Lossless Contrast Enhancement of Color Images with Reversible Data Hiding
Abstract
:1. Introduction
2. Reversible Contrast Enhancement Methods for Grayscale Images
2.1. RDH with Image Contrast Enhancement
2.2. An Order-Preserving Preprocessing
2.3. Automatic Contrast Enhancement with Reversible Data Hiding
3. Proposed Scheme for Contrast Enhancement of Color Images
3.1. HSV Color Model
3.2. Proposed Scheme
Algorithm 1: Enhancing an RGB image based on HSV color model |
|
- (1)
- Calculate the histogram of channel and carry out the preprocessing described in Section 2.2. Then the bookkeeping data is generated to record the changes made in preprocessing.
- (2)
- Find the highest two bins in the histogram and apply Equation (1) or Equation (2) to every value, respectively. Then find out the highest two bins in the newly generated histogram and repeatedly apply Equation (1) or Equation (2) until pairs of histogram bins have been expanded in total. Hide the necessary information during histogram bin expansion, including the bookkeeping data and its length.
- (3)
- (4)
- Replace the LSBs of the last 16 values with the lastly expanded bin values so that the modified V channel (i.e., channel) is generated.
3.3. Data Extraction and Image Recovery
Algorithm 2: Recovering the original color image |
|
- (1)
- Collect the LSBs of the last 16 values in the channel and the last expanded two bins can be obtained as .
- (2)
- Calculate the histogram of channel except the last 16 values and then perform data extraction by
- (3)
- Obtain the value of S, the previously expanded bins and the original LSBs of the last 16 values from the extracted data. Then write back the values of the original 16 LSBs back.
- (4)
- (5)
- Obtain the bookkeeping data from the extracted data and recover the original channel with it.
- (6)
- Make use of the rest extracted data (optional).
4. Experimental Results
4.1. Color Difference and Image Entropy
4.2. Contrast Enhancement Effects
4.3. Original Image Recovery
4.4. Pure Hiding Rate
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Image Set | Scheme | CIEDE2000 | Entropy | ||||||
---|---|---|---|---|---|---|---|---|---|
Original | S = 20 | S = 30 | S = 40 | Original | S = 20 | S = 30 | S = 40 | ||
USC | UCE [28] | 0 | 6.59 | 9.51 | 11.40 | 7.154 | 7.614 | 7.709 | 7.755 |
Proposed | 4.20 | 5.99 | 7.06 | 7.455 | 7.513 | 7.547 | |||
Kodak | UCE [28] | 0 | 6.89 | 9.16 | 10.71 | 7.104 | 7.487 | 7.562 | 7.604 |
Proposed | 4.13 | 5.58 | 6.60 | 7.414 | 7.492 | 7.534 |
Test Image | Scheme | RCE | RMBE | SSIM | PSNR | Entropy (Original) | CIEDE 2000 |
---|---|---|---|---|---|---|---|
Figure 3a | [28] | 0.548 | 0.933 | 0.843 | 19.47 | 7.788 (7.298) | 11.02 |
(S = 50) | Proposed | 0.529 | 0.943 | 0.859 | 20.10 | 7.537 (7.298) | 8.98 |
Figure 3e | [28] | 0.485 | 0.914 | 0.843 | 19.74 | 7.645 (7.293) | 13.71 |
(S = 50) | Proposed | 0.493 | 0.961 | 0.952 | 24.58 | 7.496 (7.293) | 4.30 |
Figure 3i | [28] | 0.552 | 0.919 | 0.862 | 18.45 | 7.815 (7.368) | 14.00 |
(S = 50) | Proposed | 0.549 | 0.996 | 0.905 | 22.41 | 7.642 (7.368) | 6.10 |
Metric | Image Set | t-Value | ||
---|---|---|---|---|
S = 20 | S = 30 | S = 40 | ||
CIEDE2000 | USC (6 images) | 4.648 | 3.011 | 3.539 |
Kodak (24 images) | 10.260 | 9.960 | 9.155 | |
entropy | USC (6 images) | 2.448 | 2.661 | 2.694 |
Kodak (24 images) | 2.688 | 2.270 | 2.188 |
S | Scheme | USC Image Set | Kodak Image Set | ||||||
---|---|---|---|---|---|---|---|---|---|
RCE | RMBE | SSIM | PSNR | RCE | RMBE | SSIM | PSNR | ||
20 | UCE [28] | 0.529 | 0.967 | 0.918 | 24.80 | 0.5348 | 0.9747 | 0.9207 | 24.51 |
Proposed | 0.517 | 0.969 | 0.944 | 26.31 | 0.5319 | 0.9869 | 0.9367 | 26.26 | |
30 | UCE [28] | 0.539 | 0.954 | 0.872 | 21.79 | 0.5476 | 0.9624 | 0.8815 | 21.79 |
Proposed | 0.524 | 0.953 | 0.910 | 23.32 | 0.5445 | 0.9798 | 0.8994 | 23.44 | |
40 | UCE [28] | 0.545 | 0.937 | 0.840 | 20.13 | 0.5569 | 0.9492 | 0.8540 | 20.12 |
Proposed | 0.528 | 0.941 | 0.887 | 21.88 | 0.5533 | 0.9738 | 0.8714 | 21.80 |
S | Image Set | USC Image Set | Kodak Image Set | ||||||
---|---|---|---|---|---|---|---|---|---|
SSIM | PSNR | Entropy | CIEDE2000 | SSIM | PSNR | Entropy | CIEDE2000 | ||
20 | original | 1.0000 | ∞ | 7.154 | 0.0000 | 1.0000 | ∞ | 7.104 | 0.0000 |
recovered | 0.9997 | 60.97 | 7.153 | 0.0703 | 0.9990 | 54.61 | 7.101 | 0.0885 | |
30 | original | 1.0000 | ∞ | 7.154 | 0.0000 | 1.0000 | ∞ | 7.104 | 0.0000 |
recovered | 0.9995 | 58.86 | 7.151 | 0.1016 | 0.9989 | 54.40 | 7.100 | 0.1092 | |
40 | original | 1.0000 | ∞ | 7.154 | 0.0000 | 1.0000 | ∞ | 7.104 | 0.0000 |
recovered | 0.9994 | 58.00 | 7.150 | 0.1199 | 0.9989 | 54.06 | 7.100 | 0.1164 |
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Wu, H.-T.; Wu, Y.; Guan, Z.; Cheung, Y.-m. Lossless Contrast Enhancement of Color Images with Reversible Data Hiding. Entropy 2019, 21, 910. https://doi.org/10.3390/e21090910
Wu H-T, Wu Y, Guan Z, Cheung Y-m. Lossless Contrast Enhancement of Color Images with Reversible Data Hiding. Entropy. 2019; 21(9):910. https://doi.org/10.3390/e21090910
Chicago/Turabian StyleWu, Hao-Tian, Yue Wu, Zhihao Guan, and Yiu-ming Cheung. 2019. "Lossless Contrast Enhancement of Color Images with Reversible Data Hiding" Entropy 21, no. 9: 910. https://doi.org/10.3390/e21090910