CN114663268B - Reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion - Google Patents
Reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion Download PDFInfo
- Publication number
- CN114663268B CN114663268B CN202210180641.4A CN202210180641A CN114663268B CN 114663268 B CN114663268 B CN 114663268B CN 202210180641 A CN202210180641 A CN 202210180641A CN 114663268 B CN114663268 B CN 114663268B
- Authority
- CN
- China
- Prior art keywords
- image
- watermark
- blocks
- embedded
- pixel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 97
- 230000002441 reversible effect Effects 0.000 title claims abstract description 34
- 238000000354 decomposition reaction Methods 0.000 title claims abstract description 33
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000013139 quantization Methods 0.000 claims abstract description 18
- 238000000605 extraction Methods 0.000 claims abstract description 9
- 238000012163 sequencing technique Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 7
- 230000009466 transformation Effects 0.000 claims description 6
- 230000000007 visual effect Effects 0.000 abstract description 14
- 238000011084 recovery Methods 0.000 abstract description 4
- 230000016776 visual perception Effects 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 4
- 230000003044 adaptive effect Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000013507 mapping Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 235000002566 Capsicum Nutrition 0.000 description 1
- 241001504519 Papio ursinus Species 0.000 description 1
- 239000006002 Pepper Substances 0.000 description 1
- 235000016761 Piper aduncum Nutrition 0.000 description 1
- 235000017804 Piper guineense Nutrition 0.000 description 1
- 244000203593 Piper nigrum Species 0.000 description 1
- 235000008184 Piper nigrum Nutrition 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000969 carrier Substances 0.000 description 1
- 230000001149 cognitive effect Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
- G06T1/0092—Payload characteristic determination in a watermarking scheme, e.g. number of bits to be embedded
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L2209/00—Additional information or applications relating to cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
- H04L2209/60—Digital content management, e.g. content distribution
- H04L2209/608—Watermarking
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Editing Of Facsimile Originals (AREA)
- Image Processing (AREA)
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-block containing the abrupt points by utilizing multi-scale decomposition. And finally embedding the scrambled watermark information and auxiliary information into the carrier image by using a generalized difference value expansion algorithm and a difference value 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, higher 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 expansion.
Background
Digital watermarking has received a great deal of attention as an effective means of copyright protection. When a certain amount of watermarks are embedded by using the digital watermarking technology, the original image can generate certain distortion. However, for some special types of carriers, it is required that the original carrier image can be recovered nondestructively after the embedded information is extracted, so that the reversible digital watermark is rapidly developed. The difference with the digital watermarking technology is that the reversible watermarking technology can recover the original carrier image without distortion after the embedded information is extracted, so that the method can be applied to the fields with higher requirements on image quality, such as military, remote sensing, medical treatment and the like.
When embedding watermark information, distortion is inevitably generated to the original image. Therefore, li et al propose a reversible information hiding algorithm based on predictive differential expansion to reduce image distortion, which improves the visual quality of the hidden image but has a low embedding capacity, and the larger the image block, the lower the embedding capacity.
For difference expansion, pixel overflow locations need to be located and compressed, which is an important factor affecting the embedding rate. Eliminating pixel overflow caused by embedding the watermark through difference expansion has important significance in improving the performance of the watermark algorithm. In order to avoid pixel overflow, the pixel value is adjusted to a certain range and the adjusted pixel position is recorded, and the embedding technology is unique in terms of overflow processing, but still needs to embed compression positioning mapping.
And combining a reversible watermarking algorithm of the difference expansion and reversible contrast map, and forming a difference expansion pixel pair and a reversible contrast image pixel pair for 4 pixels in each block, wherein watermarks can be embedded in the two pixel pairs. The reversible contrast image pixel pair is mainly used for embedding a small amount of additional information to replace a positioning map, and the embedding capacity is greatly improved. However, there is a half-pixel pair in the algorithm, which adopts reversible contrast mapping transformation, and the image quality is more degraded. A reversible watermark embedding method based on adjacent pixel difference, which adjusts pixel values before embedding watermark, but the algorithm still needs to embed a small position diagram. The method is characterized in that the overflow processing is performed, and a compressed positioning map is needed to be embedded.
Disclosure of Invention
The invention aims to: aiming at the problems in the prior art, the invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion, which has high embedding rate and higher visual quality and can realize the complete recovery of an original image.
The technical scheme is as follows: the invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference 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: the original image I with the size of M multiplied by N (M, N is an integer multiple of 4) is divided into image blocks I i which are not overlapped with each other and have the size of 4 multiplied by 4,
Step 3: calculating the smoothness value of all pixel blocks I i by using a smoothness calculation method, and stably sequencing the smoothness value from small to large to establish a sequencing index information table;
Step 4: bit plane decomposition is carried out on all image blocks I i, and the image blocks which are correspondingly arranged in the front 1/3 are generated into image sub-blocks containing high 7 bits according to the smoothness value of the step 3 Generating image subblocks containing high 6 bits from image blocks correspondingly arranged in the middle 1/3Generating image subblocks containing upper 5 bits from the image blocks correspondingly arranged at the rear 1/3 of the image blocks；
Step 5: for selected image sub-blocksDeleting the image sub-block with the abrupt point through 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 image sub-blocks with the abrupt points removed, embedding watermark information into n-m image blocks, and simultaneously recording the sequence number of the image sub-blocks containing the abrupt points;
Step 7: for any selected sub-block (I is more than or equal to 0 and less than or equal to n) utilizing a generalized difference expansion algorithm to embed the watermark; for pixel points which can exceed the gray value range of the image after information is embedded by using a generalized difference expansion algorithm, marking in an overflow image, compressing the overflow image, and hiding the overflow image, watermark embedding amount and watermark scrambling frequency auxiliary information into a texture complex block of an original carrier image;
Step 8: for the corresponding image blocks which are not used for embedding watermark information in the original image I, selecting the k sub-blocks after the sequence, recovering to the state when bit plane decomposition is not carried out, and embedding auxiliary information for each pixel in each selected pixel block by using a difference quantization method;
Step 9: watermark information is embedded through generalized difference expansion and a difference quantization algorithm, and then a watermark image I is generated.
Further, the watermark embedding method also comprises a watermark extraction method, and the watermark extraction method comprises the following steps:
STEP1: a watermark image I "of size M x N (M, N are integer multiples of 4) is block-divided into non-overlapping image blocks I i" of size 4 x4,
STEP2: calculating the smoothness values of all pixel blocks I i' by using a smoothness calculation method, and then stably sequencing the smoothness values from small to large to generate a sequencing index information table;
STEP3: performing bit plane decomposition on an original watermark image I ', generating an image subblock I' i containing high 7 bits from the blocks arranged in the front 1/3, an image subblock I 'i containing high 6 bits from the blocks arranged in the middle 1/3, and an image subblock I' i containing high 5 bits from the blocks arranged in the rear 1/3 according to the smoothness value in STEP 2;
STEP4: recovering the k sub-blocks after the selection sequence to a state when bit plane decomposition is not performed, and extracting auxiliary information from each pixel in each selected pixel block by using a difference value quantization method;
STEP5: extracting watermark from the first n ordered blocks by using an inverse generalized difference expansion algorithm according to the auxiliary information extracted by STEP4, wherein m image sub-blocks containing abrupt points are removed from the first n blocks; recovering watermark information W through Arnold reverse scrambling;
STEP6: and combining the image I', which is recovered after extracting the watermark information, of the low-level bit plane with the corresponding high-level bit plane decomposed by the bit plane to obtain an image I, and combining the image I with the image obtained after extracting the auxiliary information to obtain a final image A.
Further, the specific operation of performing Arnold transformation on the watermark W in the step 1 to obtain W' is as follows:
wherein, (x, y) is the original pixel coordinates, (x ', y') is the transformed pixel coordinates, M is the image size, c and d are the scrambling times, and c and d are randomly generated.
Further, 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 an original image pixel block corresponding to the 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 sizes of the divided sub-blocks, respectively, and x 1,x2,…,xm×n is the pixel point contained in the sub-block;
2) Extracting the maximum pixel value and the minimum pixel value in each sub-block, and embedding auxiliary information by utilizing difference quantization:
2.1 Using the minimum pixel value and the mean value to compare the embedded auxiliary information:
Wherein a represents the pixel value to be embedded, Representing the average value of the sub-block pixel points where the embedded pixel points are located, w represents embedded binary watermark information, and% represents the remainder;
2.2 Maximum pixel value and average value for comparison embedded auxiliary information:
Wherein a represents the pixel value to be embedded, Representing the average value of the sub-block pixel points where the embedded pixel points are located, w represents embedded binary watermark information, and% represents the remainder.
Further, when the auxiliary information is extracted by the difference quantization method in STEP4, the auxiliary information is first embedded by using the minimum pixel value and then embedded by using the maximum pixel value, and when the auxiliary information is extracted, the auxiliary information is extracted by using the maximum pixel value and then extracted by using the minimum pixel value, so that the parity relationship between the minimum pixel value and the average value of the maximum pixel value and the pixel block in the image block can be kept consistent before and after the auxiliary information is embedded, namely:
Wherein a represents the pixel value to be embedded, Representing the average value of the sub-block pixel points where the embedded pixel points are located, w representing the embedded binary watermark information, and% representing the remainder.
Further, the specific principle of extracting the watermark from the ordered first n blocks by using the inverse generalized difference expansion algorithm in STEP5 is as follows:
When the one-bit watermark information embedded in any pixel pair is 1, the obtained new pixel pair difference value 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 odd, the embedded watermark information is 1, otherwise, the embedded watermark information is 0.
The beneficial effects are that:
The invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion in order to improve 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 in this order. And then carrying out bit plane decomposition on each selected smooth block, and removing the image sub-block containing the abrupt points by utilizing multi-scale decomposition. And finally embedding the scrambled watermark information and auxiliary information into the carrier image by using a generalized difference value expansion algorithm and a difference value quantization algorithm. Experimental results show that the algorithm has high embedding rate and higher visual quality, can realize complete recovery of an original image, and has certain advantages compared with other algorithms.
Drawings
FIG. 1 is a flow chart of the algorithm watermark embedding of the present invention;
FIG. 2 is a graph of the test used in the algorithm of the present invention, where a is Lena, b is Barbara, c is Baboon, and d is Pepper;
FIG. 3 is a watermark image used in the experiments of the present invention;
FIG. 4 is a bit-plane exploded view of the original carrier image of the present invention;
FIG. 5 is an original image and a low 6 bit-plane reconstruction of the present invention;
fig. 6 is a graph showing the comparison of the experimental visual effects of the algorithm of the invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
The invention provides a reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion, which comprises a watermarking embedding method, and comprises the following steps:
step 1: arnold transformation is performed on the watermark W to obtain W ', and the transformed watermark W' is converted into a one-dimensional binary sequence.
The specific operation of obtaining W' by Arnold transformation of the watermark W is as follows:
wherein, (x, y) is the original pixel coordinates, (x ', y') is the transformed pixel coordinates, M is the image size, c and d are the scrambling times, and c and d are randomly generated.
Step 2: the original image I with the size of M multiplied by N (M, N is an integer multiple of 4) is divided into image blocks I i which are not overlapped with each other and have the size of 4 multiplied by 4,
Step 3: the smoothness value of all pixel blocks I i is calculated by using the smoothness calculation method in literature (Zhengwei Zhang,Lifa Wu,Yunyang Yan,Shaozhang Xiao,He Sun.An Improved Reversible Image Watermarking Algorithm Based on Difference Expansion.International Journal ofDistributed Sensor Networks,2017,13(1):1-15.), and is stably sorted from small to large, and a sorting index information table is established.
Step 4: bit plane decomposition is carried out on all image blocks I i, and the image blocks which are correspondingly arranged in the front 1/3 are generated into image sub-blocks containing high 7 bits according to the smoothness value of the step 3Generating image subblocks containing high 6 bits from image blocks correspondingly arranged in the middle 1/3Generating image subblocks containing upper 5 bits from the image blocks correspondingly arranged at the rear 1/3 of the image blocks。
For the block corresponding to the first 1/3 row, assume that the two pixel values are 90 and 93, take the upper 7 bits (0101101, 0101110) of the two pixels for difference expansion, and assume that the embedded watermark is 1, then the two newly generated pixel values are 45 and 46, respectively. By concatenating the least significant bits of the original two pixel values, the two watermarked pixel values are 90 and 93, respectively. Assuming that the embedded watermark is 0, the new two pixel values generated are 44 and 46, respectively, and the two watermarked pixel values are 88 and 93, respectively, by concatenating the least significant bits of the original two pixel values.
The image is subjected to bit plane decomposition, the original carrier image is an 8-bit gray scale image, the original carrier image is divided into 8 bit planes, and the lower 6 bit planes are selected to be combined together to form a new image, as shown in fig. 4.
After the removal of the top two bitplanes, the resulting image is shown in fig. 5 with only the lower 6 bitplanes.
Step 5: for selected image sub-blocksImage sub-blocks with abrupt points are deleted by the multi-scale decomposition algorithm (Zhengwei Zhang,He Sun,Shangbing Gao,Shenghua Jin.Self-recovery Reversible Image Watermarking Algorithm.Plos One,2018,13(6):e0199143).
Step 6: according to the watermark capacity embedding requirement, selecting n pixel sub-blocks arranged in front in the sequence, removing the selected m image sub-blocks with the abrupt points removed, embedding watermark information into the n-m image blocks, and simultaneously recording the sequence number of the image sub-blocks containing the abrupt points.
Step 7: for any selected sub-block(I is more than or equal to 0 and less than or equal to n) utilizing a generalized difference expansion algorithm to embed the watermark; and labeling pixel points which can exceed the gray value range of the image after information is embedded by using a generalized difference expansion algorithm in an overflow image, compressing the overflow image, and hiding the pixel points, watermark embedding amount, watermark scrambling times B (c and d) and other auxiliary information in a texture complex block of an original carrier image.
Overflow may occur after the watermark is embedded by the generalized difference expansion algorithm, and the overflow processing may have a significant impact on the embedding capacity of the watermark. In the invention, overflow points generated after watermark embedding by a generalized difference expansion algorithm are marked in an image with the same size as an original image, and a generated positioning map is a binary image marked with 0 and 1.
Step 8: and selecting the k sub-blocks after the original image I, which are not used for embedding watermark information, namely the original pixel blocks with higher texture complexity, and recovering to a state when bit plane decomposition is not performed, wherein each pixel value in the blocks is represented by 8-bit binary numbers. And embedding auxiliary information by using a difference value quantization method for each pixel in each selected pixel block.
The specific process is as follows:
1) And calculating an original image pixel block corresponding to the 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 sizes of the divided sub-blocks, respectively, and x 1,x2,…,xm×n is the pixel point contained in the sub-block;
2) Extracting the maximum pixel value and the minimum pixel value in each sub-block, and embedding auxiliary information by utilizing difference quantization:
2.1 Using the minimum pixel value and the mean value to compare the embedded auxiliary information:
Wherein a represents the pixel value to be embedded, Representing the average value of the sub-block pixel points where the embedded pixel points are located, w represents embedded binary watermark information, and% represents the remainder;
2.2 Maximum pixel value and average value for comparison embedded auxiliary information:
Wherein a represents the pixel value to be embedded, Representing the average value of the sub-block pixel points where the embedded pixel points are located, w represents embedded binary watermark information, and% represents the remainder.
Step 9: watermark information is embedded through generalized difference expansion and a difference quantization algorithm, and then a watermark image I is generated.
The watermark embedding method also comprises a watermark extraction method, and the watermark information is embedded by the difference expansion on any pixel pair (x, y) in the original image. 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 new pixel pair difference value is an odd value. Similarly, if the embedded watermark information is 0, the new pixel pair difference value obtained is an even value. By this method, when we restore the original carrier image, if the difference between the pixel pairs (a, b) in the watermark image is odd, it represents that the embedded watermark information is 1, otherwise it is 0. By this method, the watermark information can be extracted.
Therefore, the watermark extraction method comprises the steps of:
STEP1: a watermark image I "of size M x N (M, N are integer multiples of 4) is block-divided into non-overlapping image blocks I i" of size 4 x4,
STEP2: and calculating the smoothness values of all pixel blocks I i' by using a smoothness calculation method, and then stably ordering the smoothness values from small to large and generating an ordering index information table.
STEP3: the original watermark image I 'is subjected to bit plane decomposition, according to the size of the smoothness value in STEP2, the blocks arranged in the front 1/3 are generated into an image subblock I' i containing the high 7 bits, the blocks arranged in the middle 1/3 are generated into an image subblock I 'i containing the high 6 bits, and the blocks arranged in the back 1/3 are generated into an image subblock I' i containing the high 5 bits.
STEP4: and recovering the k sub-blocks after the selection sequence to a state when bit plane decomposition is not performed, and extracting auxiliary information from each pixel in each selected pixel block by using a difference quantization method.
When the auxiliary information is extracted by the difference quantization method, the auxiliary information is embedded by utilizing the minimum pixel value, and then the auxiliary information is embedded by utilizing the maximum pixel value, and when the auxiliary information is extracted, the auxiliary information is extracted by utilizing the maximum pixel value, and then the auxiliary information is extracted by utilizing the minimum pixel value, so that the parity relation between the minimum pixel value and the average value of the maximum pixel value and the pixel block in the image block can be kept consistent before and after the auxiliary information is embedded, namely:
Wherein a represents the pixel value to be embedded, Representing the average value of the sub-block pixel points where the embedded pixel points are located, w represents embedded binary watermark information, and% represents the remainder.
STEP5: extracting watermark from the first n ordered blocks by using an inverse generalized difference expansion algorithm according to the auxiliary information extracted by STEP4, wherein m image sub-blocks containing abrupt points are removed from the first n blocks; and recovering the watermark information W through Arnold anti-scrambling.
STEP6: and combining the image I', which is recovered after extracting the watermark information, of the low-level bit plane with the corresponding high-level bit plane decomposed by the bit plane to obtain an image I, and combining the image I with the image obtained after extracting the auxiliary information 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 (Normalized Correlation, NC) of the original image and the carrier image recovered after watermark extraction can be measured.
Table 1 integrity assessment table without attack
Table 1 shows the integrity of the results of 4 different types of watermark images without any attack based on the algorithm of the present invention. The result shows that the algorithm of the invention can completely restore the original image without being attacked. This indicates that the algorithm is reversible.
After 4 x4 segmentation of the original carrier image, a comparison of PSNR and SSIM was performed using the algorithm of the present invention with algorithm one (Hala S.El-sayed,S.F. El-Zoghdy,Osama S.Faragallah.Adaptive Difference Expansion-Based Reversible Data Hiding Scheme for Digital Images.Arabian Journal for Science and Engineering,2016,41:1091-1107.), as shown in table 2.
Table 2 algorithmic visual quality analysis
After watermark information is embedded in 4 original carrier images in the algorithm of the invention aiming at the figure 2, the PSNR value of the algorithm can reach 59.35dB, and the algorithm has better invisibility compared with the algorithm I. While its SSIM is also higher than algorithm one. It can be seen from table 2 that the algorithm of the present invention has better PSNR and SSIM values than algorithm one when embedding the same amount of watermark information. This also illustrates that the algorithms studied by the present invention have better visual quality. The specific visual effect and watermark extraction effect are shown in figure 6.
From these observations, it is found that the human eye does not perceive the presence of watermark information in the watermark image. The watermark-containing image has good visual effect, and the corresponding PSNR value shows that the watermark-containing image has good imperceptibility to different types of image algorithms, and the average PSNR value is up to 58.42dB.
As can be seen from Table 2 and FIG. 6, the algorithm of the present invention has a 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 block containing the abrupt point).
Table 3 watermark algorithm performance comparison
In table 310,30,70,90and 100% refers to the specific gravity of the capacity of the watermark to be embedded to the maximum embedding capacity. At 10,30,70,90and 100% of the maximum embedding capacity, PSNR was used to evaluate the visual quality of the watermark image. As can be readily 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 based on difference expansion.International Journal ofDistributed Sensor Networks,2017,13(1):1-15.) and algorithm three (Hala S.El-sayed,S.F.El-Zoghdy,Osama S.Faragallah.Adaptive Difference Expansion-Based Reversible Data Hiding Scheme for Digital Images.Arabian Journal for Science and Engineering,2016,41:1091-1107.), in terms of payload capacity, with good SSIM and PSNR values. 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 algorithm of the invention is compared with the performance of algorithm four (Soliman M M,Hassanien A E,Onsi H M.An adaptive watermarking approach based on weighted quantum particle swarm optimization.Neural Computing&Applications,2016,27(2):1-13.)、, algorithm five (Yin Z,Niu X,Zhou Z,et al.Improved Reversible Image Authentication Scheme.Cognitive Computation,2016,8(5):1-10.) and algorithm six (Hiary S,Jafar I,Hiary H.An efficient multi-predictor reversible data hiding algorithm based on performance evaluation of different prediction schemes.Multimedia Tools&Applications,2017, 76(2):1-27.), and the results are shown in table 4.
Table 4 peak signal to noise ratio and maximum payload comparison for different algorithms
The algorithm four selects four sub-graphs to embed data, and the embedding parameter L is set to 0; algorithm five selects bilinear interpolation, the values of parameters T 1 and T 0 are set to 8 and 60; and a sixth algorithm is to embed the watermark on the basis of the prediction difference expansion. The invention embeds the watermark using a difference extension algorithm and sets the block size to 4x 4. Simulation results show that the performance of the algorithm is superior to that of the algorithm four, the algorithm five and the algorithm six. Compared with the fourth algorithm and the fifth algorithm, the visual quality and the maximum load of the algorithm are improved for simple texture images. 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. The algorithm produces more prediction error bits than algorithm six, can make more full use of these bits, and can be embedded in a larger capacity. For example, for test image Lena, if the block size is set to 4×4, then the resulting watermark image quality is 36.47dB, the maximum payload is 234432 bits, which is slightly better than the other three algorithms. The maximum capacity of embedding by using the algorithm is far higher than other algorithms on the premise of keeping good visual quality.
The foregoing embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the present invention and to implement the same, not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be included in the scope of the present invention.
Claims (4)
1. A reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion, comprising a watermark embedding method comprising the steps of:
Step 1: performing Arnold transformation on the watermark W to obtain W ', and converting the transformed watermark W' into a one-dimensional binary sequence;
Step2: the original image I of size mxn is block-divided into non-overlapping image blocks I i of size 4 x4, M, N are all integer multiples of 4;
step 3: calculating the smoothness values of all the image blocks I i by using a smoothness calculation method, and stably sequencing the smoothness values from small to large to establish a sequencing index information table;
Step 4: performing bit plane decomposition on all image blocks I i, according to the smoothness value of step 3, generating an image sub-block I ' i containing the upper 7 bits for the image blocks which are correspondingly arranged in the front 1/3, generating an image sub-block I ' i containing the upper 6 bits for the image blocks which are correspondingly arranged in the middle 1/3, and generating an image sub-block I ' i containing the upper 5 bits for the image blocks which are correspondingly arranged in the rear 1/3;
step 5: deleting the image subblock with the abrupt point from the selected image subblock I' i through a multi-scale decomposition algorithm;
Step 6: according to the watermark capacity embedding requirement, selecting n image sub-blocks arranged in front in the sequence, removing the selected m image sub-blocks with abrupt points removed, embedding watermark information into the n-m image sub-blocks, and simultaneously recording the sequence number of the image sub-blocks containing the abrupt points;
Step 7: watermark embedding is carried out on any selected image subblock I' i by utilizing a generalized difference expansion algorithm, wherein I is more than or equal to 0 and less than or equal to n; for pixel points which can exceed the gray value range of the image after information is embedded by using a generalized difference expansion algorithm, marking in an overflow graph, compressing the overflow graph, and hiding the overflow graph, watermark embedding amount and watermark scrambling frequency auxiliary information into a texture complex block of an original carrier image;
Step 8: selecting the image sub-blocks of the k blocks after the sequence from the corresponding image sub-blocks which are not used for embedding watermark information in the original image I, recovering to the state when bit plane decomposition is not carried out, and embedding auxiliary information in each pixel in each selected image block by using a difference value quantization method;
1) Calculating an original image block corresponding to the k image sub-blocks after the smoothness value sequencing sequence, and calculating the average value of each pixel in the image block;
Wherein m and n are the row and column sizes of the divided image blocks, and x 1,x2,…,xm×n is the pixel point contained in the image block;
2) Extracting a maximum pixel value and a minimum pixel value in each image block, and embedding auxiliary information by utilizing difference quantization:
2.1 Using the minimum pixel value and the mean value to compare the embedded auxiliary information:
Wherein a represents the pixel value to be embedded, Representing the average value of the pixel points of the image block where the embedded pixel points are located, w represents embedded binary watermark information, and% represents remainder;
2.2 Maximum pixel value and average value for comparison embedded auxiliary information:
Wherein a represents the pixel value to be embedded, Representing the average value of the pixel points of the image block where the embedded pixel points are located, w represents embedded binary watermark information, and% represents remainder;
Step 9: watermark information is embedded through generalized difference expansion and a difference quantization algorithm, and then a watermark image I is generated.
2. The reversible image watermarking algorithm based on improved bit-plane decomposition and difference expansion according to claim 1, further comprising a watermark extraction method corresponding to the watermark embedding method, the watermark extraction method comprising the steps of:
STEP1: the M x N size watermark image I "is block-divided into 4 x 4 size non-overlapping image blocks I i", M, N are all integer multiples of 4;
STEP2: calculating the smoothness values of all mutually non-overlapped image blocks I i' by using a smoothness calculation method, and then stably sequencing the smoothness values from small to large to generate a sequencing index information table;
STEP3: performing bit plane decomposition on an original watermark image I ', generating an image subblock I' i containing high 7 bits from the blocks arranged in the front 1/3, an image subblock I i 'containing high 6 bits from the blocks arranged in the middle 1/3, and an image subblock I i' containing high 5 bits from the blocks arranged in the rear 1/3 according to the smoothness value in STEP 2;
STEP4: restoring the sub-blocks of the k images after the selection sequence to a state when bit plane decomposition is not performed, and extracting auxiliary information from each pixel in each selected image block by using a difference quantization method;
When the auxiliary information is extracted by the difference quantization method in STEP4, 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 relation between the minimum pixel value and the average value of the maximum pixel value in the image block can be kept consistent before and after the auxiliary information is embedded, namely:
Wherein a represents the pixel value to be embedded, Representing the average value of the pixel points of the image block where the embedded pixel points are located, w represents embedded binary watermark information, and% represents remainder;
STEP5: extracting watermark from the ordered first n image sub-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; recovering watermark information W through Arnold reverse scrambling;
STEP6: and combining the image I', which is recovered after extracting the watermark information, of the low-level bit plane with the corresponding high-level bit plane decomposed by the bit plane to obtain an image I, and combining the image I with the image obtained after extracting the auxiliary information to obtain a final image A.
3. The reversible image watermarking algorithm based on improved bit-plane decomposition and difference expansion according to claim 1, wherein the specific operation of performing Arnold transform on the watermark W to obtain W' in step 1 is:
wherein, (x, y) is the original pixel coordinates, (x ', y') is the transformed pixel coordinates, M is the image size, c and d are the scrambling times, and c and d are randomly generated.
4. The reversible image watermarking algorithm based on improved bit-plane decomposition and difference expansion according to claim 2, wherein the specific principle of extracting the watermark from the ordered first n blocks by using the inverse generalized difference expansion algorithm in STEP5 is as follows:
When the one-bit watermark information embedded in any pixel pair is 1, the obtained new pixel pair difference value 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 odd, the embedded watermark information is 1, otherwise, the embedded watermark information is 0.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210180641.4A CN114663268B (en) | 2022-02-25 | 2022-02-25 | Reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210180641.4A CN114663268B (en) | 2022-02-25 | 2022-02-25 | Reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114663268A CN114663268A (en) | 2022-06-24 |
| CN114663268B true CN114663268B (en) | 2024-06-21 |
Family
ID=82026973
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210180641.4A Active CN114663268B (en) | 2022-02-25 | 2022-02-25 | Reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114663268B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115393151A (en) * | 2022-08-19 | 2022-11-25 | 淮阴工学院 | Reversible watermarking algorithm based on IWT and prediction difference value histogram translation |
| CN116468594B (en) * | 2023-05-09 | 2024-06-28 | 淮阴工学院 | Reversible watermarking algorithm based on diamond pixel pair complementary embedding |
| CN116957894B (en) * | 2023-06-28 | 2024-06-28 | 淮阴工学院 | Prediction error expansion reversible watermarking algorithm based on pixel correlation |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049877A (en) * | 2012-12-03 | 2013-04-17 | 江苏大学 | Method for embedding and detecting watermark based on vertex distribution feature digital three-dimensional model |
| CN106485642A (en) * | 2016-09-30 | 2017-03-08 | 北京交通大学 | The method of embedded visible watermark in three-dimensional grid model |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB9006080D0 (en) * | 1990-03-17 | 1990-05-16 | Int Computers Ltd | Progressive encoding |
| AU2003239735A1 (en) * | 2002-06-24 | 2004-01-06 | Koninklijke Philips Electronics N.V. | Embedding of image authentication signatures |
| CN100394443C (en) * | 2006-07-07 | 2008-06-11 | 中山大学 | Reversible watermark method for image certification |
| EP2431970A1 (en) * | 2010-09-21 | 2012-03-21 | Fraunhofer-Gesellschaft zur Förderung der Angewandten Forschung e.V. | Watermark generator, watermark decoder, method for providing a watermarked signal based on discrete valued data and method for providing discrete valued data in dependence on a watermarked signal |
| CN106530196A (en) * | 2016-09-26 | 2017-03-22 | 上海理工大学 | JPEG2000 based multi-scale Laplacian pyramid watermarking method |
| US10037587B2 (en) * | 2016-11-23 | 2018-07-31 | Macau University Of Science And Technology | Color image watermarking |
| US10296999B2 (en) * | 2017-02-13 | 2019-05-21 | Macau University Of Science And Technology | Methods and apparatus for color image watermarking |
| CN107423611B (en) * | 2017-06-26 | 2021-04-06 | 口碑控股有限公司 | Graphic code identification method and device and electronic equipment |
| CN109934936A (en) * | 2019-03-07 | 2019-06-25 | 太原科技大学 | A kind of three dimensional model printing visible watermark embedding grammar based on dot character |
| CN110490790B (en) * | 2019-08-26 | 2020-08-25 | 淮阴工学院 | High-capacity reversible image watermarking algorithm for improving difference value expansion |
| CN110738592B (en) * | 2019-09-06 | 2020-08-25 | 淮阴工学院 | High-capacity reversible image watermarking algorithm based on multi-scale decomposition and interpolation expansion |
| CN111199506B (en) * | 2019-12-17 | 2021-12-17 | 淮阴工学院 | Reversible image watermarking algorithm combining quadratic difference expansion and interpolation expansion |
-
2022
- 2022-02-25 CN CN202210180641.4A patent/CN114663268B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049877A (en) * | 2012-12-03 | 2013-04-17 | 江苏大学 | Method for embedding and detecting watermark based on vertex distribution feature digital three-dimensional model |
| CN106485642A (en) * | 2016-09-30 | 2017-03-08 | 北京交通大学 | The method of embedded visible watermark in three-dimensional grid model |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114663268A (en) | 2022-06-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114663268B (en) | Reversible image watermarking algorithm based on improved bit plane decomposition and difference expansion | |
| Subburam et al. | High performance reversible data hiding scheme through multilevel histogram modification in lifting integer wavelet transform | |
| Shi et al. | Lossless data hiding: Fundamentals, algorithms, and applications | |
| CN110490790B (en) | High-capacity reversible image watermarking algorithm for improving difference value expansion | |
| CN101105857A (en) | High capacity reversible water mark method based on predication and companding technology | |
| WO2021103676A1 (en) | Self-adaptive reversible information hiding method based on integer wavelet transform | |
| CN111898136A (en) | High-fidelity reversible information hiding method and device based on prediction error value sequencing | |
| CN114399419B (en) | Reversible image watermarking algorithm based on prediction error expansion | |
| Wu et al. | A high capacity reversible data hiding scheme with edge prediction and difference expansion | |
| CN113032813B (en) | Reversible information hiding method based on improved pixel local complexity calculation and multi-peak embedding | |
| Pal et al. | A secure reversible color image watermarking scheme based on LBP, lagrange interpolation polynomial and weighted matrix | |
| CN110738592B (en) | High-capacity reversible image watermarking algorithm based on multi-scale decomposition and interpolation expansion | |
| Gao et al. | Reversible watermarking algorithm based on wavelet lifting scheme | |
| CN115393151A (en) | Reversible watermarking algorithm based on IWT and prediction difference value histogram translation | |
| CN115222575A (en) | Vector data watermark embedding and extracting method using frequency domain coefficient ratio | |
| Chandrasekaran et al. | Applying reversible data hiding for medical images in hybrid domain using haar and modified histogram | |
| Jamdar et al. | Edge adaptive steganography using DWT | |
| Zhang et al. | A reversible information hiding algorithm in AMBTC domain based on human vision system | |
| CN115631084B (en) | Reversible watermarking method based on IWT and interpolation expansion | |
| Jinna et al. | Lossless image watermarking using lifting wavelet transform | |
| Chang et al. | Reversible watermarking schemes using spatial quad-based difference expansion | |
| CN111787422B (en) | Video watermarking method based on time factor matrix | |
| Geetha et al. | Multilevel RDH scheme using image interpolation | |
| Huang | A reversible visible watermarking technique for BTC-compressed images | |
| Naheed et al. | Intelligent reversible digital watermarking technique using interpolation errors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |