.9282 |
Lena | 85 | 152 | 196,768 | 200,000 | 209,000 | 0.9132 | 0.9138 | 0.9272 |
Lake | 76 | 145 | 191,854 | 111,000 | 193,458 | 0.9157 | 0.9115 | 0.9284 |
Bridge | 84 | 151 | 192,472 | 185,000 | 196,874 | 0.9125 | 0.9114 | 0.9279 |
Cameraman | 91 | 174 | 194,968 | 159,000 | 199,762 | 0.9148 | 0.9118 | 0.9256 |
Peppers | 61 | 136 | 195,414 | 178,000 | 196,985 | 0.9136 | 0.9145 | 0.9274 |
SSIM | ||||||||
---|---|---|---|---|---|---|---|---|
0.1 bpp | 0.2 bpp | 0.3 bpp | 0.4 bpp | 0.5 bpp | 0.6 bpp | 0.7 bpp | ||
Airplane | [3] | 0.9736 | 0.9658 | 0.9531 | 0.9462 | 0.9312 | 0.9243 | 0.9134 |
Proposed | 0.9865 | 0.9736 | 0.9638 | 0.9582 | 0.9462 | 0.9365 | 0.9245 | |
Baboon | [3] | 0.9735 | 0.9685 | 0.9538 | 0.9425 | 0.9365 | 0.9235 | 0.9141 |
Proposed | 0.9846 | 0.9734 | 0.9648 | 0.9536 | 0.9468 | 0.9328 | 0.9267 | |
Barbara | [3] | 0.9762 | 0.9694 | 0.9539 | 0.9462 | 0.9361 | 0.9217 | 0.9119 |
Proposed | 0.9873 | 0.9725 | 0.9647 | 0.9543 | 0.9486 | 0.9369 | 0.9278 | |
Ship | [3] | 0.9748 | 0.9657 | 0.9567 | 0.9474 | 0.9313 | 0.9236 | 0.9167 |
Proposed | 0.9839 | 0.9746 | 0.9625 | 0.9512 | 0.9452 | 0.9385 | 0.9286 | |
Lena | [3] | 0.9743 | 0.9651 | 0.9512 | 0.9436 | 0.9321 | 0.9238 | 0.9118 |
Proposed | 0.9849 | 0.9783 | 0.9674 | 0.9572 | 0.9445 | 0.9368 | 0.9264 | |
Lake | [3] | 0.9739 | 0.9645 | 0.9536 | 0.9412 | 0.9336 | 0.9225 | 0.9136 |
Proposed | 0.9818 | 0.9762 | 0.9652 | 0.9548 | 0.9462 | 0.9368 | 0.9275 | |
Bridge | [3] | 0.9786 | 0.9638 | 0.9536 | 0.9438 | 0.9356 | 0.9283 | 0.9169 |
Proposed | 0.9863 | 0.9782 | 0.9671 | 0.9582 | 0.9468 | 0.9397 | 0.9247 | |
Cameraman | [3] | 0.9768 | 0.9637 | 0.9532 | 0.9413 | 0.9367 | 0.9214 | 0.9179 |
Proposed | 0.9864 | 0.9726 | 0.9682 | 0.9551 | 0.9439 | 0.9369 | 0.9264 | |
Peppers | [3] | 0.9739 | 0.9632 | 0.9539 | 0.9462 | 0.9363 | 0.9258 | 0.9179 |
Proposed | 0.9827 | 0.9746 | 0.9648 | 0.9583 | 0.9486 | 0.9378 | 0.9248 |
30,000 (bits) | 50,000 (bits) | |||||||
---|---|---|---|---|---|---|---|---|
psnr | ssim | psnr | ssim | |||||
Image | Yao et al. [30] | PM | Yao et al. [30] | PM | ||||
Airplane | 65.56 | 0.9736 | 66.12 | 0.9846 | 64.34 | 0.9616 | 65.22 | 0.9765 |
Baboon | 65.56 | 0.9747 | 66.68 | 0.9874 | 64.34 | 0.9623 | 65.44 | 0.9716 |
Barbara | 65.56 | 0.9732 | 66.23 | 0.9834 | 64.34 | 0.9675 | 65.65 | 0.9736 |
Ship | 65.56 | 0.9747 | 66.42 | 0.9845 | 64.34 | 0.9646 | 65.61 | 0.9765 |
Lena | 65.56 | 0.9761 | 66.29 | 0.9856 | 64.34 | 0.9654 | 65.12 | 0.9748 |
Lake | 65.42 | 0.9719 | 66.18 | 0.9885 | 64.12 | 0.9638 | 65.83 | 0.9716 |
Bridge | 65.56 | 0.9764 | 66.47 | 0.9849 | 64.34 | 0.9676 | 65.79 | 0.9734 |
Cameraman | 65.55 | 0.9773 | 66.42 | 0.9859 | 64.34 | 0.9649 | 65.68 | 0.9756 |
Peppers | 65.56 | 0.9772 | 66.82 | 0.9817 | 64.34 | 0.9647 | 65.36 | 0.9748 |
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Mehbodniya, A.; Douraki, B.k.; Webber, J.L.; Alkhazaleh, H.A.; Elbasi, E.; Dameshghi, M.; Abu Zitar, R.; Abualigah, L. Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm. Processes 2022, 10, 858. https://doi.org/10.3390/pr10050858
Mehbodniya A, Douraki Bk, Webber JL, Alkhazaleh HA, Elbasi E, Dameshghi M, Abu Zitar R, Abualigah L. Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm. Processes. 2022; 10(5):858. https://doi.org/10.3390/pr10050858
Chicago/Turabian StyleMehbodniya, Abolfazl, Behnaz karimi Douraki, Julian L. Webber, Hamzah Ali Alkhazaleh, Ersin Elbasi, Mohammad Dameshghi, Raed Abu Zitar, and Laith Abualigah. 2022. "Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm" Processes 10, no. 5: 858. https://doi.org/10.3390/pr10050858