CN114663268A - Reversible image watermarking algorithm based on improved bit plane decomposition and difference value expansion - Google Patents
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Abstract
The invention relates to the technical field of information hiding and digital watermarking, and discloses a reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion. And then carrying out bit plane decomposition on each selected smooth block, and removing the image sub-blocks containing the sharp points by utilizing multi-scale decomposition. And finally, embedding the scrambled watermark information and auxiliary information into a carrier image by utilizing a generalized difference expansion algorithm and a difference quantization algorithm. The watermark extraction algorithm is the inverse of the watermark embedding algorithm. Compared with the prior art, the method has the advantages of high embedding rate, high visual quality, capability of realizing complete recovery of the original image, better visual perception on images with different texture types, and certain advantages compared with other algorithms.
Description
Technical Field
The invention relates to the technical field of information hiding and digital watermarking, in particular to a reversible image watermarking algorithm based on improved bit plane decomposition and difference value expansion.
Background
Digital watermarking has received much attention as an effective means of copyright protection. When a certain amount of watermarks are embedded by using the digital watermarking technology, a certain distortion is generated in an original image. However, for some special types of carriers, it is required to recover the original carrier image without loss after extracting the embedded information, and therefore, reversible digital watermarking is rapidly developed. The method is different from the digital watermarking technology in that the reversible watermarking technology can recover the original carrier image without distortion after extracting the embedded information, so that the method can be applied to the fields with higher image quality requirements, such as military, remote sensing, medical treatment and the like.
When embedding watermark information, distortion is inevitably generated in the original image. Therefore, Li et al propose a reversible information hiding algorithm based on predictive differential expansion to reduce image distortion, which has a low embedding capacity although it improves the visual quality of the hidden image, and the larger the image block, the lower the embedding capacity.
For difference expansion, it is necessary to locate and compress the pixel overflow location, which is an important factor affecting the embedding rate. Eliminating pixel overflow caused by embedding watermark through difference value expansion has important significance for improving the performance of the watermark algorithm. A reversible watermark embedding method based on a differential histogram adjusts pixel values to a certain range and records the positions of the adjusted pixels in order to avoid pixel overflow.
And combining a reversible watermarking algorithm of the difference expansion and reversible comparison image, forming a difference expansion pixel pair and a reversible comparison image pixel pair for 4 pixels in each block, and embedding watermarks into the two pixel pairs. Reversible contrast image pixel pairs are used primarily to embed small amounts of additional information instead of the scout map, and the embedding capacity is greatly improved. However, the image quality is reduced more by using reversible contrast mapping transformation for half of the pixel pairs in the algorithm. A reversible watermark embedding method based on adjacent pixel difference adjusts the pixel value before embedding the watermark, but the algorithm still needs to embed a small position map. A reversible embedding method based on translation of difference histogram includes regulating pixel value to be in a certain range before translation and recording position of regulated pixel in positioning diagram.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems in the prior art, the invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference value expansion, which not only has high embedding rate, but also has higher visual quality and can realize the complete recovery of the original image.
The technical scheme is as follows: the invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference value expansion, which comprises a watermarking embedding method and comprises the following steps:
step 1: performing Arnold transformation on the watermark W to obtain W ', and converting the transformed watermark W' into a one-dimensional binary sequence;
step 2: an original image I of size M × N (M, N are all integer multiples of 4) is divided into blocks I of size 4 × 4 which do not overlap with each otheri，
And step 3: computing all pixel blocks I by utilizing smoothness computing methodiThe smoothness values are stably sorted from small to large, and a sorting index information table is established;
and 4, step 4: for all image blocks IiPerforming bit plane decomposition, and generating image sub-blocks containing 7 high bits from the image blocks correspondingly arranged at the top 1/3 according to the smoothness value in step3
Generating image sub-blocks containing 6 high bits from the corresponding image blocks arranged in the middle 1/3
Generating image sub-blocks containing 5 high bits corresponding to the next-ranked 1/3 image blocks
；
And 5: for selected image sub-blocks
Deleting the image subblocks with the sharp points by a multi-scale decomposition algorithm;
step 6: according to the watermark capacity embedding requirement, selecting n pixel sub-blocks arranged in front in the sequence, removing m selected image sub-blocks with the sharp points removed, embedding watermark information into the n-m image blocks, and recording the sequencing sequence number of the image sub-blocks containing the sharp points;
and 7: for any selected sub-block
(i is more than or equal to 0and less than or equal to n) watermark embedding is carried out by utilizing a generalized difference expansion algorithm; marking pixel points which exceed the range of the image gray value after embedding information by using a generalized difference expansion algorithm in an overflow map, compressing the overflow map, and hiding the overflow map, the watermark embedding amount and the auxiliary information of the watermark scrambling times in texture complex blocks of an original carrier image;
and 8: selecting the last k sub-blocks in the sequence of the corresponding image blocks which are not used for embedding the watermark information in the original image I, restoring the sub-blocks to the state without bit plane decomposition, and embedding auxiliary information in each pixel in each selected pixel block by using a differential quantization method;
and step 9: after watermark information is embedded through a generalized difference expansion and difference quantization algorithm, a watermark-containing image I' is generated.
Further, the method for extracting the watermark corresponding to the method for embedding the watermark also comprises a method for extracting the watermark, wherein the method for extracting the watermark comprises the following steps:
STEP 1: the watermark-containing image I' of size M × N (M, N are all integer multiples of 4) is divided into non-overlapping image blocks I of size 4 × 4i”，
STEP 2: computing all pixel blocks I by utilizing smoothness computing methodi"and then steadily ordering the smoothness values from small to large and generating an ordering index information table;
STEP 3: bit-plane decomposition is performed on the original watermark image I ', and according to the smoothness value in STEP2, the top 1/3 block is generated into an image sub-block I ' containing the upper 7 bits 'iThe block arranged at the middle 1/3 is generated into an image sub-block I 'containing the upper 6 bits'iThe block arranged at the end 1/3 is generated into an image sub-block I 'containing the upper 5 bits'i；
STEP 4: restoring the sub-blocks of the last k blocks in the selected sequence to a state without bit plane decomposition, and extracting auxiliary information from each pixel in each selected pixel block by using a difference value quantization method;
STEP 5: extracting the watermark from the sequenced first n blocks by using an inverse generalized difference expansion algorithm according to the auxiliary information extracted by STEP4, wherein the first n blocks remove m image sub-blocks containing abrupt points; restoring watermark information W by Arnold reverse scrambling;
STEP 6: and combining the image I' ″ of the low-order bit plane recovered after the watermark information is extracted with the corresponding high-order bit plane decomposed by the bit plane to obtain an image I, and combining the image I with the image obtained after the auxiliary information is extracted to obtain a final image A.
Further, the specific operation of performing Arnold transformation on the watermark W to obtain W' in step1 is as follows:
wherein, (x, y) is the original pixel coordinate, (x ', y') is the transformed pixel coordinate, M is the image size, c, d are the scrambling times, and c, d are generated randomly.
Further, the specific process of implementing embedding of auxiliary information by using a difference quantization method for each pixel in each selected pixel block in step 8 is as follows:
1) and calculating the original image pixel blocks corresponding to the last k sub blocks in the smoothness value sequencing sequence, and calculating the pixel mean value of each sub block in the block.
Wherein m and n are the row and column size of the sub-block, x1,x2,…,xm×nPixel points contained in the sub-blocks;
2) extracting the maximum pixel value and the minimum pixel value in each sub-block, and embedding auxiliary information by using difference quantization:
2.1) embedding auxiliary information by comparing the minimum pixel value and the average value:
where a denotes the pixel point value to be embedded,
expressing the average value of the sub-block pixel points where the embedded pixel points are located, w expressing embedded binary watermark information, and percent expressing remainder;
2.2) comparing the maximum pixel value with the average value to embed auxiliary information:
where a denotes the pixel point value to be embedded,
the average value of the sub-block pixel points where the embedded pixel points are located is represented, w represents embedded binary watermark information, and% represents remainder.
Further, in the STEP4, the STEP of extracting the auxiliary information by the difference quantization method is to embed the auxiliary information by using the minimum pixel value and then embed the auxiliary information by using the maximum pixel value when embedding the auxiliary information, and then extract the auxiliary information by using the maximum pixel value and then extract the auxiliary information by using the minimum pixel value when extracting the auxiliary information, so that the parity relationship between the minimum pixel value and the parity relationship between the maximum pixel value and the pixel block average value in the image block can be kept consistent before and after embedding the auxiliary information, that is:
where a denotes the pixel point value to be embedded,
the average value of the sub-block pixel points where the embedded pixel points are located is represented, w represents embedded binary watermark information, and% represents remainder.
Further, the specific principle of extracting the watermark from the sorted top n blocks by using the inverse generalized difference extension algorithm in STEP5 is as follows:
when the embedded one-bit watermark information in any pixel pair is 1, the difference value of the obtained new pixel pair is an odd value; if the embedded watermark information is 0, the obtained new pixel pair difference value is an even value; when the original image is restored, if the pixel pair difference value in the watermark image is an odd number, the embedded watermark information is 1, otherwise, the embedded watermark information is 0.
Has the beneficial effects that:
the invention provides a reversible image watermarking algorithm based on bit plane modification decomposition and difference value expansion, aiming at improving the visual quality and the embedding rate of the conventional reversible image watermarking algorithm. First, the divided image blocks are subjected to smoothness calculation by a smoothness calculation algorithm and sorted accordingly. And then performing bit plane decomposition on each selected sliding block, and removing image sub-blocks containing the abrupt point by utilizing multi-scale decomposition. And finally, embedding the scrambled watermark information and auxiliary information into a carrier image by utilizing a generalized difference expansion algorithm and a difference quantization algorithm. The experimental result shows that the algorithm has high embedding rate, higher visual quality and certain advantages compared with other algorithms, and can realize the complete recovery of the original image.
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FIG. 1 is a flow chart of the algorithm watermark embedding of the present invention;
FIG. 2 is a graph of a test used in the algorithm of the present invention, wherein a is a Lena graph, b is a Barbara graph, c is a Baboon graph, and d is a Pepper graph;
FIG. 3 is a watermark image used in the experiment of the present invention;
FIG. 4 is an exploded view of the original carrier image bit plane according to the present invention;
FIG. 5 is an original image and a lower 6 bit-plane reconstructed image according to the present invention;
FIG. 6 is a comparison graph of the experimental visual effect of the algorithm of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference value expansion, which comprises a watermarking embedding method and comprises the following steps:
step 1: performing Arnold transformation on the watermark W to obtain W ', and converting the transformed watermark W' into a one-dimensional binary sequence.
The specific operation of performing Arnold transformation on the watermark W to obtain W' is as follows:
wherein, (x, y) is the original pixel coordinate, (x ', y') is the transformed pixel coordinate, M is the image size, c, d are the scrambling times, and c, d are generated randomly.
Step 2: an original image I of size M × N (M, N are all integer multiples of 4) is divided into blocks I of size 4 × 4 which do not overlap with each otheri，
And step 3: all pixel blocks I are calculated using smoothness calculation methods in the literature (Zhengwei Zhang, Lifa Wu, Yunyang Yan, Shaozhang Xiao, He Sun. an Improved Reversible Image watermarming Algorithm Based on Difference Expansion. International Journal of distributed Sensor Networks,2017,13(1):1-15.)iAnd stably sorting the smoothness values from small to large to build a sorting index information table.
And 4, step 4: for all image blocks IiPerforming bit plane decomposition, and generating image sub-blocks containing 7 high bits from the image blocks correspondingly arranged at the top 1/3 according to the smoothness value in step3
Generating image sub-blocks containing 6 high bits from the image blocks arranged at the middle 1/3
Generating image sub-blocks containing 5 high bits corresponding to the next-ranked 1/3 image blocks
。
For the corresponding top-ranked block of 1/3, assuming that the two pixel values are 90and 93, the upper 7 bits (0101101, 0101110) of the two pixels are taken for difference expansion, and assuming that the embedded watermark is 1, the two newly generated pixel values are 45 and 46, respectively. The two watermarked pixel values are 90and 93, respectively, by and above the lowest bit of the original two pixel values. Assuming that the embedded watermark is 0, the new two pixel values generated are 44 and 46, respectively, and the two watermarked pixel values pass through and are the lowest bits of the original two pixel values, 88 and 93, respectively.
And (3) carrying out bit plane decomposition on the image, wherein the original carrier image is an 8-bit gray level image, dividing the original carrier image into 8 bit planes, and selecting the lower 6 bit planes to combine together to form a new image, as shown in fig. 4.
After removing the top two bit planes, the resulting image containing only the lower 6 bit planes is shown in fig. 5.
And 5: for selected image sub-blocks
Image sub-blocks with sharp points are deleted by multi-scale decomposition algorithms (ZHENGWEI ZHANG, He Sun, Shangbing Gao, Shenghua jin. Self-recovery Image Watermarking Algorithm. plos One,2018, 13(6): e 0199143).
Step 6: according to the requirement of watermark capacity embedding, n pixel sub-blocks arranged at the front in the sequence are selected, m selected image sub-blocks with the sharp points removed are removed, watermark information is embedded into the n-m image blocks, and simultaneously, the sequence number of the image sub-blocks containing the sharp points is recorded.
And 7: for any selected sub-block
(i is more than or equal to 0and less than or equal to n) watermark embedding is carried out by utilizing a generalized difference expansion algorithm; and marking the pixel points which exceed the range of the image gray value after the information is embedded by using the generalized difference expansion algorithm in the overflow graph, compressing the overflow graph, and hiding the overflow graph and auxiliary information such as the watermark embedding amount, the watermark scrambling times B (c and d) and the like in the texture complex blocks of the original carrier image.
After the watermark is embedded by the generalized difference expansion algorithm, overflow can be generated, and the overflow processing of the overflow can have a great influence on the embedding capacity of the watermark. In the invention, overflow points generated after the watermark is embedded by the generalized difference expansion algorithm are marked in the image with the same size as the original image, and the generated positioning graph is a binary image marked by 0and 1.
And 8: for the corresponding image block which is not used for embedding the watermark information in the original image I, namely the original pixel block with higher texture complexity, the last k sub-blocks in the sequence are selected and restored to the state without bit plane decomposition, and at the moment, each pixel value in the block is represented by 8-bit binary number. And embedding auxiliary information by utilizing a difference value quantization method for each pixel in each selected pixel block.
The specific process is as follows:
1) and calculating the original image pixel blocks corresponding to the last k sub blocks in the smoothness value sequencing sequence, and calculating the pixel mean value of each sub block in the block.
Wherein m and n are the row and column size of the sub-block, x1,x2,…,xm×nPixel points contained in the sub-blocks;
2) extracting the maximum pixel value and the minimum pixel value in each sub-block, and embedding auxiliary information by using difference quantization:
2.1) embedding auxiliary information by comparing the minimum pixel value and the mean value:
where a denotes the pixel point value to be embedded,
expressing the average value of the sub-block pixel points where the embedded pixel points are located, w expressing embedded binary watermark information, and percent expressing remainder;
2.2) comparing the maximum pixel value with the average value to embed auxiliary information:
where a represents the pixel point value to be embedded，
And the average value of the sub-block pixel points where the embedded pixel points are located is represented, w represents the embedded binary watermark information, and% represents the remainder.
And step 9: after watermark information is embedded through a generalized difference expansion and difference quantization algorithm, a watermark-containing image I' is generated.
The watermark embedding method also comprises a watermark extracting method, and the watermark information is supposed to be embedded into any pixel pair (x, y) in the original image through difference value expansion. If the embedded watermark information is 1, the newly generated pixel pair (a, b) has the following values:
thus a-b ═ 2x-2y + 1.
So when the embedded one-bit watermark information is 1 in any pixel pair, the resulting new pixel pair difference value is an odd value. Similarly, if the embedded watermark information is 0, the obtained new pixel pair difference value is an even value. By this method, when we restore the original carrier image, if the difference between the pixel pair (a, b) in the watermark image is odd, it represents that the embedded watermark information is 1, otherwise it is 0. By this method, watermark information can be extracted.
Therefore, the watermark extraction method includes the steps of:
STEP 1: the watermark-containing image I' of size M × N (M, N are all integer multiples of 4) is divided into non-overlapping image blocks I of size 4 × 4i”，
STEP 2: computing using a smoothness computation methodAll pixel blocks Ii"and then steadily sort the smoothness values from small to large and generate a sorted index information table.
STEP 3: bit-plane decomposition is performed on the original watermark image I ', and according to the smoothness value in STEP2, the top 1/3 block is generated into an image sub-block I ' containing the upper 7 bits 'iThe block arranged at the middle 1/3 is generated into an image sub-block I 'containing the upper 6 bits'iThe block arranged at the end 1/3 is generated into an image sub-block I 'containing the upper 5 bits'i。
STEP 4: and recovering the sub-blocks of the last k blocks in the selected sequence to a state without bit plane decomposition, and extracting auxiliary information from each pixel in each selected pixel block by using a difference value quantization method.
The difference quantization method is used for extracting the auxiliary information, namely when the auxiliary information is embedded, the auxiliary information is embedded by using the minimum pixel value, and then the auxiliary information is embedded by using the maximum pixel value, when the auxiliary information is extracted, the auxiliary information is extracted by using the maximum pixel value, and then the auxiliary information is extracted by using the minimum pixel value, so that the parity relationship between the minimum pixel value and the parity relationship between the maximum pixel value and the pixel block average value in the image block can be kept consistent before and after the auxiliary information is embedded, namely:
where a denotes the pixel point value to be embedded,
the average value of the sub-block pixel points where the embedded pixel points are located is represented, w represents embedded binary watermark information, and% represents remainder.
STEP 5: extracting watermarks from the sequenced first n blocks by using an inverse generalized difference extension algorithm according to the auxiliary information extracted by STEP4, wherein the first n blocks remove m image sub-blocks containing sharp points; and recovering the watermark information W through Arnold descrambling.
STEP 6: and combining the image I' ″ of the low-order bit plane recovered after the watermark information is extracted with the corresponding high-order bit plane decomposed by the bit plane to obtain an image I, and combining the image I with the image obtained after the auxiliary information is extracted to obtain a final image A.
The invention can completely recover the original carrier image after extracting the watermark, and realizes the reversibility of the algorithm. The Correlation coefficient (NC) between the original image and the carrier image recovered after extraction of the watermark can be used for the measurement.
TABLE 1 integrity assessment Table without attack
Table 1 shows the completeness of the results for 4 different types of watermark images based on the inventive algorithm without any attack. The result shows that the algorithm can completely recover the original image under the condition of not being attacked. This indicates that the algorithm is reversible.
The original carrier image was blocked by 4 × 4 and compared between PSNR and SSIM using the algorithm of the present invention and algorithm one (Hala S.El-sayed, S.F.El-Zoghdy, Osama S.Faragallah.Adaptation Difference Expansion-Based conversion Data Hiding Scheme for Digital images. Arabidopsis Journal for Science and Engineering,2016,41: 1091-.
TABLE 2 Algorithm visual quality analysis
After watermark information is embedded into the 4 original carrier images in the image of the FIG. 2, the PSNR value of the algorithm can be up to 59.35dB at most, and compared with the algorithm, the algorithm has better invisibility. Meanwhile, compared with the first algorithm, the SSIM is higher. As can be seen from table 2, the algorithm of the present invention has better PSNR and SSIM values than the algorithm one when embedding the same amount of watermark information. This also demonstrates the better visual quality of the algorithms studied by the present invention. The specific visual effect and watermark extraction effect are shown in fig. 6.
From these image observations, the human eye does not perceive the presence of watermark information in the watermark image. The watermark-containing image has better visual effect, the corresponding PSNR value shows that the algorithm has better non-perceptibility to different types of images, and the average PSNR value is up to 58.42 dB.
As can be seen from Table 2 and FIG. 6, the algorithm of the present invention has better visual perception for images of different texture types.
In order to estimate the maximum watermark embedding capacity of the original image, the present invention requires watermark embedding for all blocks in the original image (except for the found blocks containing sharp points).
Table 3 comparison of watermark algorithm performance
In table 3, 10,30,70,90and 100% refer to the ratio of the capacity of the watermark to be embedded to the maximum embedding capacity. PSNR was used to evaluate the visual quality of the watermarked image at 10,30,70,90and 100% of the maximum embedding capacity. As can be seen from Table 3 above, the Reversible watermarking algorithm proposed by the present invention is superior to algorithm two (Zhengwei Zhang, Lifa Wu, Yunyang Yan, et al. An improved Reversible image watermarking algorithm) in terms of payload capacity, algorithm two (Zhengwei Zhang, Lifa Wu, Yunyang Yan, et al. An improved Reversible watermark algorithm Based on Difference evaluation. International Journal of distributed Sensor Networks,2017,13(1):1-15.) and algorithm three (Hala S.El-layer, S.F.El.Zoghdy, Osama S.Faragallah.Adaptive Difference-Based Reversible mapping Scheme for Digital image Data and algorithm III. environmental Journal for Science, Engineering, En41: 1. PSN 109, and good SSIR 109values at the same time. The results presented here show that the reversible watermarking technique based on difference expansion and bit-plane decomposition proposed by the present invention greatly increases the payload capacity while still maintaining good visual quality of the watermarked image.
The performance of the inventive algorithm was compared with the performance of the fourth (solvent M M, Hassanien A E, Onsi H M. additive water marking adaptive present square particulate optimization. New Computing & Applications,2016,27(2):1-13.), fifth (Yin Z, Niu X, Zhou Z, et al. improved Reversible Image evaluation scheme. cognitive Computation,2016,8(5):1-10.) and sixth (bearing S, Jafar I, bearing H. An effect multi-prediction Reversible algorithm. 12. 1-10.) algorithms and sixth (bearing S, music I. 2017. 11. 12. 1-2. expression).
TABLE 4 Peak SNR and maximum payload comparison of different algorithms
The fourth algorithm selects four subgraphs to embed data, and an embedding parameter L is set to be 0; algorithm five-selection bilinear interpolation method, parameter T1And T0The values of (c) are set to 8 and 60; the sixth algorithm is to embed the watermark on the basis of the prediction difference expansion. The invention adopts a difference expansion algorithm to embed the watermark and sets the block size to be 4 multiplied by 4. Simulation results show that the performance of the algorithm is superior to that of algorithm four, algorithm five and algorithm six. Compared with the fourth algorithm and the fifth algorithm, the visual quality and the maximum load of the algorithm are improved for the simple texture image. For images with complex textures, the performance of the algorithm is slightly reduced, but the performance of the algorithm can be improved by adjusting parameters. This algorithm produces more prediction error bits than algorithm six, can make more efficient use of these bits, and can be embedded in a larger capacity. For example, for the test image Lena, if the block size is set to 4 × 4, the obtained watermark image quality is 36.47dB, and the maximum payload is 234432bit, which is slightly better than the other three algorithms. The maximum capacity of embedding using this algorithm is much higher than other algorithms, while maintaining good visual quality.
The above embodiments are merely illustrative of the technical concepts and features of the present invention, and the purpose of the embodiments is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (6)
1. A reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion is characterized by comprising a watermarking embedding method, and the reversible image watermarking algorithm comprises the following steps:
step 1: performing Arnold transformation on the watermark W to obtain W ', and converting the transformed watermark W' into a one-dimensional binary sequence;
step 2: an original image I of size M × N (M, N are all integer multiples of 4) is divided into blocks I of size 4 × 4 which do not overlap with each otheri，
And step 3: calculating all image blocks I by utilizing smoothness calculation methodiThe smoothness values are stably sorted from small to large, and a sorting index information table is established;
and 4, step 4: for all image blocks IiPerforming bit-plane decomposition, and generating image sub-block I 'containing 7 high bits from the image block corresponding to the first 1/3 according to the smoothness value in step 3'iGenerating an image sub-block I 'containing the upper 6 bits from the image block correspondingly arranged at the middle 1/3'iGenerating image sub-block I 'containing 5 high bits from the corresponding image block arranged at the last 1/3'i；
And 5: for selected image subblock I'iDeleting the image subblocks with the sharp points by a multi-scale decomposition algorithm;
step 6: according to the watermark capacity embedding requirement, selecting n pixel sub-blocks arranged at the front in the sequence, removing m selected image sub-blocks with the sharp points removed, embedding watermark information into the n-m image blocks, and recording the sequencing sequence number of the image sub-blocks containing the sharp points;
and 7: to any selected sub-block I'i(i is more than or equal to 0and less than or equal to n) watermark embedding is carried out by utilizing a generalized difference expansion algorithm; marking pixel points which exceed the range of the gray value of the image after embedding information by using a generalized difference expansion algorithm in the overflow image, compressing the overflow image, and hiding the overflow image, the watermark embedding amount and the auxiliary information of the watermark scrambling times in the texture complex block of the original carrier image;
and 8: selecting the last k sub-blocks in the sequence of the corresponding image blocks which are not used for embedding the watermark information in the original image I, recovering the state of the image blocks without bit plane decomposition, and embedding auxiliary information into each pixel in each selected pixel block by using a differential quantization method;
and step 9: after watermark information is embedded through a generalized difference expansion and difference quantization algorithm, a watermark-containing image I' is generated.
2. The reversible image watermarking algorithm based on bit-plane decomposition and difference expansion as claimed in claim 1, further comprising a watermark extraction method corresponding to the watermark embedding method, wherein the watermark extraction method comprises the steps of:
STEP 1: dividing a watermark-containing image I' of size M × N (M, N are integral multiples of 4), into image blocks I of size 4 × 4 which do not overlap each otheri”，
STEP 2: computing all pixel blocks I by utilizing smoothness computing methodiThe smoothness values are then stably sorted from small to large and a sorting index information table is generated;
STEP 3: bit-plane decomposition is performed on the original watermark image I ', and according to the smoothness value in STEP2, the top 1/3 block is generated into an image sub-block I ' containing the upper 7 bits 'iThe block arranged at the middle 1/3 is generated into an image sub-block I 'containing the upper 6 bits'iThe block arranged at the end 1/3 is generated into an image sub-block I 'containing the upper 5 bits'i；
STEP 4: restoring the last k sub-blocks in the selected sequence to the state without bit plane decomposition, and extracting auxiliary information from each pixel in each selected pixel block by using a difference value quantization method;
STEP 5: extracting watermarks from the sequenced first n blocks by using an inverse generalized difference extension algorithm according to the auxiliary information extracted by STEP4, wherein the first n blocks remove m image sub-blocks containing sharp points; restoring watermark information W by Arnold reverse scrambling;
STEP 6: and combining the image I' ″ of the low-order bit plane recovered after the watermark information is extracted with the corresponding high-order bit plane decomposed by the bit plane to obtain an image I, and combining the image I with the image obtained after the auxiliary information is extracted to obtain a final image A.
3. The invertible image watermarking algorithm based on carry-over plane decomposition and difference expansion as claimed in claim 1, wherein the specific operation of performing Arnold transformation on the watermark W to obtain W' in step1 is as follows:
wherein, (x, y) is the original pixel coordinate, (x ', y') is the transformed pixel coordinate, M is the image size, c, d are the scrambling times, and c, d are generated randomly.
4. The reversible image watermarking algorithm based on bit-plane decomposition and difference expansion as claimed in claim 1, wherein the specific process of embedding the auxiliary information by using the difference quantization method for each pixel in each selected pixel block in the step 8 is as follows:
1) and calculating the original image pixel blocks corresponding to the last k sub blocks in the smoothness value sequencing sequence, and calculating the pixel mean value of each sub block in the block.
Wherein m and n are the row and column size of the sub-block, x1,x2,…,xm×nPixel points contained in the sub-blocks;
2) extracting the maximum pixel value and the minimum pixel value in each sub-block, and embedding auxiliary information by using difference quantization:
2.1) embedding auxiliary information by comparing the minimum pixel value and the mean value:
where a denotes the pixel point value to be embedded,
expressing the average value of the sub-block pixel points where the embedded pixel points are located, w expressing embedded binary watermark information, and percent expressing remainder;
2.2) comparing the maximum pixel value with the average value to embed auxiliary information:
where a denotes the pixel point value to be embedded,
the average value of the sub-block pixel points where the embedded pixel points are located is represented, w represents embedded binary watermark information, and% represents remainder.
5. The reversible image watermarking algorithm based on improved bit-plane decomposition and difference expansion as claimed in claim 2, wherein the STEP4 is characterized in that the STEP of extracting the auxiliary information by the difference quantization method is to embed the auxiliary information by using the minimum pixel value and then embed the auxiliary information by using the maximum pixel value when embedding the auxiliary information, and then extract the auxiliary information by using the maximum pixel value and then extract the auxiliary information by using the minimum pixel value when extracting the auxiliary information, so as to keep the parity relationship between the minimum pixel value and the average pixel block value in the image block consistent before and after embedding the auxiliary information, that is:
where a denotes the pixel point value to be embedded,
the average value of the sub-block pixel points where the embedded pixel points are located is represented, w represents embedded binary watermark information, and% represents remainder.
6. The reversible image watermarking algorithm based on improved bit-plane decomposition and difference expansion as claimed in claim 2, wherein the specific principle of extracting the watermark from the ordered top n blocks by using the inverse generalized difference expansion algorithm in STEP5 is as follows:
when one bit of watermark information embedded in any pixel pair is 1, the difference value of the obtained new pixel pair is an odd value; if the embedded watermark information is 0, the obtained new pixel pair difference value is an even value; when the original image is restored, if the pixel pair difference value in the watermark image is an odd number, the embedded watermark information is 1, otherwise, the embedded watermark information is 0.
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