CN111325650A - Reversible watermarking method - Google Patents

Reversible watermarking method Download PDF

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CN111325650A
CN111325650A CN201811531852.8A CN201811531852A CN111325650A CN 111325650 A CN111325650 A CN 111325650A CN 201811531852 A CN201811531852 A CN 201811531852A CN 111325650 A CN111325650 A CN 111325650A
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channel
information
embedded
image
reversible watermarking
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常杰
丁峰
王员根
杨建权
朱国普
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Shenzhen Institute of Advanced Technology of CAS
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Shenzhen Institute of Advanced Technology of CAS
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/0021—Image watermarking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2201/00—General purpose image data processing
    • G06T2201/005—Image watermarking
    • G06T2201/0203—Image watermarking whereby the image with embedded watermark is reverted to the original condition before embedding, e.g. lossless, distortion-free or invertible watermarking

Abstract

The application belongs to the technical field of image processing, and particularly relates to a reversible watermarking method. The prior art methods also distort the mask after the watermark is embedded. The image obtained by performing the gray-scale conversion on the original image may be regarded as a noise image and may not be used. The application provides a reversible watermarking method, which comprises the following steps: step 1: preprocessing the image, and converting the color image into a gray image; step 2: embedding information into a first channel and a second channel of a color image; and step 3: and adjusting the offset of the first channel and the second channel after the information is embedded through the third channel. The method can realize that the image distortion degree is reduced after the information is embedded, and the gray value of the image is unchanged, and the method is used for processing subsequent color images, such as making reading materials for color blindness people.

Description

Reversible watermarking method
Technical Field
The application belongs to the technical field of image processing, and particularly relates to a reversible watermarking method.
Background
In recent years, with the rapid development of internet technology and the popularization of digital devices such as mobile phones and computers, digital multimedia including images, texts, videos, audios and the like as information carriers are gradually recognized and accepted by the public. At the same time, however, these multimedia information are easily tampered, copied and spread maliciously by an illegal person, and the interests of the property owners are seriously damaged, and in addition, copyright protection and information security are increasingly emphasized. The traditional encryption technology is to protect the content during the transmission of data by a sender, but after the data is received and decrypted, the data is very likely to be illegally copied and falsified. The information hiding technology is developed according to the defects in copyright protection and information security of the traditional cryptography. Reversible watermarking is an important method of information hiding. The reversible watermark refers to a special watermark which can be completely recovered by embedding a carrier after the watermark is extracted. Compared with the traditional watermark, the reversible watermark has stricter requirements on the lossless recovery of the embedded carrier, is generally used for the distortion-free protection of important images, and has important application value on military images and medical images.
The current reversible watermarking method is mostly realized based on gray level images. At present, color images become mainstream, and reversible watermarks based on gray level images cannot meet the requirements of people. The existing color image embedding increases the embedding capacity by establishing a sharp prediction error histogram, and reduces the total distortion degree. These methods can still leave the bunker of embedded watermarks with false positives. The image obtained by performing the gray-scale conversion on the original image may be regarded as a noise image and may not be used.
Disclosure of Invention
1. Technical problem to be solved
The method based on the reversible watermark is mostly realized based on gray level images. At present, color images become mainstream, and reversible watermarks based on gray level images cannot meet the requirements of people. The existing color image embedding increases the embedding capacity by establishing a sharp prediction error histogram, and reduces the total distortion degree. These methods still distort the mask after the watermark is embedded. The method has the advantages that the image obtained by performing gray scale conversion on the original image can be regarded as a noise image and cannot be used, and the reversible watermarking method is provided.
2. Technical scheme
In order to achieve the above object, the present application provides a reversible watermarking method, comprising the steps of:
step 1: preprocessing the image, and converting the color image into a gray image;
step 2: embedding information into a first channel and a second channel of a color image;
and step 3: and adjusting the offset of the first channel and the second channel after the information is embedded through the third channel.
Optionally, the step 2 includes the following steps:
step 201: acquiring an error correction value;
step 202: predicting a first channel pixel value and an error, and predicting a second channel pixel value and an error;
step 203: the location of the embedded information is selected and the information is embedded.
Optionally, the prediction method in step 202 includes gradient adjustment prediction or median edge detection.
Optionally, the position in step 203 is a position in the grayscale image where the local variance is smaller than the standard variance.
Optionally, in step 2, watermark information is embedded into the red channel, and an error correction value is embedded into the blue channel.
Optionally, the embedded watermark information is embedded into the red channel based on a raster scan order.
Optionally, the method further includes embedding auxiliary information, where the auxiliary information is embedded in the least significant bits of the blue channel, and the auxiliary information includes a determination threshold of the local variance and a length of the watermark information.
Optionally, in step 3, the offset of the red channel and the blue channel after embedding the information is adjusted by the green channel.
Optionally, the method further comprises the steps of:
and 4, step 4: extracting the auxiliary information of the second channel processed in the step 3;
and 5: after extracting the auxiliary information of the second channel, determining the position of the first channel for embedding the watermark information;
step 6: extracting embedded watermark information;
and 7: recovering the third channel after extracting the embedded information;
and 8: and repeating the step 6 and the step 7 to obtain the embedded watermark information and the carrier.
Optionally, the extracting of the embedded watermark information in step 6 is based on the inverse raster order and adjusts the prediction method according to the gradient.
3. Advantageous effects
Compared with the prior art, the reversible watermarking method has the beneficial effects that:
the reversible watermarking method provided by the application aims at a color image, and firstly, the color image is converted into a gray image; second, embedding information into the red and blue channels of the color image (R, G, B); finally, the green channel is used for adjusting the offset of the red channel and the blue channel after the information is embedded, so that the image fidelity is reduced after the information is embedded, the gray value of the image is unchanged, and the image is used for processing subsequent color images, such as making reading materials for color blindness people.
Drawings
FIG. 1 is a schematic diagram of the present application for predicting pixel values based on a gradient adjustment prediction method;
fig. 2 is a schematic diagram illustrating a process of embedding watermark information in the reversible watermarking method of the present application;
fig. 3 is a schematic diagram illustrating a process of extracting watermark information in the reversible watermarking method of the present application.
Detailed Description
Hereinafter, specific embodiments of the present application will be described in detail with reference to the accompanying drawings, and it will be apparent to those skilled in the art from this detailed description that the present application can be practiced. Features from different embodiments may be combined to yield new embodiments, or certain features may be substituted for certain embodiments to yield yet further preferred embodiments, without departing from the principles of the present application.
The prediction of color image pixel values is realized by using a Bayer color filter array method, and the proposed algorithm uses spectral spatial correlation to realize small prediction errors in the color difference domain to embed hidden data. Since such prediction errors tend to follow a laplacian distribution with relatively small variance, the proposed algorithm achieves high embedding capacity and good localization map quality.
Referring to fig. 1 to 3, the present application provides a reversible watermarking method, including the following steps:
step 1: preprocessing the image, and converting the color image into a gray image;
step 2: embedding information into a first channel and a second channel of a color image;
and step 3: and adjusting the offset of the first channel and the second channel after the information is embedded through the third channel.
The first channel, the second channel, and the third channel in this application denote a red channel, a blue channel, and a green channel, that is, the first channel, the second channel, and the third channel are different in color. In the application, the first channel selects the red channel, the second channel selects the blue channel, and the third channel selects the green channel. In this application, the red channel is referred to as the R channel for short, the blue channel is referred to as the B channel for short, and the green channel is referred to as the G channel for short.
Gray scale conversion
Reading an original image I ═ { r, g, b }, performing gradation conversion on the original image, and converting the original image into a gradation image v ═ f }v(r, g, b), where a classical grey map conversion algorithm is used:
Figure BDA0001905848560000031
wherein, R, G, B respectively represent pixel values of R, G, B channels.
Optionally, the step 2 includes the following steps:
step 201: acquiring an error correction value;
step 202: predicting a first channel pixel value and an error, and predicting a second channel pixel value and an error;
step 203: the location of the embedded information is selected and the information is embedded.
Optionally, the prediction method in step 202 includes gradient adjustment prediction or median edge detection.
Optionally, the position in step 203 is a position in the grayscale image where the local variance is smaller than the standard variance.
Optionally, in step 2, watermark information is embedded into the red channel, and an error correction value is embedded into the blue channel.
Optionally, the embedded watermark information is embedded into the red channel based on a raster scan order.
Obtaining an error correction value
The method is to embed information into R, B channels, and then adjust the offset through the G channel to keep the gray value of the whole image unchanged.
In the watermark information extraction process, the pixel value of the G channel
Figure BDA0001905848560000041
The acquisition is obtained by the following method
Figure BDA0001905848560000042
Due to the rounding of the above function, the actual pixel value g resultsi，jAnd
Figure BDA0001905848560000043
there is an error, which is typically 1 or 0. To ensure that the embedding and extracting process of the watermark information is reversible, a correction error is defined
Figure BDA0001905848560000044
Is composed of
Figure BDA0001905848560000045
R, B channel prediction based on GAP method
Predicting a pixel value R at { ij } position in R channel based on GAPi，j：
Figure BDA0001905848560000046
Wherein Δ v ═ ri，j+1-ri+1，j+1|+|ri+1，j-1-ri+2，j-1|+|ri+1，j-ri+2，j|,
ΔH＝|ri，j+1-ri，j+2|+|ri+1，j-1-ri+1，j|+|ri+1，j-ri+1，j+1|
Figure BDA0001905848560000047
Δ＝ΔV-ΔH
Prediction error
Figure BDA0001905848560000048
Obtaining the predicted value of the B channel in the same way
Figure BDA0001905848560000049
And prediction error
Figure BDA00019058485600000410
Selecting location embedded information
Generally, the distortion degree is small after the information is embedded at a position with small error. And a location with a small error, typically its local variance, is small. In order to be able to select a position where the local variance of the color image is small, a position having a small local variance in the image is selected based on the grayscale image. Local variance ρi，jThe calculation method of (a) is as follows:
Figure BDA0001905848560000051
wherein the content of the first and second substances,
Figure BDA0001905848560000052
Figure BDA0001905848560000053
when rhoi，j＜ρTThen that location can be used to embed the pixel.
In accordance with past experience, ρ is setT＝2。
Embedding watermark information and error correction values
The method and the device ensure that the gray value of the image obtained after the information is embedded into the image is kept unchanged, therefore, the method and the device embed the watermark information into the R channel based on the raster (raster order) scanning sequence, embed the error correction value information into the B channel, and adjust the offset generated by the whole image by adopting the G channel.
Obtained according to the formula (1)
Figure BDA0001905848560000054
i is watermark information.
Figure BDA0001905848560000055
Figure BDA0001905848560000056
To correct for errors.
Then at the { i, j } positions, the pixel values obtained after embedding the information are:
Figure BDA0001905848560000057
Figure BDA0001905848560000058
Figure BDA0001905848560000059
Figure BDA00019058485600000510
is the predicted pixel value at the i, j position in the R channel,
Figure BDA00019058485600000511
is a prediction error of R 'after embedding information in the R channel'i，jIs the pixel value of the R channel after embedding information, similarly,
Figure BDA00019058485600000512
b′i，jthe prediction value of the i, j position of the B channel, the prediction error after embedding the information and the pixel value after embedding the information are respectively. v. ofi，jIs the gray value of the gray map corresponding to the color image at the position i, j. g'i，jIs the pixel value of the G channel at the i, j position.
Optionally, the method further includes embedding auxiliary information, where the auxiliary information is embedded in the least significant bits of the blue channel, and the auxiliary information includes a determination threshold of the local variance and a length of the watermark information.
Embedding auxiliary information
In order to ensure that the watermark information can be completely and reversibly extracted, auxiliary information needs to be embedded. This side information is ρTLast error correction value
Figure BDA00019058485600000513
And the length L of the watermark information. Therefore, the total length of the embedded information is N, and N is L + 7. Wherein the auxiliary information occupies 7 bits, respectively rhoTOccupying 2bit storage, last error correction value
Figure BDA00019058485600000514
And 1bit storage is occupied, and L is occupied with 4bit storage. This part of information is stored using Least Significant Bits (LSBs) of the B channel, i.e., the LSBs of the B channel are replaced with auxiliary information. In order to ensure that the gray value of the image is unchanged before and after the information is embedded, 3 gray value invariable positions are selected in the B channel to ensure that the gray value is not changed
Figure BDA0001905848560000061
Therefore, the gray value of the image is unchanged before and after the image value is embedded.
Through the above steps, after the watermark information is embedded in the input image I ═ { r, g, b }, the image I ═ { r ', b', g } is obtained, and the gradation value of the entire image is unchanged.
Optionally, in step 3, the offset of the red channel and the blue channel after embedding the information is adjusted by the green channel.
Optionally, the method further comprises the steps of:
and 4, step 4: extracting the auxiliary information of the second channel processed in the step 3;
and 5: after extracting the auxiliary information of the second channel, determining the position of the first channel for embedding the watermark information;
step 6: extracting embedded watermark information;
and 7: recovering the third channel after extracting the embedded information;
and 8: and repeating the step 6 and the step 7 to obtain the embedded watermark information and the carrier.
Optionally, the extracting of the embedded watermark information in step 6 is based on the inverse raster order and adjusts the prediction method according to the gradient.
Extracting watermark information
(1) Extracting auxiliary information
Determining 3 gray value invariable positions in the B channel in I' according to formula (5), extracting LSB values of the 3 positions to obtain rhoT，
Figure BDA0001905848560000062
And L.
(2) Determining the location of embedded watermark information
The color image is converted to a gray image. Calculating local variance ρ in the gray-scale image based on the raster order and according to equation (4), and selecting L positions ρ < ρT. These L positions are denoted as { I'1，I′2，…，I′L}。
(3) Extracting embedded watermark information
From L 'to the pixels of these L positions'LInitially, a predicted value for the R, B channel is obtained based on the inverse raster order and according to the GAP prediction method
Figure BDA0001905848560000063
And prediction error
Figure BDA0001905848560000064
Figure BDA0001905848560000065
Figure BDA0001905848560000066
Figure BDA0001905848560000067
Where i is the embedded watermark information.
The same can be obtained
Figure BDA0001905848560000071
(4) Restore G channel
Auxiliary information obtained according to the step (1)
Figure BDA0001905848560000072
Judgment of
Figure BDA0001905848560000073
Whether or not it is 0. If 0, g equals g'. If not, then,
Figure BDA0001905848560000074
judgment of vLWhether or not equal to
Figure BDA0001905848560000075
If g ═ g '+ 1, otherwise, g ═ g' -1.
And (5) repeating the step (3) and the step (4) to obtain the embedded watermark information and the carrier.
The reversible watermarking method comprises two parts, wherein the first part is embedded watermark information, and the second part is extracted watermark information.
Reversible watermarking method based on prediction error expansion
Predicting the current pixel x by using the neighboring pixels according to the correlation of the neighboring pixels, thereby obtaining a predicted value
Figure BDA0001905848560000076
The prediction error P is then:
Figure BDA0001905848560000077
1-bit data i is embedded in the prediction error expansion, wherein i is 0 or 1, and the embedding mode is as follows:
p′＝2p+i (1)
the embedded pixel values are:
Figure BDA0001905848560000078
extracting the embedded information i as follows:
Figure BDA0001905848560000079
restore original prediction error and pixel values:
Figure BDA00019058485600000710
x＝x′-p-i
thus, the embedding and extraction of data can be realized.
Gradient-adjusted Prediction (GAP)
GAP is a simple adaptive prediction method, and has higher prediction accuracy compared with a classical median-edge detector (MED). For images at { i, j }Elemental value vi，jObtaining the predicted value
Figure RE-GDA0001973649110000079
Figure BDA0001905848560000081
Wherein, Deltav＝|vi，j+1-vi+1，j+1|+|vi+1，j-1-vi+2，j-1|+|vi+1，j-vi+2，j|,
ΔH＝|vi，j+1-vi，j+2|+|vi+1，j-1-vi+1，j|+|vi+1，j-vi+1，j+1|
Figure BDA0001905848560000082
Δ＝ΔV-ΔH
In the GAP prediction method used in the present application, a reversible watermarking technology based on prediction error expansion is a commonly used method in the reversible watermarking method, and currently, existing mature codes realize these functions. Therefore, the method is mainly based on the method, and only needs to judge the embeddable position, embed the watermark information and realize reversible extraction of the watermark information.
Grey versions of color images are widely used, such as black and white printing (electronic ink based book readers), making reading material for color blind people, and so on. For these applications it makes great sense to keep the gray values of the color images unchanged. The gray value of the image after the watermark is embedded is the same as the gray value of the image before the watermark is embedded.
The reversible watermarking method provided by the application aims at the color image and provides the reversible watermarking method. Firstly, converting a color image into a gray image; second, embedding information into the red and blue channels of the color image (R, G, B); finally, the green channel is used for adjusting the offset of the red channel and the blue channel after the information is embedded, so that the image fidelity is reduced after the information is embedded, the gray value of the image is ensured to be unchanged, and the method is used for processing subsequent color images, such as making reading materials for color blindness people.
Although the present application has been described above with reference to specific embodiments, those skilled in the art will recognize that many changes may be made in the configuration and details of the present application within the principles and scope of the present application. The scope of protection of the application is determined by the appended claims, and all changes that come within the meaning and range of equivalency of the technical features are intended to be embraced therein.

Claims (10)

1. A reversible watermarking method, characterized by: the method comprises the following steps:
step 1: preprocessing the image, and converting the color image into a gray image;
step 2: embedding information into a first channel and a second channel of a color image;
and step 3: and adjusting the offset of the first channel and the second channel after the information is embedded through the third channel.
2. A reversible watermarking method according to claim 1, characterized in that: the step 2 comprises the following steps:
step 201: acquiring an error correction value;
step 202: predicting a first channel pixel value and an error, and predicting a second channel pixel value and an error;
step 203: the location of the embedded information is selected and the information is embedded.
3. A reversible watermarking method according to claim 2, characterized in that: the prediction method in step 202 includes gradient adjustment prediction or median edge detection.
4. A reversible watermarking method according to claim 2, characterized in that: the position in step 203 is a position in the gray image where the local variance is smaller than the standard variance.
5. A reversible watermarking method according to claim 4, characterized in that: and (3) embedding watermark information into the red channel and embedding an error correction value into the blue channel in the step (2).
6. A reversible watermarking method according to claim 5, characterized in that: the embedded watermark information is embedded into the red channel based on a raster scan order.
7. A reversible watermarking method according to claim 5, characterized in that: the method further comprises embedding auxiliary information, wherein the auxiliary information is embedded into the least significant bit of the blue channel, and the auxiliary information comprises a judgment threshold value of the local variance and the length of the watermark information.
8. A reversible watermarking method according to claim 1, characterized in that: and 3, adjusting the offset of the red channel and the blue channel after the information is embedded through the green channel.
9. A reversible watermarking method according to claim 1, characterized in that: the method further comprises the steps of:
and 4, step 4: extracting the auxiliary information of the second channel processed in the step 3;
and 5: after extracting the auxiliary information of the second channel, determining the position of the first channel for embedding the watermark information;
step 6: extracting embedded watermark information;
and 7: recovering the third channel after extracting the embedded information;
and 8: and repeating the step 6 and the step 7 to obtain the embedded watermark information and the carrier.
10. A reversible watermarking method according to claim 9, wherein: and 6, extracting the embedded watermark information based on the inverse raster sequence and adjusting the prediction method according to the gradient.
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Application publication date: 20200623