CN113726974A - Reversible information hiding method, system, equipment and medium - Google Patents
Reversible information hiding method, system, equipment and medium Download PDFInfo
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- H04N1/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
- H04N1/32101—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
- H04N1/32144—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title embedded in the image data, i.e. enclosed or integrated in the image, e.g. watermark, super-imposed logo or stamp
- H04N1/32149—Methods relating to embedding, encoding, decoding, detection or retrieval operations
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- H04N1/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
- H04N1/32101—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
- H04N1/32144—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title embedded in the image data, i.e. enclosed or integrated in the image, e.g. watermark, super-imposed logo or stamp
- H04N1/32149—Methods relating to embedding, encoding, decoding, detection or retrieval operations
- H04N1/32288—Multiple embedding, e.g. cocktail embedding, or redundant embedding, e.g. repeating the additional information at a plurality of locations in the image
- H04N1/32299—Multiple embedding, e.g. cocktail embedding, or redundant embedding, e.g. repeating the additional information at a plurality of locations in the image using more than one embedding method
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Abstract
The invention discloses a reversible information hiding method, a system, equipment and a medium, wherein the method comprises the following steps: obtaining a preprocessed carrier image and a position map; splicing the position map after preprocessing the position map into the secret information of the binary code stream; obtaining a plurality of image blocks by partitioning, and calculating the complexity of each image block; complexity threshold T based on pre-acquisition1、T2And classifying the complexity of each image block, wherein the complexity is less than or equal to a complexity threshold T1Selecting a Hilbert curve to predict image blocks in the image block set, and performing embedding operation on pixels in the image blocks; for complexity greater than a complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Selecting pixel value sequencing prediction to carry out embedding operation on pixels in the image blocks of the image block set; embedding auxiliary information required for decoding into the first row of pixels of the carrier image after the secret information embedding process. The invention can improve the hiding performance of the reversible information hiding algorithm.
Description
Technical Field
The invention belongs to the technical field of information security, relates to the field of reversible information hiding based on airspace, and particularly relates to a reversible information hiding method, a reversible information hiding system, reversible information hiding equipment and a reversible information hiding medium.
Background
Personal privacy information is revealed, and the situation that the confidential information of the country and the enterprise is attacked frequently happens, so that the problem that the information security cannot be guaranteed brings great loss to the country, the society and the individual, and the guarantee of the data security becomes important. Reversible information hiding technology hides confidential information into a carrier, then transmits the carrier embedded with the confidential information in an open channel, and simultaneously, a receiver can recover the original confidential information and the carrier without loss. Information hiding achieves the aim of hiding communication by reducing carrier distortion. And an attacker can see that the secret information and the original carrier information are not different, so that the safety of the secret information is ensured.
In order to ensure that confidential information is transmitted safely and covertly, a reversible information hiding algorithm needs to pursue larger embedding capacity and lower carrier distortion. The embedding capacity refers to the total amount of secret information which can be embedded in the carrier, and reflects the efficiency of secret information transmission, and the higher the embedding capacity is, the higher the transmission efficiency of the secret information is. Carrier distortion refers to quality loss before and after embedding of the carrier image into the secret information, the imperceptibility of secret information transmission is reflected, and the lower the carrier distortion is, the stronger the imperceptibility of secret information transmission is. But both the embedding capacity and the carrier distortion are dual, and in order to obtain a higher embedding capacity the carrier distortion is increased at the cost and vice versa.
In order to pursue larger embedding capacity, researchers propose an information hiding algorithm based on adjacent pixel value difference expansion, so that secret information of one bit can be embedded into every two pixels, but the difference expansion directly causes the problem of larger modification of pixel values, and larger carrier distortion is caused; in addition, problems such as overflow of pixel values, increase of side information, and the like are also induced.
In order to reduce carrier distortion, it has been proposed by researchers to hide secret information among the largest number of pixel values in the carrier image gray histogram, so that the value of each pixel changes by at most 1, and to modify the pixel values only for part of the pixels, which can effectively reduce carrier distortion, but in doing so the embedding capacity of the image is relatively small and depends largely on the content of the carrier image.
At present, researchers propose to hide secret information in a prediction error histogram of a pixel to obtain a good comprehensive effect, but the method still has a large improvement space: the redundancy between the carrier image pixels still needs to be further exploited to increase the embedding capacity; the body distortion needs to be further reduced under low embedding capacity.
Disclosure of Invention
The invention aims to provide a reversible information hiding method, a reversible information hiding system, reversible information hiding equipment and a reversible information hiding medium, which are used for solving the technical problems of reversible information hiding performance limitation, such as insufficient development of redundancy among pixels, unreasonable condition of embedding secret information and the like in the pixel value sequencing prediction method in the prior art. The invention can improve the hiding performance of the reversible information hiding algorithm.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention discloses a reversible information hiding method, which comprises the following steps:
until the embedding of the secret information is completed or there are no available pixels;
and 5, embedding auxiliary information required by decoding into the first row of pixels of the processed carrier image in the step 4.
The invention has the further improvement that the step 1 specifically comprises the following steps:
scanning each pixel except the first line of the carrier image according to the raster scanning sequence, setting the initial value of i to be 1, and performing the following operation on each pixel:
in the formula, px,yRepresents the pixel value with coordinates (x, y), where x ∈ [2, H ]]，y∈[1,W]H and W denote the height and width of the carrier image, respectively; LM is a position map, used for recording the one-dimensional vector of pixel value adjustment;
performing arithmetic compression on the LM to obtain a compressed position map CLM; and splicing and combining the compressed location map CLM after the secret information.
The invention has the further improvement that the step 2 specifically comprises the following steps:
step 2.1, dividing the carrier image into non-overlapping image blocks with the size of h multiplied by w, and recording pixels from the 1 st to the w +2 th columns from the h +1 th row to the h +2 th row and from the w +1 st to the w +2 th columns from the 1 st to the h +2 th row;
step 2.2, for the image Block BlockiThe intra-block and the out-block pixels are pm,n，1≤m≤h+2，1≤n≤w+2；
The complexity calculation formula is as follows:
a further development of the invention consists in the pre-acquired complexity threshold T being used in step 31、T2The obtaining step comprises:
setting a complexity threshold T1And T2；
Wherein, T is more than or equal to 01<T2≤max(Complexity(Blocki))，max(Complexity(Blocki) Represents the maximum value of the image block complexity in the carrier image;
traversing image block complexity sets in carrier images, and respectively using the image block complexity sets as T1And T2Calculating distortion; selecting T corresponding to optimal distortion condition1、T2And the value combination of Bin1 and Bin2 is the final complexity threshold T1、T2And embedded bins 1, Bin 2; selecting T corresponding to optimal distortion condition1、T2Is combined to the final complexity threshold T1、T2；
The specific steps of calculating distortion are as follows:
(1) according to the currently set T1And T2Is performed in step 4, resulting in a given T1And T2Sub-optimal distortion embedding results under the conditions: dense image container (T)1,T2Bin1, Bin2) and embedded histogram Bin1, Bin 2; where Bin1, Bin2 denote at a given T1,T2Embedding under the condition; t is1,T2Bin1, Bin2 together determine the optimal embedding conditions;
(2) calculating peak signal-to-noise ratio (PSNR) of the carrier image and the dense image1,T2Bin1, Bin2)), where cover is the carrier image and PSNR (-) represents the peak signal-to-noise ratio calculation formula;
the steps for obtaining the optimal distortion condition are as follows:
1) step 4 is executed to obtain the value at the given T1And T2Suboptimal distortion embedding case under conditions:
2) traversing image block complexity sets in carrier images, and respectively using the image block complexity sets as T1And T2Traversing all possible combinations to obtain the optimal distortion condition:
the invention is further improved in that, in step 4, the complexity is less than or equal to the complexity threshold T1The specific step of selecting the hilbert curve prediction to perform the embedding operation on the pixels in the image blocks in the image block set comprises the following steps:
for image blocks classified as image blocks predicted by using a Hilbert curve, selecting embedded vertical bins Bin1 and Bin2 of prediction errors; wherein min (error) is more than or equal to Bin1 and less than Bin2 and more than or equal to max (error), min (error) represents the minimum value of the prediction error, max (error) represents the maximum value of the prediction error, the embedded vertical direction Bin1 and Bin2 are positive integers; the embedded histogram is updated by traversing all possible values of Bin1 and Bin 2;
for each image block, acquiring each pixel value in the image block according to the Hilbert curve scanning sequence to obtain a sequence { p1,p2,…,ph×wFor piAnd pi+1，piAs a predicted pixel, pi+1As the predicted pixel, calculating the prediction error and performing the embedding or shifting operation, the expression is as follows:
ei＝pi+1-pi，1≤i≤h×w-1，
where b ∈ {0,1} is a secret information bit,
is the embedded pixel value;
in step 4, for complexity greater than complexity threshold T1And the complexity is less than or equal to the complexity threshold T2The specific steps of selecting pixel value ordering prediction to perform embedding operation on pixels in an image block of the image block set comprise:
for image blocks classified as pixel value ordering prediction, each pixel value is obtained in raster scan order, resulting in a sequence { p }1,p2,…,ph×wAnd arranging the sequences in the order from small to large to obtain a sequence (p) after sequencingσ(1),pσ(2),…,pσ(h×w)}; wherein, sigma: {1,2, …, h × w } → {1,2, …, h × w } is a one-to-one ordering mapping, and the mapping result is pσ(1)≤pσ(2)≤…≤pσ(h×w)(ii) a Wherein, in pσ(n)＝pσ(m)And n is<m is, has sigma (n)<σ(m)；
Maximum pixel p of each image blockσ(h×w)And a minimum pixel pσ(1)The second largest pixel p of each image block, being the predicted pixelσ(h×w-1)And the second smallest pixel pσ(2)As predicted pixel values, prediction errors thereof are respectively calculated as follows:
eσ(h×w)＝pσ(h×w)-pσ(h×w-1)，
eσ(1)＝pσ(2)-pσ(1)，
embedding or moving the pixel according to the value of the prediction error, wherein the expression is as follows:
where b ∈ {0,1} is a secret information bit,
for the maximum pixel value within the embedded block,
is the minimum pixel value in the embedded block;
updating the embedded histograms Bin1 and Bin2, repeating until a prediction error set of the predicted pixel and the predicted pixel is traversed, respectively serving as a value combination of Bin1 and Bin2, calculating distortion, and recording suboptimal distortion conditions;
wherein the calculation of the distortion comprises the steps of:
according to the currently set T1,T2Bin1, Bin2, yields the embedding result under the given conditions: dense image container (T)1,T2,Bin1,Bin2)；
Calculating peak signal-to-noise ratio (PSNR) of the carrier image and the dense image1,Bin2Bin1, Bin2)), where cover is the carrier image and PSNR (-) represents the peak signal-to-noise ratio calculation formula;
the method for obtaining the suboptimal distortion comprises the following steps:
obtaining a dense image container (T) after performing the embedding operation1,T2Bin1, Bin 2); the sub-optimal embedding case is obtained by the following method:
in a further improvement of the present invention, in step 5, the side information required for decoding includes: dividing the sizes h and w of the image blocks; complexity threshold T1And T2(ii) a Embedded bins 1 and Bin 2; last position of embedding Pend(ii) a Length l of compressed position mapCLM。
The invention is further improved in that after the step 5, a decoding process is also included;
the decoding process specifically includes the steps of:
before reading the first line of the carrier image
Obtaining the auxiliary information from the least significant bit of the pixel;
starting from the last pixel of the embedding, scanning block by block in the reverse order of raster scanning, and calculating complexity by using pixels outside the blocks;
selecting a corresponding predictor to decode the image block based on the complexity of each image block; for an image block predicted by using a Hilbert curve, obtaining a scanning sequence according to the Hilbert curve, taking a first pixel as a reference pixel, sequentially extracting secret information and recovering an original pixel value; for an image block which adopts pixel value sequencing prediction, sequencing pixels in the image block, respectively extracting secret information in a maximum value and a minimum value by utilizing a secondary large value and a secondary small value, and recovering an original pixel value;
after the solved secret information
Before bit replacement of the first row
The least significant bit of the pixel of (a);
decompressing the compressed position map in the auxiliary information to obtain a position map; and restoring the original edge pixel value by using the position map.
The invention discloses a reversible information hiding system, which comprises:
the preprocessing module is used for performing anti-overflow preprocessing on the parts of the carrier image except the first row of pixels to obtain a processed carrier image and a position map; splicing the position map after preprocessing the position map into the secret information of the binary code stream;
the blocking module is used for carrying out non-overlapping blocking on the obtained processed carrier image except the first row of pixels to obtain a plurality of image blocks; calculating and obtaining the complexity of each image block by utilizing the pixels outside the blocks;
a classification module for pre-acquisition based complexity threshold T1、T2And the complexity of each image block, classifying the plurality of image blocks obtained by partitioning, and obtaining the complexity less than or equal to a complexity threshold T1Image block set, complexity greater than complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Image block set and complexity greater than complexity threshold T2The set of image blocks of (1); wherein, T1Less than T2；
A first embedding module for setting a complexity threshold T for complexity less than or equal to1Selecting a Hilbert curve to predict image blocks in the image block set, and performing embedding operation on pixels in the image blocks; for complexity greater than a complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Selecting pixel value sequencing prediction to carry out embedding operation on pixels in the image blocks of the image block set; for complexity greater than complexity threshold T2The image blocks of the image block set do not carry out embedding operation; until the embedding of the secret information is completed or there are no available pixels;
and the second embedding module is used for embedding auxiliary information required by decoding into the first row of pixels of the processed carrier image by the first embedding module.
An electronic device of the present invention comprises a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the reversible information hiding method according to any one of the above aspects of the present invention.
A computer-readable storage medium of the present invention stores at least one instruction, which when executed by a processor, implements a reversible information hiding method as any one of the above described methods of the present invention.
Compared with the prior art, the invention has the following beneficial effects:
the invention combines the Hilbert curve prediction and the pixel value sequencing prediction to further exert the advantages of the two algorithms, and specifically comprises the following steps:
(1) the Hilbert curve prediction is adopted in a low-complexity area, so that the redundancy among pixels is fully developed, and more prediction errors are obtained;
(2) the image is firstly partitioned and then predicted by using a Hilbert curve, so that the complexity is utilized, and the moving distortion caused by embedding is reduced;
(3) under the condition of low embedding capacity, the selection of an embedding histogram is considered, the histogram is represented by histograms close to two sides on the prediction error histogram, and the moving distortion can be effectively reduced by embedding the histogram;
(4) for blocks with higher complexity, pixel value sequencing prediction is adopted, the performance is improved by utilizing the correlation between the sequenced pixel values, and compared with Hilbert curve prediction, unnecessary shifting distortion is reduced, so that the combination of the Hilbert curve prediction and the pixel value sequencing prediction is realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art are briefly introduced below; it is obvious that the drawings in the following description are some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 is a flowchart illustrating a reversible information hiding method based on hilbert curve prediction and pixel value ordering prediction according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of Hilbert curve scanning using a tile size of 2 × 2 in an embodiment of the present invention;
FIG. 3 is a diagram illustrating pixel value ordering using a tile size of 2 × 2 in an embodiment of the present invention;
FIG. 4 is a histogram of prediction errors when the algorithm of this embodiment compares the pixel value ordering prediction when the block size is 2 × 2 and the embedding capacity is 36000 with the prediction error histogram when the block size is 2 × 2 and the Hilbert curve prediction when the block size is 2 × 2 according to the embodiment of the present invention;
fig. 5 is a diagram illustrating the number of image blocks predicted by using hilbert curve prediction and pixel value ordering with a block size of 2 × 2 according to an embodiment of the present invention as a function of Embedding Capacity (EC);
fig. 6 is a schematic diagram of the variation of peak signal-to-noise ratio (PSNR) of the Lena and the original image with the Embedding Capacity (EC) when the algorithm of the embodiment of the present invention is compared with the pixel value ordering prediction and the hilbert curve prediction.
Detailed Description
In order to make the purpose, technical effect and technical solution of the embodiments of the present invention clearer, the following clearly and completely describes the technical solution of the embodiments of the present invention with reference to the drawings in the embodiments of the present invention; it is to be understood that the described embodiments are only some of the embodiments of the present invention. Other embodiments, which can be derived by one of ordinary skill in the art from the disclosed embodiments without inventive faculty, are intended to be within the scope of the invention.
Referring to fig. 1, a reversible information hiding algorithm based on hilbert curve prediction and pixel value ordering prediction according to an embodiment of the present invention includes the following steps:
step 1: the portions of the carrier image other than the first line are subjected to an overflow/underflow prevention operation.
Optionally, step 1 specifically includes: setting i to an initial value of 1 by scanning each pixel out of the first line of the carrier image from left to right in raster scanning order, i.e., from top to bottom, and performing the following operations for each pixel:
in the formula, px,yRepresents the pixel value with coordinates (x, y), where x ∈ [2, H ]],y∈[1,W]H and W represent the height and width of the image, respectively; LM is a position map, which is used to record pixelsA value adjusted one-dimensional vector. The well-recorded position map is used at the decoding end to restore the pixel values adjusted to prevent overflow/underflow, i.e., the values of 254 and 1 pixels whose corresponding LM { i } is 1 are changed to 255 and 0, respectively.
And performing arithmetic compression on the LM to reduce the required storage amount to obtain a compressed position map CLM. The CLM is incorporated as part of the secret information after the original secret information.
Step 2: and partitioning the image according to the set size of the image block, and simultaneously calculating the complexity of the image block.
(1) Dividing an image into non-overlapping image blocks with the size of h multiplied by w, and simultaneously recording pixels from the 1 st column to the w +2 th column from the h +1 th row to the h +2 th row and pixels from the w +1 st column to the w +2 th column from the 1 st row to the h +2 th row;
(2) for image Block BlockiThe intra-block and the out-block pixels are pm,nM is more than or equal to 1 and less than or equal to h +2, and n is more than or equal to 1 and less than or equal to w + 2. The complexity calculation formula is as follows:
in the formula (2), the gradient of the pixels outside the image block is used as the calculation basis of the complexity. The lower the gradient of pixels outside the block, the lower the complexity; and the redundancy among pixels is further developed by utilizing Hilbert curve prediction, more available prediction errors are obtained, and the embedding capacity is improved. The higher the gradient of pixels outside the block, the higher the complexity; the redundancy among the required pixel values is predicted by utilizing the pixel value sequencing, so that unnecessary shifting distortion is avoided, and the carrier distortion is reduced.
And step 3: a complexity threshold is set.
Setting a complexity threshold T1And T2，
Wherein, T is more than or equal to 01<T2≤max(Complexity(Blocki)),max(Complexity(Blocki) Represents the maximum value of the image block complexity; by traversing T1And T2All possible values are taken as complexity thresholds.
And 4, step 4: and sequentially selecting each block and pixels outside the block according to the raster scanning sequence, calculating the complexity of the block, and selecting a corresponding predictor according to a complexity threshold value.
(1) For each Block BlockiThe Complexity (Block) is calculated by the method shown in step 2i) For Complexity (Block)i)≤T1The image block adopts Hilbert curve prediction to the complexity T1<Complexity(Blocki)≤T2The image block adopts the pixel value sequencing prediction to the complexity T2≤Complexity(Blocki) The image blocks do not adopt embedding operation;
(2) performing an embedding operation on blocks classified as predicted using a Hilbert curve;
a. the embedded prediction error histogram is selected, and the histogram of the prediction error is selected as Bin1 and Bin 2. Wherein min (error) is not less than Bin1 and less than Bin2 is not less than max (error), min (error) represents the minimum value of the prediction error, and max (error) represents the maximum value of the prediction error;
b. for each block, each pixel value is acquired in a Hilbert curve scanning order, resulting in a sequence { p }1,p2,…,ph×wFor piAnd pi+1，piAs a predicted pixel, pi+1As the predicted pixel, calculating the prediction error and performing the embedding or shifting operation, the expression is as follows:
ei＝pi+1-pi，1≤i≤h×w-1,#(3)
where b ∈ {0,1} is a secret information bit, and a randomly generated bit stream is selected as the secret information in the experiment.
For the embedded pixel values, the first pixel in the sequence obtained by scanning each block with the Hilbert curve is used asThe reference pixel is not embedded or shifted, and the original value of the second pixel in the scanned sequence can be recovered at the decoding end. The recovered pixel is used as a reference pixel of the next pixel to be decoded, the original pixel value is sequentially recovered, and meanwhile, secret information is extracted;
(3) for blocks classified as employing pixel value ordering prediction, an embedding operation is performed.
a. For each block, each pixel value therein is acquired in raster scan order, resulting in a sequence { p }1,p2,…,ph×w}；
b. The sequences are arranged from small to large to obtain an ordered sequence { pσ(1),pσ(2),…,pσ(h×w)Wherein, σ: {1,2, …, hxw } → {1,2, …, hxw } is a one-to-one ordering mapping, and the mapping result is pσ(1)≤pσ(2)≤…≤pσ(h×w)Wherein, in pσ(n)＝pσ(m)And n is<m is, has sigma (n)<σ(m)；
c. Maximum pixel p of each blockσ(h×w)And a minimum pixel pσ(1)The second largest pixel p of each block, being the predicted pixelσ(h×w-1)And the second smallest pixel pσ(2)As predicted pixel values, prediction errors thereof are respectively calculated as follows:
eσ(h×w)＝pσ(h×w)-pσ(h×w-1),#(5)
eσ(1)＝pσ(2)-pσ(1).#(6)
d. embedding or moving the pixel according to the value of the prediction error, wherein the expression is as follows:
wherein b ∈ {0,1} is secretThe bits of the information are transmitted to the receiver,
for the maximum pixel value within the embedded block,
for the minimum pixel value in the embedded block, it can be seen that the maximum value and the minimum value of each block are still the maximum value or the minimum value of the block in which the block is located after the block is embedded or moved, so that the difference between the maximum value and the second-largest value and the second-smallest value can be used for determining whether the block is a dense pixel at a decoding end, and the operations of extracting secret information and recovering the original pixel value are performed on the block.
(4) Turning to the step (3) to update the embedded histograms Bin1 and Bin2 until a prediction error set of the predicted pixel and the predicted pixel is traversed and respectively used as a value combination of Bin1 and Bin 2;
(5) bin1 and Bin2, which record the least volume distortion at a given embedding capacity, i.e., Bin1 and Bin2, satisfy the following equations:
and 5: the complexity threshold is updated.
(1) Go to step three to update the complexity threshold T1And T2Until the complexity set of the image blocks in the carrier image is traversed and respectively used as T1And T2Value combination of (1);
(2) recording threshold T at which minimum distortion of the payload is met for a given embedding capacity1And T2And corresponding Bin1 and Bin2, threshold T1And T2And Bin1 and Bin2, respectively, satisfy the following formula:
step 6: the side information required for decoding is embedded in the first row of pixels of the image.
Taking the image with size H multiplied by W asFor example, before the first line of the image
The least significant bits of the individual pixels are recorded and these data are incorporated into the secret information. In order to realize blind solution at the decoding end, the original least significant bit is replaced by the following auxiliary information, including:
(1) dividing the sizes h and w of the image blocks, and occupying 2+ 2-4 bits;
(2) complexity threshold T1And T2Occupying 12 bits;
(3) embedding the bins 1 and 2, and occupying 8 bits;
(4) last position of embedding PendOccupied
A bit;
(5) length l of compressed position mapCLMOccupied
A bit;
in the above formula, the first and second carbon atoms are,
indicating rounding up.
The performance of the final method can be measured by the embedding capacity-peak signal-to-noise ratio curve, i.e. the quality of the image of the carrier at a certain amount of embedded information.
The reversible information hiding algorithm based on pixel value sequencing prediction and diamond prediction is used for covert communication or secret information storage, and decoding comprises the following steps:
and 2, starting from the last embedded pixel, scanning block by block in the reverse order of raster scanning, and calculating complexity by using pixels outside the blocks. And (2) selecting a corresponding predictor to decode the image block by referring to the complexity threshold obtained by decoding in the step 1: for an image block predicted by using a Hilbert curve, obtaining a scanning sequence according to the Hilbert curve, taking a first pixel as a reference pixel, sequentially extracting secret information and recovering an original pixel value; for an image block which adopts pixel value sequencing prediction, sequencing pixels in the image block, respectively extracting secret information in a maximum value and a minimum value by utilizing a secondary large value and a secondary small value, and recovering an original pixel value;
and 4, decompressing the compressed position map in the auxiliary information to obtain a position map, and recovering the original edge pixel value by using the position map.
Referring to fig. 1 to 6, fig. 4h-2 × 2 shows a prediction error histogram obtained by hilbert curve prediction when the block size is 2 × 2; p-2 x 2 represents a prediction error histogram obtained by pixel value sequencing prediction when the block size is 2 x 2; com-2 x 2 represents the prediction error histogram obtained by the algorithm of this example when the block size is 2 x 2 and the embedding capacity is 36000 in the embodiment of the present invention. It can be seen from fig. 4 that the reversible information hiding algorithm of hilbert curve prediction and pixel value ordering prediction (0 and 1 are selected as embedding direction when the embedding capacity is 36000) can effectively improve the embedding capacity and reduce the carrier distortion. The number of pixels with prediction errors of 0 and 1 is higher than the number of pixels with prediction errors of 0 and 1 (0 and 1 are embedded vertical directions) obtained by Hilbert curve prediction, and the number of pixels with prediction errors of 1 (1 is an embedded vertical direction) obtained by pixel value sorting prediction. In addition, the proportion of pixels with prediction errors of 0 and 1 to all the predicted pixels is higher than the proportion of pixels with prediction errors of 0 and 1 (0 and 1 are embedded vertical direction) to all the predicted pixels obtained by the hilbert curve prediction, and the proportion of pixels with prediction errors of 1 (1 is embedded vertical direction) to all the predicted pixels obtained by the pixel value ordering prediction is higher, so the carrier distortion is claimed to be effectively reduced.
Fig. 5Pixel-H shows the number of image blocks predicted using the hilbert curve, and Pixel-P shows the number of image blocks predicted using Pixel value ordering. It can be seen from fig. 5 that the present invention realizes effective combination of Hilbert curve prediction and pixel value ordering prediction, and that n × n-1 pixels can be operated for a block of size n × n by using Hilbert curve prediction, so that the embedding capacity can be improved well in a low complexity region, and the distortion is small at a low embedding capacity; in a high complexity region, the invention adopts PVO prediction to reduce distortion by reducing the movement.
FIG. 6Baseline-H shows the peak SNR of the Hilbert curve prediction guidance embedded download body image and the original image, Baseline-P shows the peak SNR of the pixel value sequencing prediction guidance embedded download body image and the original image, and Proposed shows the peak SNR of the algorithm guidance embedded download body image and the original image in the embodiment of the present invention. Fig. 6 compares the performance of the reversible information hiding algorithm based on the hilbert curve prediction with the performance of the reversible information hiding algorithm based on the pixel value ordering prediction. It is found that on a standard test image Lena, with the change of the embedded capacity, the algorithm of the invention compares a reversible information hiding algorithm based on Hilbert curve prediction, and the performance of the algorithm is closer to that of the reversible information hiding algorithm at low capacity, but the performance of the algorithm is gradually superior to that of the comparison algorithm when the capacity is gradually increased, which is caused by mainly using Hilbert curve prediction at low capacity. Similarly, the reversible information hiding algorithm based on the pixel value sequencing prediction is compared, when the capacity is gradually increased, more and more image blocks are subjected to the pixel value sequencing prediction, and the performance of the algorithm gradually tends to the comparison algorithm. Fig. 5 also demonstrates this view.
The reversible information hiding system based on the Hilbert curve prediction and the pixel value sequencing prediction in the embodiment of the invention comprises the following components:
the overflow/underflow preventing module is used for adjusting the pixel value before information embedding so that the embedded and moved pixel value does not exceed the upper and lower boundaries of the pixel value;
the complexity calculating module is used for dividing the image into image blocks and calculating the complexity of the image blocks so as to determine a predictor adopted by the image blocks to be embedded;
the embedded histogram selection module is used for selecting the prediction error histogram subjected to the embedding operation to reduce the moving distortion;
the prediction and embedding module is used for obtaining the prediction error value of the predicted pixel and embedding the secret information by modifying the value of the prediction error value;
an auxiliary information embedding module, which can embed auxiliary information required by decoding into pixels at specific positions of the image, so that the decoding can be performed without additional information;
and a decoding module for losslessly decoding the embedded secret information and losslessly restoring the carrier image by using the auxiliary information.
In summary, the embodiment of the present invention provides a reversible information hiding algorithm based on hilbert curve prediction and pixel value ordering prediction, so as to solve the problems of insufficient redundancy development for low-complexity regions and large shifting distortion caused by embedding operation in the prior art, and improve the performance of the reversible information hiding algorithm. The invention integrates the advantages of two methods through the research of Hilbert curve prediction and pixel value sequencing prediction, and the proposed adaptive complexity further develops redundancy by adopting Hilbert curve prediction on the image block which is easier to embed, thereby improving the embedding capacity. Meanwhile, the method is self-adaptive to the embedded histogram, and unnecessary shifting distortion is reduced. In addition, the redundancy among pixel values is developed by adopting pixel value sequencing prediction on image blocks which are difficult to embed, the moving distortion is further reduced, and the embedding performance of the algorithm is improved. The invention discloses a reversible information hiding algorithm based on Hilbert curve prediction and pixel value sequencing prediction, which comprises the following steps of: the method comprises the following steps: the portions of the carrier image other than the first line are subjected to an overflow/underflow prevention operation and corresponding information for image recovery is recorded. Step two: and partitioning the parts of the carrier image except the first row without overlapping, and calculating the complexity by using pixels outside the blocks. Step three: a complexity threshold is set. Step four: extracting an image block, calculating the complexity of the current image block, classifying the current image block through a complexity threshold, and selecting a Hilbert curve prediction or a pixel value ordering prediction according to a classification result to perform embedding operation on pixels in the image block until secret information is completely embedded or no available pixels exist. Step five: and embedding auxiliary information required by decoding into the first row of pixels of the image, calculating the distortion at the moment, recording the optimal condition, turning to the third step, and updating the complexity threshold until all conditions are traversed. Step six: the side information required for decoding is embedded in the first row of pixels of the image. The invention provides an effective prediction method to improve the embedding performance of a reversible information hiding algorithm, and the effectiveness of the method is verified through experiments.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the embodiments of the present invention without departing from the spirit and scope of the present invention, which is set forth in the claims of the present application.
Claims (10)
1. A reversible information hiding method is characterized by comprising the following steps:
step 1, performing anti-overflow pretreatment on the part of a carrier image except for a first row of pixels to obtain a processed carrier image and a position map; splicing the position map after preprocessing the position map into the secret information of the binary code stream;
step 2, carrying out non-overlapping blocking on the processed carrier image obtained in the step 1 except for the first row of pixels to obtain a plurality of image blocks; calculating and obtaining the complexity of each image block by utilizing the pixels outside the blocks;
step 3, based on the complexity threshold T of pre-acquisition1、T2And the complexity of each image block, classifying the plurality of image blocks obtained by partitioning in the step 2 to obtain the complexity less than or equal to a complexity threshold T1Image block set, complexity greater than complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Image block set and complexity greater than complexity threshold T2The set of image blocks of (1); wherein, T1Less than T2；
Step 4, for the complexity less than or equal to the complexity threshold T1Selecting a Hilbert curve to predict image blocks in the image block set, and performing embedding operation on pixels in the image blocks; for complexity greater than a complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Selecting pixel value sequencing prediction to carry out embedding operation on pixels in the image blocks of the image block set; for complexity greater than complexity threshold T2The image blocks of the image block set do not carry out embedding operation;
until the embedding of the secret information is completed or there are no available pixels;
and 5, embedding auxiliary information required by decoding into the first row of pixels of the processed carrier image in the step 4.
2. The reversible information hiding method according to claim 1, wherein step 1 specifically comprises:
scanning each pixel except the first line of the carrier image according to the raster scanning sequence, setting the initial value of i to be 1, and performing the following operation on each pixel:
in the formula, px，yRepresents the pixel value with coordinates (x, y), where x ∈ [2, H ]]，y∈[1，W]H and W denote the height and width of the carrier image, respectively; LM is a position map, used for recording the one-dimensional vector of pixel value adjustment;
performing arithmetic compression on the LM to obtain a compressed position map CLM; and splicing and combining the compressed location map CLM after the secret information.
3. The reversible information hiding method according to claim 2, wherein the step 2 specifically comprises:
step 2.1, dividing the carrier image into non-overlapping image blocks with the size of h multiplied by w, and recording pixels from the 1 st to the w +2 th columns from the h +1 th row to the h +2 th row and from the w +1 st to the w +2 th columns from the 1 st to the h +2 th row;
step 2.2, for the image Block BlockiThe intra-block and the out-block pixels are pm，n，1≤m≤h+2，1≤n≤w+2；
The complexity calculation formula is as follows:
4. a reversible information hiding method as claimed in claim 3, characterized in that in step 3, the pre-obtained complexity threshold T is1、T2The obtaining step comprises:
setting a complexity threshold T1And T2；
Wherein, T is more than or equal to 01＜T2≤max(Complexity(Blocki))，max(Complexity(Blocki) Represents the maximum value of the image block complexity in the carrier image;
traversing image block complexity sets in carrier images, and respectively using the image block complexity sets as T1And T2Calculating distortion; selecting T corresponding to optimal distortion condition1、T2And the value combination of Bin1 and Bin2 is the final complexity threshold T1、T2And embedded bins 1, Bin 2; selecting T corresponding to optimal distortion condition1、T2Is combined to the final complexity threshold T1、T2；
The specific steps of calculating distortion are as follows:
(1) according to the currentSet T1And T2Is performed in step 4, resulting in a given T1And T2Sub-optimal distortion embedding results under the conditions: dense image container (T)1，T2Bin1, Bin2) and embedded histogram Bin1, Bin 2; where Bin1, Bin2 denote at a given T1，T2Embedding under the condition; t is1，T2Bin1, Bin2 together determine the optimal embedding conditions;
(2) calculating peak signal-to-noise ratio (PSNR) of the carrier image and the dense image1，T2Bin1, Bin2)), where cover is the carrier image and PSNR (-) represents the peak signal-to-noise ratio calculation formula;
the steps for obtaining the optimal distortion condition are as follows:
1) step 4 is executed to obtain the value at the given T1And T2Suboptimal distortion embedding case under conditions:
2) traversing image block complexity sets in carrier images, and respectively using the image block complexity sets as T1And T2Traversing all possible combinations to obtain the optimal distortion condition:
5. a reversible information hiding method as claimed in claim 4, characterized in that in step 4, for complexity less than or equal to complexity threshold T1The specific step of selecting the hilbert curve prediction to perform the embedding operation on the pixels in the image blocks in the image block set comprises the following steps:
for image blocks classified as image blocks predicted by using a Hilbert curve, selecting embedded vertical bins Bin1 and Bin2 of prediction errors; wherein min (error) is more than or equal to Bin1 and more than or equal to Bin2 and more than or equal to max (error), min (error) represents the minimum value of the prediction error, max (error) represents the maximum value of the prediction error, the embedded vertical direction Bin1 and Bin2 are positive integers; the embedded histogram is updated by traversing all possible values of Bin1 and Bin 2;
for each image block, acquiring each pixel value in the image block according to the Hilbert curve scanning sequence to obtain a sequence { p1，p2，…，ph×wFor piAnd pi+1，piAs a predicted pixel, pi+1As the predicted pixel, calculating the prediction error and performing the embedding or shifting operation, the expression is as follows:
ei＝pi+1-pi，1≤i≤h×w-1，
where b ∈ {0,1} is a secret information bit,
is the embedded pixel value;
in step 4, for complexity greater than complexity threshold T1And the complexity is less than or equal to the complexity threshold T2The specific steps of selecting pixel value ordering prediction to perform embedding operation on pixels in an image block of the image block set comprise:
for image blocks classified as pixel value ordering prediction, each pixel value is obtained in raster scan order, resulting in a sequence { p }1，p2，…，ph×wAnd arranging the sequences in the order from small to large to obtain a sequence (p) after sequencingσ(1)，pσ(2)，…，pσ(h×w)}; in the formula, σ: {1,2, …, h × w } → {1,2, …, h × w } is a one-to-one ordering map, with the result of the map being pσ(1)≤pσ(2)≤…≤pσ(h×w)(ii) a Wherein, in pσ(n)＝pσ(m)When n is less than m, the value of sigma (n) < sigma (m);
maximum per image blockPixel pσ(h×w)And a minimum pixel pσ(1)The second largest pixel p of each image block, being the predicted pixelσ(h×w-1)And the second smallest pixel pσ(2)As predicted pixel values, prediction errors thereof are respectively calculated as follows:
eσ(h×w)＝pσ(h×w)-pσ(h×w-1)，
eσ(1)＝pσ(2)-pσ(1)，
embedding or moving the pixel according to the value of the prediction error, wherein the expression is as follows:
where b ∈ {0,1} is a secret information bit,
for the maximum pixel value within the embedded block,
is the minimum pixel value in the embedded block;
updating the embedded histograms Bin1 and Bin2, repeating until a prediction error set of the predicted pixel and the predicted pixel is traversed, respectively serving as a value combination of Bin1 and Bin2, calculating distortion, and recording suboptimal distortion conditions;
wherein the calculation of the distortion comprises the steps of:
according to the currently set T1，T2Bin1, Bin2, yields the embedding result under the given conditions: dense image container (T)1，T2，Bin1，Bin2)；
Calculating peak signal-to-noise ratio (PSNR) of the carrier image and the dense image1，T2Bin1, Bin2)), where cover is the carrier image and PSNR (-) represents the peak signal-to-noise ratio calculation formula;
the method for obtaining the suboptimal distortion comprises the following steps:
obtaining a dense image container (T) after performing the embedding operation1，T2Bin1, Bin 2); the sub-optimal embedding case is obtained by the following method:
6. a reversible information hiding method as claimed in claim 5, wherein in step 5, said side information required for decoding includes: dividing the sizes h and w of the image blocks; complexity threshold T1And T2(ii) a Embedded bins 1 and Bin 2; last position of embedding Pend(ii) a Length l of compressed position mapCLM。
7. A reversible information hiding method as claimed in claim 6, characterized in that, after step 5, it further comprises a decoding process;
the decoding process specifically includes the steps of:
before reading the first line of the carrier image
Obtaining the auxiliary information from the least significant bit of the pixel;
starting from the last pixel of the embedding, scanning block by block in the reverse order of raster scanning, and calculating complexity by using pixels outside the blocks;
selecting a corresponding predictor to decode the image block based on the complexity of each image block; for an image block predicted by using a Hilbert curve, obtaining a scanning sequence according to the Hilbert curve, taking a first pixel as a reference pixel, sequentially extracting secret information and recovering an original pixel value; for an image block which adopts pixel value sequencing prediction, sequencing pixels in the image block, respectively extracting secret information in a maximum value and a minimum value by utilizing a secondary large value and a secondary small value, and recovering an original pixel value;
after the solved secret information
Before bit replacement of the first row
The least significant bit of the pixel of (a);
decompressing the compressed position map in the auxiliary information to obtain a position map; and restoring the original edge pixel value by using the position map.
8. A reversible information hiding system, comprising:
the preprocessing module is used for performing anti-overflow preprocessing on the parts of the carrier image except the first row of pixels to obtain a processed carrier image and a position map; splicing the position map after preprocessing the position map into the secret information of the binary code stream;
the blocking module is used for carrying out non-overlapping blocking on the obtained processed carrier image except the first row of pixels to obtain a plurality of image blocks; calculating and obtaining the complexity of each image block by utilizing the pixels outside the blocks;
a classification module for pre-acquisition based complexity threshold T1、T2And the complexity of each image block, classifying the plurality of image blocks obtained by partitioning, and obtaining the complexity less than or equal to a complexity threshold T1Image block set, complexity greater than complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Image block set and complexity greater than complexity threshold T2The set of image blocks of (1); wherein, T1Less than T2；
A first one of the embedded modules is configured to,for complexity less than or equal to a complexity threshold T1Selecting a Hilbert curve to predict image blocks in the image block set, and performing embedding operation on pixels in the image blocks; for complexity greater than a complexity threshold T1And the complexity is less than or equal to the complexity threshold T2Selecting pixel value sequencing prediction to carry out embedding operation on pixels in the image blocks of the image block set; for complexity greater than complexity threshold T2The image blocks of the image block set do not carry out embedding operation; until the embedding of the secret information is completed or there are no available pixels;
and the second embedding module is used for embedding auxiliary information required by decoding into the first row of pixels of the processed carrier image by the first embedding module.
9. An electronic device, characterized in that the electronic device comprises a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the reversible information hiding method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that it stores at least one instruction which, when executed by a processor, implements a reversible information hiding method as claimed in any one of claims 1 to 7.
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