CN109671010A - It is a kind of based on multiple two-dimensional histograms modification reversible information hide and extracting method - Google Patents
It is a kind of based on multiple two-dimensional histograms modification reversible information hide and extracting method Download PDFInfo
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- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2201/00—General purpose image data processing
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Abstract
The invention discloses a kind of reversible information hidden methods based on the modification of multiple two-dimensional histograms, including S1: gray level image is divided into mutually non-conterminous two set as unit of pixel pair；S2: predicting the pixel of pixel centering adjacent pixel using pixel, obtains prediction error, predicted composition error pair；S3: predicting error pair to each, calculates its Local Complexity, then be divided into 16 prediction errors to the identical set of number, construct 16 two-dimensional prediction histogram of error the Local Complexity of all prediction errors pair according to arranging from low to high；S4: selecting a mapping mode as all prediction errors pair of the prediction histogram from 8 mapping graphs being pre-designed, and the insertion of information is carried out according to corresponding mapping ruler.The present invention efficiently embedding information and can correctly can extract embedded information, nondestructively restore original image, with the visual quality for improving image after embedding information, i.e. Y-PSNR increase.
Description
Technical field
The present invention relates to field of multi-media information safety, are modified more particularly, to one kind based on multiple two-dimensional histograms
Reversible information hide and extracting method.
Background technique
Information hiding belongs to a kind of emerging information security technology, it is the mistake that information privacy is embedded into multimedia bearer
Journey, have extremely important theoretical research and practical application value, but some applications for example medical diagnosis, court put to the proof,
In artistic work, not only embedding information is needed to protect initial carrier, also wants nondestructively restore initial carrier.It is reversible
The purpose of Information Hiding Techniques is can be by initial carrier from containing Distortionless in close carrier, while can accurately extract secret
Confidential information, research are mainly used in secret communication, copyright protection, multimedia and distort evidence obtaining, Cloud Server certification and management etc.
Numerous areas.
Image information, which is hidden, has been developed many years as an important branch of Information hiding, also occurs both at home and abroad
The a variety of information concealing methods for being used for image, therefore be of great significance to the innovation and optimization of its hidden algorithm.
Summary of the invention
The present invention in order to overcome at least one of the drawbacks of the prior art described above, provides a kind of based on multiple two-dimentional histograms
The reversible information of figure modification hides and extracting method.
The present invention is directed to solve above-mentioned technical problem at least to a certain extent.
Primary and foremost purpose of the invention is insertion and the image for guaranteeing to realize information in the case where higher picture quality
Distortionless.
In order to solve the above technical problems, technical scheme is as follows:
A kind of reversible information hidden method based on the modification of multiple two-dimensional histograms, which is characterized in that apply in grayscale image
As in, comprising the following steps:
S1: using two pixels adjacent in gray level image as a pixel pair, by gray level image as unit of pixel pair
It is divided into mutually non-conterminous two set, shade set and blank set；
S2: to each pixel pair, adjacent pixel predicts the pixel of pixel centering using pixel, obtains
To the pixel predictors of pixel centering, predicted value and original pixel value subtract each other to obtain prediction error, two adjacent prediction errors
Form a prediction error pair；
S3: predicting error pair to each, calculates its Local Complexity, then the part of all prediction errors pair is complicated
Degree determines n threshold value according to being arranged from low to high, and n is the integer greater than 2, is missed all predictions according to n threshold value
Difference constructs n+1 two-dimensional prediction error to being divided into n+1 prediction error to the identical set of number, and according to n+1 set
Histogram；
S4: according to the capacity of wanted embedding information, each set selects a work from 8 mapping graphs being pre-designed
For the prediction histogram it is all prediction errors pair mapping modes, and according to corresponding mapping ruler carry out information insertion.
Preferably, step S2 specifically:
S2.1: for pixel to (x, y), the surface x pixel is v1, x left pixel is v2, the underface x pixel is v3, y
Underface pixel is v4, y right pixel is v5, the surface y pixel is v6, x predicted value is px, y predicted value is py, then:
px=(v1+v2+v3+(v4+v5+v6+(v1+v2+v3)/3)/4)/4
py=(v4+v5+v6+(v1+v2+v3+(v4+v5+v6)/3)/4)/4
Wherein, the pixel of gray-scale Image Edge does not need to be predicted；
S2.2: two adjacent prediction error es are obtainedx=x-pxAnd ey=y-py, wherein exFor the prediction error of pixel x,
eyFor the prediction error of pixel y, exAnd eyA prediction error is formed to (ex, ey)。
Preferably, the n value 15 of step S3.
Preferably, error pair is predicted to each in step S3, calculates its Local Complexity, specifically:
Adjacent pixels all to (x, y) for pixel ask them absolutely according to horizontally and vertically making the difference
The sum of value, as its Local Complexity.
Preferably, in step S4 8 mapping graphs mapping mode, including operate, modify direction, information bit to be embedded
Value corresponding relationship after position b, with change, table 1 are the value condition of first mapping graph mapping mode:
Table 1
Table 2 is the value condition of the mapping mode of the second to seven mapping graph, and the number of the second to seven mapping graph, which is used, divides
It is not indicated with bi=1,2,3,4,5,6:
Table 2
A kind of extracting method that the reversible information based on the modification of multiple two-dimensional histograms is hiding is held when extracting embedding information
The inverse process of the mapping mode of row Tables 1 and 2, can correctly extract embedding information, and can Distortionless original pixels
Value.
Compared with prior art, the beneficial effect of technical solution of the present invention is:
The present invention is that Information hiding is carried out mainly in gray level image, efficiently embedding information and can correctly be mentioned
It takes out embedded information, nondestructively restore original image.The present invention improves the visual quality of image after embedding information, i.e.,
Y-PSNR increases, and the method for the present invention distorts evidence obtaining, Cloud Server certification and pipe in secret communication, copyright protection, multimedia
It is very practical in the multiple fields such as reason and realizes good effect.
Detailed description of the invention
Fig. 1 is the flow chart for the reversible information hidden method modified the present invention is based on multiple two-dimensional histograms.
Fig. 2 be reversible information hidden method modify the present invention is based on multiple two-dimensional histograms partial phantom set with
Blank set divides exemplary diagram.
Fig. 3 is that the different two dimension of 8 kinds of the reversible information hidden method modified the present invention is based on multiple two-dimensional histograms is straight
Square figure mapping graph.
Fig. 4 is that the different two dimension of 8 kinds of the reversible information hidden method modified the present invention is based on multiple two-dimensional histograms is straight
The first two-dimensional histogram mapping graph in square figure mapping graph.
Fig. 5 is the Y-PSNR statistical experiment result figure of the gray level image embedding information of Lena.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent；
In order to better illustrate this embodiment, the certain components of attached drawing have omission, zoom in or out, and do not represent practical production
The size of product；
To those skilled in the art, it is to be understood that certain known features and its explanation, which may be omitted, in attached drawing
's.
The following further describes the technical solution of the present invention with reference to the accompanying drawings and examples.
Embodiment 1
The present embodiment provides a kind of reversible information hidden method based on the modification of multiple two-dimensional histograms, and the present embodiment
Using the gray level image of Lena as carrier image, such as Fig. 1, comprising the following steps:
S1: being revised as 254 and 1 for the pixel that pixel value is 255 and 0, and construct positioning figure, positioning figure is carried out lossless
Compression, the least significant bit of compressed positioning figure and some pixels of picture the first row is by a part as secret information
It is embedded into picture.Using two adjacent pixels of original-gray image as a pixel pair, by whole picture with pixel to for
Unit is divided into mutually non-conterminous two set: shade set and blank set.The part that shade set and blank set divide
Example such as Fig. 1.
S2: since the second secondary series, according to sequence from left to right from top to bottom, to each of " blank " set
Pixel pair predicts the pixel of the pixel centering adjacent pixel using the pixel, to obtain the pixel centering
The predicted value of pixel, predicted value and original pixel value subtract each other to obtain prediction error, and two adjacent prediction errors form one in advance
Survey error pair.Wherein specific prediction technique is as follows:
As shown in Fig. 2, the surface x pixel is v for pixel to (x, y)1, x left pixel is v2, pixel is immediately below x
v3, the underface y pixel is v4, y right pixel is v5, the surface y pixel is v6, x predicted value is px, y predicted value is py, then:
px=(v1+v2+v3+(v4+v5+v6+(v1+v2+v3)/3)/4)/4
py=(v4+v5+v6+(v1+v2+v3+(v4+v5+v6)/3)/4)/4
Wherein, the pixel at gray image edge does not need to be predicted；
Obtain two adjacent prediction error esx=x-pxAnd ey=y-py, wherein exFor the prediction error of pixel x, eyFor
The prediction error of pixel y, exAnd eyA prediction error is formed to (ex, ey)。
S3: the Local Complexity of each prediction error pair is calculated, then the Local Complexity of all prediction errors pair is pressed
According to being arranged from low to high, and determine 15 threshold value s0,s1,…,s14, this 15 threshold values can by all prediction errors to draw
It is divided into 16 prediction error set essentially identical to number, i.e., each set comprises about 1/16 prediction error pair, and root
16 two-dimensional prediction histogram of error are constructed according to this 16 set:
h0,h1,…,h15。
Wherein as shown in Fig. 2, prediction error is to (ex, ey) Local Complexity calculation method are as follows: (x, y) is all adjacent
Pixel { v1, v2 ..., v8, w1, w2 ..., w10 } according to horizontally and vertically making the difference, and ask their absolute values it
With.
S4: for h0, h1 ..., each of h15 two-dimensional histogram, we divide according to the difference of embedding capacity
It does not select one of be pre-designed eight kinds of mapping modes (as shown in Figure 3), the foundation of selection is an equal amount of in insertion
In the case where secret, image fault is minimum.Simultaneously use 16 parameters b0, b1 ..., b15 respectively represent each two dimension histogram
Scheme selected mapping mode.Specifically, being eight kinds of different mappings figures involved in the method for the present invention such as Fig. 3, Fig. 4 is figure
3 (a) demonstration, solid line indicate 1 bit information of expansion insertion to the left or to the right, and three sections of dotted line expressions are expanded embedding upward or downward
Enter 1 bit information, both ends dotted line indicates translation, guarantees invertibity.
In the specific implementation process, the two-dimensional histogram of the first mapping mode is selected, as shown in figure 4, prediction error pair
It for (- 1, -1), when information to be embedded is 0, remains unchanged, when information to be embedded is 1, changes into (- 2, -1).
For the prediction error pair for translation, by taking (0,2) as an example, when translation, changes into (0,3).For under normal circumstances, in more detail
Mapping ruler listed in table 1.It is detailed to reflect for selecting the two-dimensional histogram of second to the 7th kind of mapping mode
Rule is penetrated to list in table 2.For the two-dimensional histogram of the 8th kind of mapping mode of selection, it is not embedded in any secret information,
It makes no modifications.Remember the last one because insertion secret information and the prediction error modified to for 1 prediction error pair of kth.
Next shade set is remembered using same Embedded step, the last one is modified because of insertion secret information
Prediction error to for 2 prediction errors pair of kth.After all secret informations are embedded into picture, by auxiliary information: after compression
Positioning figure length, information size to be embedded, s0,s1,…,s14, b0,b1,…,b15, k1 and k2 are replaced with least significant bit
Method be embedded into the first row of picture.The close image of load is thus obtained.
For recipient after receiving and carrying the image of secret information, the step of extracting information, restoring original image, is as follows:
The least significant bit for reading picture the first row first, obtains required parameters: the length of compressed positioning figure
Degree, information size to be embedded, s0,s1,…,s14, b0,b1,…,b15, k1 and k2.First shade set is handled, from kth 2
A prediction error utilizes each pixel pair of " shade " set to beginning, according to sequence from right to left from top to bottom
The pixel predicts the pixel of the pixel centering adjacent pixel, to obtain the prediction of the pixel centering pixel
Value, predicted value and original pixel value subtract each other to obtain prediction error, and two adjacent prediction errors form a prediction error pair.
It is identical when prediction technique is with insertion.
Then, calculate each prediction error pair Local Complexity, then by it is all prediction errors pair Local Complexities
According to being arranged from low to high, according to threshold value s0,s1,…,s14, by all prediction errors to being divided into 16 prediction errors
The set essentially identical to number, i.e., each set comprise about 1/16 prediction error pair, and are constructed according to this 16 set
16 two-dimensional prediction histogram of error: h0, h1 ..., h15.It is identical when the calculation method of Local Complexity is with insertion.
To here we just obtained 16 insertion secret information after two-dimensional histogram, according to b0, b1 ..., b15 can
To determine each two-dimensional histogram used mapping mode in insertion, as long as then using correspondence mappings inverse mapping
It can restore original two dimensional histogram.Blank set will extract secret information using identical step and restore former
Beginning two-dimensional histogram.
After finally the secret information of all insertions extracts, according to the length of compressed positioning figure and letter to be embedded
Size is ceased, the secret information extracted can be divided into original information to be embedded, compressed positioning figure and picture the by we
The least significant bit of a line partial pixel.The partial pixel of picture the first row is carried out using the method for least significant bit replacement
Restore.Then compressed positioning is illustrated and is compressed, schemed to restore the pixel that original pixel value is 1 and 255 according to positioning, in this way
Original pixels just restore completely.
Some experimental results using the method for the present invention are given below:
By taking the gray level image of Lena as an example, calculate different lower the obtained gray level images of insertion rate and original-gray image it
Between Y-PSNR (PSNR) value.Fig. 4 is to take 10 times to do average statistical result, and experimental result is shown, the method for the present invention energy
Effectively improve the PSNR value of gray level image after embedding information, and can be lossless extract embedding information, restore initial carrier figure
Picture.
The same or similar label correspond to the same or similar components；
The terms describing the positional relationship in the drawings are only for illustration, should not be understood as the limitation to this patent；
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (6)
1. a kind of reversible information hidden method based on the modification of multiple two-dimensional histograms, which is characterized in that apply in gray level image
In, comprising the following steps:
S1: using two pixels adjacent in gray level image as a pixel pair, gray level image is divided as unit of pixel pair
For mutually non-conterminous two set, shade set and blank set；
S2: to each pixel pair, predicting the pixel of the pixel centering adjacent pixel using the pixel,
The pixel predictors of the pixel centering are obtained, the predicted value and original pixel value subtract each other to obtain prediction error, and two adjacent
Prediction error form a prediction error pair；
S3: predicting error pair to each, calculate its Local Complexity, then by the Local Complexities of all prediction errors pair according to
It is arranged from low to high, and determines n threshold value, n is the integer greater than 2, according to n threshold value by all prediction errors to division
It is n+1 prediction error to the identical set of number, and n+1 two-dimensional prediction histogram of error is constructed according to n+1 set；
S4: according to the capacity of wanted embedding information, it is each set selected from 8 mapping graphs being pre-designed one it is pre- as this
The mapping mode of all prediction errors pair of histogram is surveyed, and carries out the insertion of information according to corresponding mapping ruler.
2. the reversible information hidden method according to claim 1 based on the modification of multiple two-dimensional histograms, which is characterized in that
The step S2 specifically:
S2.1: for pixel to (x, y), the surface x pixel is v1, x left pixel is v2, the underface x pixel is v3, the underface y
Pixel is v4, y right pixel is v5, the surface y pixel is v6, x predicted value is px, y predicted value is py, then:
px=(v1+v2+v3+(v4+v5+v6+(v1+v2+v3)/3)/4)/4
py=(v4+v5+v6+(v1+v2+v3+(v4+v5+v6)/3)/4)/4
Wherein, the pixel of gray-scale Image Edge does not need to be predicted；
S2.2: two adjacent prediction error es are obtainedx=x-pxAnd ey=y-py, wherein exFor the prediction error of pixel x, eyFor
The prediction error of pixel y, exAnd eyA prediction error is formed to (ex, ey)。
3. the reversible information hidden method according to claim 1 based on the modification of multiple two-dimensional histograms, which is characterized in that
The n value 15 of the step S3.
4. the reversible information hidden method according to claim 2 based on the modification of multiple two-dimensional histograms, which is characterized in that
Error pair is predicted to each in the step S3, calculates its Local Complexity, specifically:
Adjacent pixels all to (x, y) for pixel according to horizontally and vertically making the difference, and ask their absolute values it
With as its Local Complexity.
5. the reversible information hidden method according to claim 4 based on the modification of multiple two-dimensional histograms, which is characterized in that
The mapping mode of 8 mapping graphs in step S4, including operate, modify direction, information bit position b to be embedded, with the value after change
Corresponding relationship, table 1 are the value condition of first mapping graph mapping mode:
Table 1
Table 2 is the value condition of the mapping mode of the second to seven mapping graph, and the number of the second to seven mapping graph with using respectively
Bi=1,2,3,4,5,6 is indicated:
Table 2
8th kind of mapping mode is not to be embedded in any information to two-dimensional histogram, i.e., does not make any modification to two-dimensional histogram.
6. a kind of information extraction side of the reversible information hidden method based on the modification of multiple two-dimensional histograms described in claim 5
Method, which is characterized in that when extracting embedding information, execute the inverse process of the mapping mode of Tables 1 and 2, can correctly extract embedding
Enter information, and the value of energy Distortionless original pixels.
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| CN112132732A (en) * | 2020-09-10 | 2020-12-25 | 宁波大学科学技术学院 | Pixel prediction method of stereo image, reversible information hiding and extracting method, terminal and storage medium |
| CN112132734A (en) * | 2020-09-25 | 2020-12-25 | 中国人民武装警察部队工程大学 | Image reversible information hiding method based on multichannel difference value sorting |
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