# High Capacity HEVC Video Hiding Algorithm Based on EMD Coded PU Partition Modes

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## Abstract

**:**

## 1. Introduction

## 2. EMD Encoding of PU Partition Modes

#### 2.1. Overview of Prediction Units in HEVC

#### 2.2. The Distribution of CUs with Different Sizes

## 3. The Proposed Hiding Algorithm

#### 3.1. EMD Coding of PU Partition Mode

#### 3.2. Information Hiding Algorithm

Algorithm 1. The embedding algorithm for one S-tuple group of 16 × 16 CUs with S = 3 |

Input: The 3-tuple 16 × 16 CU group array $\mathit{P}\text{}=\text{}\left({p}_{1},{p}_{2},\text{}{p}_{3}\right)$, where ${p}_{i}\text{}$represents the mapping integer of PU partition mode in the $i\mathrm{th}$ 16 × 16 CU decided by HEVC according to Table 1.Hidden base 7 data $\mathit{d}$; |

Output: the modified 3-tuple 16 × 16 CU group array ${\mathit{P}}^{\prime}=\left({p}_{1}^{\prime},{p}_{2}^{\prime},{p}_{3}^{\prime}\right)$; |

1. $P\prime =P$ |

2. $f\text{}={p}_{1}^{\prime}+2\times {p}_{2}^{\prime}+3\text{}\times {p}_{3}^{\prime}$ |

3. if $\left(f\text{}\%\text{}7\right)\text{}+\text{}1\text{}==\text{}d$ then |

4. ${p}_{1}^{\prime}=\text{}{p}_{1}^{\prime}+1$ |

5. else if $\left(f\text{}\%\text{}7\right)\text{}+\text{}2\text{}==\text{}d\text{}$ then |

6. ${p}_{2}^{\prime}=\text{}{p}_{2}^{\prime}+1$ |

7. else if $\left(f\text{}\%\text{}7\right)\text{}+\text{}3\text{}==\text{}d$ then |

8. ${p}_{3}^{\prime}=\text{}{p}_{3}^{\prime}+1$ |

9. else if $\left(f\text{}\%\text{}7\right)-\text{}1\text{}==\text{}d$ then |

10. ${p}_{1}^{\prime}=\text{}{p}_{1}^{\prime}-1$ |

11. else if $\left(f\text{}\%\text{}7\right)-\text{}2\text{}==\text{}d$ then |

12. ${p}_{2}^{\prime}=\text{}{p}_{2}^{\prime}-1$ |

13. else if $\left(f\text{}\%\text{}7\right)-\text{}3==d$ then |

14. ${p}_{3}^{\prime}=\text{}{p}_{3}^{\prime}-1$ |

15. end if |

Algorithm 2. The embedding algorithm for one S-tuple group of 8 × 8 CUs with S = 1 |

Input: The 1-tuple 8 × 8 CU group array $\mathit{P}\text{}=\text{}\left({p}_{1}\right)$, where ${p}_{1}\text{}$represents the mapping integer of the PU partition mode in this 8 × 8 CU decided by HEVC according to Table 2.Hidden base 3 data $\mathit{d}$; |

Output: the modified 1-tuple 8 × 8 CU group array ${\mathit{P}}^{\prime}=\left({p}_{1}^{\prime}\right)$; |

1. $P\prime =P$ |

2. $f={p}_{1}^{\prime}$ |

3. if $\left(f\text{}\%\text{}3\right)+1==d$ then |

4. ${p}_{1}^{\prime}={p}_{1}^{\prime}+1$ |

5. else if $\left(f\text{}\%\text{}3\right)-1==d$ then |

6. ${p}_{1}^{\prime}={p}_{1}^{\prime}-1$ |

7. end if |

## 4. Experimental Results

#### 4.1. Configuration

#### 4.2. Performance Evaluation

#### 4.2.1. Subjective Visual Quality

#### 4.2.2. Objective Performance

#### 4.2.3. Comparative Analysis

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 4.**Code units (CU) structures and PU partition modes of the example slice. (

**a**) is from ParkScene 1920 × 1080 and (

**b**) is from Keiba 832 × 480.

**Figure 5.**The distribution of CUs with different sizes. (

**a**) CU distribution under high resolution; (

**b**) CU distribution under low resolution.

**Figure 6.**Magnified coding tree units (CTU) in the bottom-right corner from Figure 4a.

**Figure 8.**Subjective performance evaluation of the second P-slices from: (

**a**) ParkScene 1920 × 1080; (

**b**) Keiba 832 × 480. The clean slices without embedded information are laid on the first line, and slices with hidden information are placed in the second line.

**Figure 9.**Comparison of distortion (RD) with Y. Yang’s paper ([33]): (

**a**) RD of BasketballDrive 1920 × 1080, Kimono 1920 × 1080 and Tennis 1920 × 1080; (

**b**) RD of ChinaSpeed 1024 × 768, Keiba 832 × 480 and PartyScene 832 × 480.

**Figure 10.**Comparison of capacity (RC) with [33]: (

**a**) RC of BasketballDrive 1920 × 1080, Kimono 1920 × 1080 and Tennis 1920 × 1080; (

**b**) RC of ChinaSpeed 1024 × 768, Keiba 832 × 480 and PartyScene 832 × 480.

**Table 1.**Mapping of PU partition modes in $16\times 16$, $32\times 32$, and$\text{}64\times 64$ CUs.

Modes | $2N\times 2N$ | $N\times N$ | $N\times 2N$ | $2N\times N$ | $nL\times 2N$ | $nR\times 2N$ | $2N\times nU$ | $2N\times nD$ |

Integers | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |

Modes | $8\times 8$ | $4\times 4$ | $4\times 8$ | $8\times 4$ |

Integers | 0 | 1 | 2 | 3 |

**Table 3.**The peak signal-to-noise ratio (PSNR), bit rate increasing (BRI) and capacity of the proposed algorithm with different quantization parameters (QPs).

Sequence | QP | PSNR(Clean) | PSNR(Hiding) | BRI | Capacity |
---|---|---|---|---|---|

BasketballDrive | 26 | 39.9836 | 39.9576 | 0.0209 | 2252 |

1920 × 1080 | 32 | 38.1135 | 38.0798 | 0.0226 | 926 |

38 | 35.9492 | 35.9018 | 0.0063 | 350 | |

BQTerrace | 26 | 36.9362 | 36.9268 | 0.0148 | 7578 |

1920 × 1080 | 32 | 34.6276 | 34.6540 | 0.0059 | 977 |

38 | 32.1492 | 32.1668 | 0.0025 | 141 | |

Kimono | 26 | 41.0887 | 41.1022 | 0.0112 | 1702 |

1920 × 1080 | 32 | 38.3209 | 38.3373 | 0.0140 | 790 |

38 | 35.5277 | 35.5761 | 0.0150 | 313 | |

ParkScene | 26 | 38.9657 | 38.9486 | 0.0162 | 4783 |

1920 × 1080 | 32 | 36.1111 | 36.1024 | 0.0108 | 1396 |

38 | 33.4029 | 33.4146 | 0.0056 | 280 | |

Tennis | 26 | 40.5594 | 40.5679 | 0.0155 | 3226 |

1920 × 1080 | 32 | 38.0411 | 38.0633 | 0.0110 | 1254 |

38 | 35.5259 | 35.5689 | 0.0022 | 419 | |

ChinaSpeed | 26 | 41.2659 | 41.1669 | 0.0410 | 2656 |

1024 × 768 | 32 | 36.9406 | 36.8492 | 0.0272 | 1427 |

38 | 33.1107 | 33.0431 | 0.0143 | 651 | |

Keiba | 26 | 38.7105 | 38.8770 | −0.0191 | 1148 |

832 × 480 | 32 | 35.5753 | 35.7236 | −0.0165 | 601 |

38 | 32.6737 | 32.8271 | −0.0330 | 199 | |

Racehorses | 26 | 37.0262 | 36.9092 | 0.0462 | 2558 |

832 × 480 | 32 | 33.6613 | 33.5330 | 0.0392 | 1282 |

38 | 30.5866 | 30.5369 | 0.0399 | 547 | |

PartyScene | 26 | 36.5585 | 36.5190 | −0.0368 | 2032 |

832 × 480 | 32 | 32.6259 | 32.5839 | −0.0153 | 1070 |

38 | 28.9680 | 28.9322 | −0.0069 | 243 |

Sequence | PSNR(Hiding) | PSNR (Ref. [32]) | Capacity | Capacity (Ref. [32]) |
---|---|---|---|---|

BasketballDrive | 39.9576 | 40.1833 | 2252 | 82 |

1920 × 1080 | ||||

BQTerrace | 36.9268 | 37.6133 | 7578 | 26 |

1920 × 1080 | ||||

Kimono | 41.1022 | 39.7700 | 1702 | 80 |

1920 × 1080 | ||||

ParkScene | 38.9486 | 37.8867 | 4783 | 62 |

1920 × 1080 | ||||

Tennis | 40.5679 | 40.0667 | 3226 | 108 |

1920 × 1080 | ||||

ChinaSpeed | 41.1669 | 38.4333 | 2656 | 84 |

1024 × 768 | ||||

Keiba | 38.8770 | 38.9333 | 1148 | 26 |

832 × 480 | ||||

Racehorses | 36.9092 | 35.5000 | 2558 | 118 |

832 × 480 | ||||

PartyScene | 36.5190 | 34.0667 | 2032 | 78 |

832 × 480 |

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## Share and Cite

**MDPI and ACS Style**

Li, Z.; Meng, L.; Jiang, X.; Li, Z.
High Capacity HEVC Video Hiding Algorithm Based on EMD Coded PU Partition Modes. *Symmetry* **2019**, *11*, 1015.
https://doi.org/10.3390/sym11081015

**AMA Style**

Li Z, Meng L, Jiang X, Li Z.
High Capacity HEVC Video Hiding Algorithm Based on EMD Coded PU Partition Modes. *Symmetry*. 2019; 11(8):1015.
https://doi.org/10.3390/sym11081015

**Chicago/Turabian Style**

Li, Zhonghao, Laijin Meng, Xinghao Jiang, and Zhaohong Li.
2019. "High Capacity HEVC Video Hiding Algorithm Based on EMD Coded PU Partition Modes" *Symmetry* 11, no. 8: 1015.
https://doi.org/10.3390/sym11081015