CN112312141B - HEVC video steganography method based on pixel adaptive compensation - Google Patents

HEVC video steganography method based on pixel adaptive compensation Download PDF

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CN112312141B
CN112312141B CN202010824103.5A CN202010824103A CN112312141B CN 112312141 B CN112312141 B CN 112312141B CN 202010824103 A CN202010824103 A CN 202010824103A CN 112312141 B CN112312141 B CN 112312141B
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姚远志
崔亚兵
俞能海
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University of Science and Technology of China USTC
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/80—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
    • H04N19/82—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation involving filtering within a prediction loop
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
    • H04N19/51—Motion estimation or motion compensation
    • H04N19/567—Motion estimation based on rate distortion criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
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Abstract

The invention discloses an HEVC video steganography method based on pixel adaptive compensation, which is used for designing a reasonable embedding cost function for a pixel compensation value and modeling load embedding into an optimization problem of minimizing the embedding cost of the pixel compensation value. The pixel compensation value embedding cost function considers two factors of pixel rate distortion cost fluctuation and pixel statistical distribution characteristics. The video steganography method has the self-adaptive load distribution capability in the pixel compensation value, and ensures that the dense-loaded video has higher anti-detection performance and video coding quality.

Description

HEVC video steganography method based on pixel adaptive compensation
Technical Field
The invention relates to the technical field of information hiding and video coding, in particular to an HEVC video steganography method based on pixel adaptive compensation.
Background
Video steganography is a covert communication mode taking video as a carrier, and plays an important role in privacy protection facing the Internet.
The pixel adaptive compensation is a loop filtering technology newly introduced in High Efficiency Video Coding (HEVC), and aims to further improve the quality of decoded and reconstructed video. However, there is currently no HEVC video steganography method that utilizes pixel adaptive compensation techniques.
Disclosure of Invention
The invention aims to provide an HEVC video steganography method based on pixel adaptive compensation, which has adaptive load distribution capability in a pixel compensation value and ensures that a dense-loaded video has higher anti-detection performance and video coding quality.
The purpose of the invention is realized by the following technical scheme:
an HEVC video steganography method based on pixel adaptive compensation comprises the following steps:
partially encoding the video to obtain a carrier pixel compensation value sequence, and calculating the embedding cost of each pixel compensation value;
embedding a load in the carrier pixel compensation value sequence and minimizing the embedding cost of the video according to the calculated embedding cost of each pixel compensation value to obtain a dense pixel compensation value sequence;
a video encoded bitstream is generated using the sequence of secret pixel compensation values.
According to the technical scheme provided by the invention, the load embedding is modeled into the optimization problem of minimizing the embedding cost of the pixel compensation value by designing a reasonable embedding cost function for the pixel compensation value. The pixel compensation value embedding cost function considers two factors of pixel rate distortion cost fluctuation and pixel statistical distribution characteristics. The video steganography method has the self-adaptive load distribution capability in the pixel compensation value, and ensures that the dense-loaded video has higher anti-detection performance and video coding quality.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of an HEVC video steganography method based on pixel adaptive compensation according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of four direction modes for determining the type of edge compensation according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a receiver operation characteristic curve of the video steganography method and a comparison video steganography method provided by the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides an HEVC video steganography method based on pixel adaptive compensation, which mainly comprises the following steps of:
and step 11, partially encoding the video to obtain a carrier pixel compensation value sequence, and calculating the embedding cost of each pixel compensation value.
The preferred embodiment of this step is as follows:
1) partially encoding a video to obtain a sequence of carrier pixel compensation values x ═ x (x)1,x2,...,xn) Wherein x isiThe ith carrier pixel compensation value is calculated by a pixel self-adaptive compensation technology in the video, and n is the total number of the carrier pixel compensation values. In specific implementation, only a part of encoding steps need to be performed on the video to obtain a corresponding carrier pixel compensation value sequence.
2) Calculating pixel rate distortion cost fluctuations based on individual pixel compensation values
Figure BDA0002635524150000021
And pixel statistical distribution characteristics
Figure BDA0002635524150000022
3) Calculating an embedding cost ρ of a carrier pixel compensation valuei(xi,yi)：
Figure BDA0002635524150000023
Wherein, yiIs the ith dense pixel compensation value.
In the embodiment of the invention, the embedding cost of the carrier pixel compensation value takes the pixel rate distortion cost fluctuation into consideration
Figure BDA0002635524150000031
And pixel statistical distribution characteristics
Figure BDA0002635524150000032
These two factors, provided below
Figure BDA0002635524150000033
And
Figure BDA0002635524150000034
the preferred calculation of (c).
A. Fluctuation of pixel rate distortion cost
Figure BDA0002635524150000035
The preferred calculation of (c).
Order SiFor the set of pixels of the ith coding tree block in the video, the original pixel skAnd decoding the reconstructed pixel pkMay be expressed as:
Figure BDA0002635524150000036
prior to the load embedding, the original pixel skThe distortion with the pixel-adaptively compensated filtered pixel can be expressed as:
Figure BDA0002635524150000037
before the load embedding, the pixel rate distortion cost difference value after the pixel adaptive compensation can be expressed as:
Figure BDA0002635524150000038
wherein N isiIs a set of pixels SiNumber of pixels in, EiIs the original pixel skAnd decoding the reconstructed pixel pkThe sum of the differences of (a) may be expressed as:
Figure BDA0002635524150000039
thus, the pixel set SiThe rate-distortion cost difference before load embedding can be expressed as:
ΔJ＝ΔD+λSAOR
wherein λ isSAOR is the bit number required by the self-adaptive compensation side information of the coding pixel;
after the load embedding, the original pixel skThe distortion with the pixel-adaptively compensated filtered pixel can be expressed as:
Figure BDA00026355241500000310
wherein, deltaiE { -1,0,1} is a perturbation to the carrier pixel compensation value due to load embedding;
the pixel rate distortion cost fluctuates
Figure BDA00026355241500000311
Expressed as:
Figure BDA00026355241500000312
wherein,. DELTA.J 'is D'postCalculated set of pixels SiRate distortion cost difference after load embedding.
B. Statistical distribution characteristic of pixels
Figure BDA00026355241500000313
The preferred calculation of (c).
In HEVC video coding, there are two adaptive pixel compensation methods, edge compensation and interval compensation.
Taking edge compensation as an example, four directional modes for determining the type of edge compensation are shown in fig. 2. In the four directional patterns shown in fig. 2, the directional pattern used for edge compensation is determined by comparing the numerical relationship between the current pixel c and the adjacent pixels a and b, which are respectively located at the left and right sides of the current pixel c, or at the upper and lower ends, or at the upper and lower left sides, or at the upper and lower right sides, as shown in fig. 2.
Calculating based on directional patterns in pixel adaptive compensationSet of pixels SiIntermediate decoding reconstructed pixel pkSpatial correlation u ofkThe calculation process is as follows: first, make ukIs initially ukAnd (3) axle mixing No. 1. Secondly, calculating the value of (a + b)/2 and comparing the value with the current pixel c for each direction mode; if c ≠ (a + b)/2, for ukPerforming an add-1 operation, i.e. uk←uk+1. Otherwise ukKeeping the same; when the comparison operation is executed in all four direction modes, the decoding reconstruction pixel p can be obtainedkSpatial correlation u ofk。
Then, the statistical distribution characteristic of the pixel is calculated by the following formula
Figure BDA0002635524150000041
Figure BDA0002635524150000042
Where α is the regulating parameter, viExpressed as:
Figure BDA0002635524150000043
wherein N isiIs a set of pixels SiThe number of pixels in (1).
For the decoded reconstructed pixels using the interval compensation, the above-described pixel statistical distribution characteristic calculation method can be used as well.
Finally, the embedding cost ρ of the carrier pixel compensation valuesi(xi,yi) Can be expressed as:
Figure BDA0002635524150000044
and step 12, embedding a load in the carrier pixel compensation value sequence and minimizing the embedding cost of the video according to the calculated embedding cost of each pixel compensation value to obtain a carrier density pixel compensation value sequence.
In the embodiment of the invention, according to the length m of the load to be embedded in the video and the calculated embedding cost of each pixel compensation value, the data embedding code STC is used for embedding the load in the carrier pixel compensation value sequence and minimizing the embedding cost of the video.
And step 13, generating a video coding bit stream by using the secret-carrying pixel compensation value sequence.
In the embodiment of the invention, the secret-carrying pixel compensation value sequence y is used as (y)1,y2,...,yn) And coding the video to generate a video coding bit stream to complete video steganography.
The embedded load can then also be extracted as follows: decoding the video coding bit stream to obtain a secret-carrying pixel compensation value sequence y, and extracting an embedded load from the secret-carrying pixel compensation value sequence y; specifically, the method comprises the following steps: determining a check matrix of the data embedding code STC according to the load length embedded in the least significant bit of all the secret pixel compensation values and the load length embedded in the next least significant bit, forming a secret vector by the least significant bit and the next least significant bit of all the secret pixel compensation values, multiplying the check matrix and the secret vector to obtain a load vector, and finishing load extraction.
According to the scheme provided by the embodiment of the invention, the load embedding is modeled into the optimization problem of minimizing the embedding cost of the pixel compensation value by designing a reasonable embedding cost function for the pixel compensation value. The pixel compensation value embedding cost function considers two factors of pixel rate distortion cost fluctuation and pixel statistical distribution characteristics. The video steganography method has the self-adaptive load distribution capability in the pixel compensation value, and ensures that the dense-loaded video has higher anti-detection performance and video coding quality.
In order to test the anti-detection performance of the HEVC video steganography method based on pixel adaptive compensation, provided by the invention, a comparison experiment is carried out. In a comparison experiment, the video steganography method provided by the invention is marked as deployed, and a comparison video steganography method is selected from the prior art and is marked as Baseline.
In contrast experiments, the carrier pixels are compensatedEmbedding cost ρi(xi,yi) The adjustment parameter a in (2) is set to 0.60. The embedding cost of the carrier pixel compensation value in the video steganography method is set to be a constant larger than zero, and the rest settings are the same as those of the video steganography method provided by the invention. And selecting the SPAM characteristics with 686 dimension for steganalysis. In a comparison experiment, the video steganography method provided by the invention is tested by using an HEVC video encoder x265 as an experiment platform. The relative load embedding rate is expressed by using the average embedded bit number per coding tree unit, and the unit is bits/CTU.
The anti-detection performance is an important evaluation index of the video steganography method. The anti-detection performance was measured in a comparative experiment using a receiver operating characteristic curve drawn using an ensemble classifier, in which the relative load embedding rates r were set to 0.25bits/CTU, 0.50bits/CTU and 0.75bits/CTU, respectively. As shown in fig. 3, the receiver operation characteristic curves of the video steganography method and the comparative video steganography method provided by the present invention are shown. In the receiver operation characteristic curve, the smaller the area under the curve, AUC, indicates that the video steganography method has higher anti-detection performance, and the diagonal line in fig. 3 corresponds to AUC of 0.5.
Video coding quality is another important evaluation index of video steganography methods. Video coding quality is measured by the visual quality of the secret-carrying video and the coding efficiency of the secret-carrying video. A commonly used evaluation index of the visual quality of the secret-carrying video is a peak signal-to-noise ratio (PSNR) (unit: dB). Carrier video peak signal-to-noise ratio (PSNR)cCalculated by comparing the original video sequence with the carrier video sequence. Let Δ PSNR be the luminance component peak signal-to-noise ratio difference between the dense video and the carrier video. The bit rate increase ratio is used to measure the efficiency of the coding of the dense video. The bit rate increase ratio can be expressed as:
Figure BDA0002635524150000051
wherein, BRsAnd BRcRepresenting the carrier video bit rate and the carrier video bit rate, respectively. Based on the video steganography method provided by the invention, a test video library consisting of 18 classical video sequences is subjected toAnd (5) performing steganography testing. The 18 CIF format video sequences are partitioned into non-overlapping sub-sequences of length 60 frames, with the number of sub-sequences being 181. The detailed parameters of the video sequence are shown in table 1.
Figure BDA0002635524150000061
TABLE 1 testing video sequence parameters
The video coding quality results obtained based on the video steganography method provided by the invention are shown in table 2, and it can be seen that the video steganography method provided by the invention can ensure that the dense-loaded video has higher video coding quality.
Figure BDA0002635524150000062
Table 2 video coding quality of the video steganography method proposed by the present invention
Through the above description of the embodiments, it is clear to those skilled in the art that the above embodiments can be implemented by software, and can also be implemented by software plus a necessary general hardware platform. With this understanding, the technical solutions of the embodiments can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods according to the embodiments of the present invention.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (4)

1. An HEVC video steganography method based on pixel adaptive compensation is characterized by comprising the following steps:
partially encoding the video to obtain a carrier pixel compensation value sequence, and calculating the embedding cost of each carrier pixel compensation value;
embedding a load in the carrier pixel compensation value sequence and minimizing the embedding cost of the video according to the calculated embedding cost of each carrier pixel compensation value to obtain a dense pixel compensation value sequence;
generating a video coding bit stream by using the secret-carrying pixel compensation value sequence;
wherein the calculating the embedding cost of each carrier pixel compensation value comprises:
recording the volume pixel compensation value sequence as x ═ x1,x2,...,xn) Wherein x isiCalculating the ith carrier pixel compensation value in the video through a pixel self-adaptive compensation technology, wherein n is the total number of the carrier pixel compensation values;
first, based on each carrier pixel compensation value, calculating pixel rate distortion cost fluctuation
Figure FDA0003068640150000011
And pixel statistical distribution characteristics
Figure FDA0003068640150000012
Then, the embedding cost rho of the carrier pixel compensation value is calculatedi(xi,yi)：
Figure FDA0003068640150000013
Wherein, yiIs the ith dense pixel compensation value;
fluctuation of pixel rate distortion cost
Figure FDA0003068640150000014
The calculation method comprises the following steps:
order SiTo look atSet of pixels of the ith coding tree block in frequency, then the original pixel skAnd decoding the reconstructed pixel pkIs expressed as:
Figure FDA0003068640150000015
prior to the load embedding, the original pixel skThe distortion with the pixel-adaptively compensated filtered pixel is expressed as:
Figure FDA0003068640150000016
before load embedding, the pixel rate distortion cost difference value after pixel adaptive compensation is expressed as:
Figure FDA0003068640150000017
wherein N isiIs a set of pixels SiNumber of pixels in, EiIs the original pixel skAnd decoding the reconstructed pixel pkIs given as:
Figure FDA0003068640150000018
set of pixels SiThe rate-distortion cost difference before load embedding is expressed as:
ΔJ＝ΔD+λSAOR
wherein λ isSAOR is the bit number required by the self-adaptive compensation side information of the coding pixel;
after the load embedding, the original pixel skThe distortion with the pixel-adaptively compensated filtered pixel is expressed as:
Figure FDA0003068640150000021
wherein, deltaiE { -1,0,1} is a perturbation to the carrier pixel compensation value due to load embedding;
the pixel rate distortion cost fluctuates
Figure FDA0003068640150000022
Expressed as:
Figure FDA0003068640150000023
wherein,. DELTA.J 'is D'postCalculated set of pixels SiRate-distortion cost difference after load embedding;
statistical distribution characteristic of pixels
Figure FDA0003068640150000024
The calculation method comprises the following steps:
order SiFor a set of pixels of the ith coding tree block in the video, a set S of pixels is calculated based on the directional pattern in the pixel adaptive compensationiIntermediate decoding reconstructed pixel pkSpatial correlation u ofk(ii) a The direction mode is determined by comparing the numerical relationship between the current pixel c and the adjacent pixels a and b, wherein the adjacent pixels a and b are respectively positioned at the left side and the right side of the current pixel c, or respectively positioned at the upper end and the lower end, or respectively positioned at the upper left side and the lower right side, or respectively positioned at the upper right side and the lower left side;
spatial correlation ukThe calculation process is as follows: let ukIs initially ukAxle 300, 1; for each directional mode, calculating the value of (a + b)/2 and comparing with the current pixel c; if c ≠ (a + b)/2, for ukPerforming an add-1 operation, i.e. uk←uk+1, otherwise ukKeeping the same; when the comparison operation is executed in all four direction modes, the decoding reconstruction pixel p can be obtainedkSpatial correlation u ofk；
Calculating the pixel statistic score by the following formulaCharacteristics of cloth
Figure FDA0003068640150000025
Figure FDA0003068640150000026
Where α is the regulating parameter, viExpressed as:
Figure FDA0003068640150000027
wherein N isiIs a set of pixels SiThe number of pixels in (1).
2. The HEVC video steganography method based on pixel adaptive compensation as claimed in claim 1, wherein the data embedding code STC is used to embed the payload in the carrier pixel compensation value sequence and minimize the video embedding cost according to the payload length m required to be embedded in the video and the calculated embedding cost of each carrier pixel compensation value.
3. The HEVC video steganography method based on pixel adaptive compensation as recited in claim 1, wherein a video is encoded by using a dense pixel compensation value sequence y to generate a video coding bit stream, thereby completing video steganography.
4. The HEVC video steganography method based on pixel adaptive compensation as claimed in claim 1, wherein the method further comprises extracting the embedded payload by:
decoding the video coding bit stream to obtain a secret-carrying pixel compensation value sequence y;
and extracting the embedded load from the dense pixel compensation value sequence y: determining a check matrix of the data embedding code STC according to the load length embedded in the least significant bit of all the secret pixel compensation values and the load length embedded in the next least significant bit, forming a secret vector by the least significant bit and the next least significant bit of all the secret pixel compensation values, multiplying the check matrix and the secret vector to obtain a load vector, and finishing load extraction.
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