A Reversible Information Hiding Method and System Based on Global Sorting and Single-Pixel Value Sorting

Abstract

This invention belongs to the field of information security technology and discloses a method and system for reversible information hiding based on global sorting of single-pixel values. The method includes: dividing the processed carrier image (excluding the first row) into four pixel layers, and globally sorting the pixels in each layer to obtain a one-dimensional pixel sequence; based on the one-dimensional pixel sequence, for all pixel segment sizes within a selected range, determining whether to embed secret information in each pixel segment according to the relationship between a preset complexity threshold and the complexity of each pixel segment; and selecting the carrier image with the lowest distortion as the final encrypted carrier image. This invention solves the technical problem in existing technologies where relying solely on local spatial correlation block division of images limits the performance of reversible information hiding, and improves the hiding performance of reversible information hiding.

Description

Technical Field

[0001] This invention belongs to the field of information security technology, and relates to the field of reversible information hiding, and in particular to a method and system for reversible information hiding based on global sorting of single pixel values. Background Technology

[0002] Reversible information hiding is an advanced information security technology that can conceal secret information within a publicly accessible carrier image. This makes the secret information not only invisible but also difficult to detect, causing attackers to overlook its existence and avoiding the risk of information theft during transmission, thus enabling covert communication. Furthermore, the legitimate recipient can recover all the secret information and the original carrier image without loss. Specifically, reversible information hiding technology is commonly used in fields with high requirements for carrier image quality, such as military, aerospace, forensic authentication, and medical imaging.

[0003] The main criteria for evaluating the effectiveness of reversible information hiding algorithms are carrier distortion and embedding capacity. Interpretationally, carrier distortion refers to the change in visual quality of the carrier image before and after embedding secret information, while embedding capacity refers to the maximum amount of secret information that can be embedded in a carrier image.

[0004] To reduce carrier distortion and increase embedding capacity, some researchers proposed using the surrounding pixels of the pixel to be embedded to predict it and embedding secret information into the prediction error, which achieved good results. Later, new research proposed combining prediction errors into pairs and modifying the mapping method of two-dimensional prediction errors, which further improved distortion performance and embedding capacity.

[0005] Currently, researchers have proposed dividing the carrier image into local pixel blocks and then predicting and embedding secret information separately, achieving good overall results. However, the block division method of these existing methods relies too much on the local spatial correlation of the image, and it is difficult to achieve good performance when dealing with images with complex textures. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for reversible information hiding based on global sorting of single pixel values, in order to solve one or more of the aforementioned technical problems. The technical solution disclosed in this invention groups pixels with similar values ​​globally, overcoming distance limitations. This solves the technical problem in existing technologies where relying solely on local spatial correlation block division of images restricts the performance of reversible information hiding, thereby improving the hiding performance of reversible information hiding.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a method for reversible information hiding based on global sorting of single pixel values, comprising the following steps:

[0009] Acquire the original carrier image and perform anti-overflow and anti-overflow operations to obtain the processed carrier image; based on the original carrier image, obtain a position array that records the overflow and overflow positions;

[0010] The processed carrier image, excluding the first row, is divided into four pixel layers. The predicted values ​​and complexity of all pixels in each pixel layer are calculated in sequence. The pixels in each pixel layer are then globally sorted based on the predicted values ​​and complexity of the pixels to obtain a one-dimensional pixel sequence.

[0011] Based on a one-dimensional pixel sequence, for all pixel segment sizes within the selected range, the relationship between a preset complexity threshold and the complexity of each pixel segment guides whether to embed secret information in each pixel segment. Specifically, for the selected current pixel segment size, the pixel segment complexity and the single pixel value sorting prediction error of each pixel segment are calculated. Based on the relationship between pixel segment complexity and the complexity threshold, the relationship between the pixel segment complexity and the complexity threshold guides whether to use the pixel to embed secret information in each pixel segment. The secret information is then embedded into the processed carrier image based on the prediction error value. Finally, the auxiliary information required for restoring the carrier image and extracting information is embedded into the first row of pixels of the processed carrier image to obtain a secret-containing carrier image. The auxiliary information includes a position array recording overflow and overflow positions, pixel segment size, and complexity threshold.

[0012] The distortion levels of the dense carrier image obtained at different pixel segment sizes are compared with those of the original carrier image, and the dense carrier image with the lowest distortion level is selected as the final dense carrier image.

[0013] A further improvement of the present invention is that, in the step of dividing the processed carrier image (excluding the first row) into four pixel layers, calculating the predicted value and complexity of all pixels in each pixel layer in sequence, and globally sorting the pixels of each pixel layer using the predicted value and complexity to obtain a one-dimensional pixel sequence,

[0014] The steps to divide the processed carrier image, excluding the first row, into four pixel layers are as follows: all pixels with odd horizontal and vertical coordinates form the first pixel layer; all pixels with even horizontal coordinates and odd vertical coordinates form the second pixel layer; all pixels with odd horizontal coordinates and even vertical coordinates form the third pixel layer; and all pixels with even horizontal coordinates and odd vertical coordinates form the fourth pixel layer.

[0015] The steps for calculating the predicted value and complexity of all pixels in each pixel layer in the order of the first pixel layer, the second pixel layer, the third pixel layer, and the fourth pixel layer are as follows: for each pixel in each pixel layer, the predicted value is calculated using the pixels of the 16 other pixel layers surrounding the pixel, and the complexity is calculated using the 8 pixels adjacent to the pixel.

[0016] The steps for globally sorting pixels in each pixel layer based on their predicted values ​​and complexity are as follows: For all pixels in each pixel layer, first sort them in ascending order using their predicted values. Then, sort the pixels with the same predicted values ​​in the entire pixel sequence in ascending order alternately in ascending and descending order to obtain the globally sorted sequence.

[0017] A further improvement of the present invention is that the step of calculating the predicted value and complexity of all pixels in each pixel layer in the order of the first pixel layer, the second pixel layer, the third pixel layer, and the fourth pixel layer is as follows: for each pixel in each pixel layer, the predicted value is calculated using the pixels of the 16 other pixel layers surrounding the pixel, and the complexity is calculated using the 8 pixels adjacent to the pixel.

[0018] For a selected pixel, use the pixels {x1, x2, ..., x} from the 16 other pixel layers surrounding that pixel. 16 The geometric similarity parameter A is calculated according to the following formula. i (i∈[1,8]), the calculation expression is:

[0019]

[0020] In the formula, τ is the grayscale range;

[0021] The twist distance is calculated using the following formula:

[0022] D i =d-k1×A i ×d×(d-1);

[0023] In the formula, k1 = 4 is a coefficient controlling the twist intensity; d = 1 / 2 is the original relative distance between a pixel and its neighboring pixels; the distance d1′ from a pixel to the edge of the rectangle formed by its neighboring pixels is calculated according to the following formula. 80 d9′0, d1′ 35 and d4′5:

[0024]

[0025] The inverse gradient weights in the eight directions are calculated using the following formula:

[0026]

[0027] In the formula, k2 = 0.2 is a parameter that controls the degree of influence of the gradient on the prediction;

[0028] Combining the warp distance and the corresponding inverse gradient weights, the weights of the eight neighboring pixels are calculated using the following formula:

[0029]

[0030] U = g 180 (1-d′ 180 )+g0·d′ 180 +g 90 (1-d′ 90 )+g -90 ·d′ 90 +k3·g 135 (1-d′ 135 )+k3·g -45 ·d′ 135 +k3·g 45 (1-d' 45 )+k3·g -135 ·d′ 45 ;

[0031] In the formula, These are parameters for adjusting spatial distance;

[0032] The weights are assigned to the corresponding neighboring pixels, and the predicted value of the center pixel is calculated according to the following formula.

[0033]

[0034] In the formula, [·] represents the rounding function;

[0035] The pixel complexity C is calculated using the 8 pixels adjacent to the center pixel according to the following formula:

[0036] C=|x5-x2|+|x2-x6|+|x6-x3|+|x3-x7|+|x7-x4|+|x4-x8|+|x8-x1|+|x1-x5|.

[0037] A further improvement of the present invention lies in the step of determining whether to embed secret information in each pixel segment based on a one-dimensional pixel sequence, for all pixel segment sizes within the selected range, according to the relationship between a preset complexity threshold and the complexity of each pixel segment.

[0038] Set the size of the pixel segment to s;

[0039] For a pixel segment, obtain the pixels {p, z1, z2, ..., z} in the order of global sorting. s-1}, where p represents the pixel to be embedded, z1, z2, ..., z s-1 This represents the predicted pixels used to predict p; all pixel segments are obtained sequentially in global sorting order, with an interval of one pixel.

[0040] Calculate the single-pixel sorting prediction value of the pixel p to be embedded in each pixel segment; the complexity of calculating each pixel segment is C. Seq ;

[0041] For each obtained pixel segment, the prediction error of the pixel to be embedded, p, is calculated sequentially; the complexity threshold T is then compared with the complexity C of each pixel segment. Seq Compare, if C Seq >T then skips the pixel segment; if C Seq If the value is less than or equal to T, then secret information is embedded into the pixel segment.

[0042] A further improvement of the present invention is that,

[0043] The step of calculating the single-pixel sorting prediction value of the pixel to be embedded p in each pixel segment is as follows: for each pixel segment {p, z1, z2, ..., z...} s-1}, using the predicted pixels {z1,z2,…,z} according to the following formula s-1} Obtain the sorted prediction values ​​of the two single pixel values ​​of the pixel to be embedded, p. and

[0044]

[0045] The computational complexity C for each pixel segment is... Seq In the steps, for each pixel segment {p,z1,z2,…,z} s-1 The complexity C of calculating a pixel segment is given by the following formula. Seq :

[0046]

[0047] In the formula, These are the calculated pixel values ​​p, z1, z2...z s-1 pixel complexity;

[0048] For each pixel segment obtained by sequential access, the prediction error of the pixel to be embedded, p, is calculated; the complexity threshold T is then compared with the complexity C of each pixel segment. Seq Compare, if C Seq >T then skips the pixel segment; if C Seq The specific steps for embedding secret information into pixel segments ≤T are as follows: for each pixel segment {p,z1,z2,…,z…} s-1 The predicted values ​​are sorted using the single pixel values ​​according to the following formula. and Calculate the prediction error e:

[0049]

[0050] In the formula, This indicates that there is no prediction error;

[0051] For each pixel segment {p, z1, z2, ..., z} s-1}, compare the complexity threshold T with the complexity C of each pixel segment. Seq Compare, if C Seq If >T, skip the current pixel segment; if C Seq If the value is less than or equal to T, then check the prediction error of the pixel to be embedded in the pixel segment. If the error does not exist, skip the current pixel segment; otherwise, embed the secret information into pixel p according to the following formula:

[0052]

[0053] In the formula, This represents the modified pixel; sd∈{0,1} represents the embedded secret information bits.

[0054] A further improvement of the present invention is that, in the steps of acquiring the original carrier image and performing anti-overflow operations to obtain a processed carrier image; and based on the original carrier image, acquiring a position array recording the overflow and underflow positions,

[0055] Traverse all pixels of the original carrier image except the first row in raster scan order, set the parameter k to an initial value of 1, and perform the following operation on each pixel:

[0056]

[0057] In the formula, p represents the pixel value that is traversed; LM is a position array, a one-dimensional vector used to record the position of the pixel after the pixel value has been adjusted;

[0058] Arithmetic compression of the LM is performed to reduce the number of bits required by the recorder, resulting in the compressed position array CLM.

[0059] A further improvement of the present invention is that,

[0060] The step of embedding the auxiliary information required for restoring the carrier image and extracting information into the first row of pixels of the processed carrier image is as follows: For a carrier image of size H×W, record the first row of pixels. The least significant bits of each pixel are combined with the secret information; the original first row is then merged with the first significant bits of each pixel. The least significant bit is replaced by auxiliary information; the auxiliary information includes the pixel segment size s used, occupying 3 bits; the complexity threshold T of the four layers, occupying 4×12=48 bits; and the last position P of the four-layer embedding. end Occupy Bit, Indicates rounding up; the length l of the compressed position array CLM. CLM Occupy Bit.

[0061] A further improvement of the present invention is that, after obtaining the final encrypted carrier image, a decoding step is also included; wherein,

[0062] The decoding step includes: reading the first line of the final encrypted carrier image. The least significant bit of each pixel is used to obtain auxiliary information for decoding; wherein, the auxiliary information for decoding includes the pixel segment size s, the complexity threshold T of the four layers, and the last position P of the four-layer embedding. end and the length l of the compressed position array CLM CLM ;

[0063] The decoding sequence is the reverse of the embedding stage;

[0064] For decoding each pixel layer, perform a global sort in the same manner as during embedding, calculate the complexity of all pixel segments of size s, and then start from the last embedding position P of the pixel layer. end Initially, a pixel segment of size s is acquired, and the relationship between the pixel segment's complexity and the complexity threshold T guides the pixel segment to be decoded or skipped. After decoding a pixel segment, the next pixel segment is acquired at one-pixel intervals in the opposite direction to the embedding stage, and the next pixel segment is attempted to be decoded, until all pixel segments are decoded.

[0065] The least significant bit corresponding to the first row of the decoded secret information. Bit secret information and the current first line The least significant bit of the pixel is replaced;

[0066] The corresponding CLM l CLM The secret information of the bits is extracted and decompressed to obtain the position array LM. The pixel values ​​that were originally protected against overflow are restored using LM.

[0067] In a second aspect, the present invention provides a reversible information hiding system based on global sorting of single pixel values, comprising:

[0068] The preprocessing module is used to acquire the original carrier image and perform anti-overflow and anti-overflow operations to obtain the processed carrier image; based on the original carrier image, it acquires a position array that records the overflow and overflow positions;

[0069] The global sorting module is used to divide the processed carrier image (excluding the first row) into four pixel layers, calculate the predicted value and complexity of all pixels in each pixel layer in order, and sort the pixels of each pixel layer globally based on the predicted value and complexity of the pixels to obtain a one-dimensional pixel sequence.

[0070] The prediction and embedding module is used to guide whether to embed secret information in each pixel segment based on a one-dimensional pixel sequence and for all pixel segment sizes within a selected range, according to the relationship between a preset complexity threshold and the complexity of each pixel segment. Specifically, for the selected current pixel segment size, the module calculates the pixel segment complexity and the single pixel value sorting prediction error of each pixel segment. Based on the relationship between pixel segment complexity and the complexity threshold, it guides whether to use the pixels to be embedded in each pixel segment for embedding secret information. The module embeds the secret information into the processed carrier image according to the prediction error value. Then, it embeds the auxiliary information required for restoring the carrier image and extracting information into the first row of pixels of the processed carrier image to obtain a secret-containing carrier image. The auxiliary information includes a position array recording overflow and overflow positions, pixel segment size, and complexity threshold.

[0071] The final dense carrier image acquisition module is used to compare the degree of distortion of the dense carrier image with the original carrier image under different pixel segment sizes, and select the dense carrier image with the lowest degree of distortion as the final dense carrier image.

[0072] In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the reversible information hiding method based on global sorting of single pixel values ​​as described in any one of the first aspects of the present invention.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] Existing pixel value sorting algorithms still have significant room for improvement. Currently, relying solely on the local spatial correlation of the carrier image fails to accurately predict the pixels to be embedded, and pixel aggregation methods need further refinement. In view of these existing technical problems, this invention specifically provides a reversible information hiding method based on global sorting of single pixel values. This method employs prediction based on a four-layer partitioning of the carrier image. After globally sorting the pixel prediction values ​​and complexity, all pixels are transformed into a one-dimensional sequence. Furthermore, similar pixels globally are clustered in the same neighborhood regardless of spatial distance, making prediction using pixels within the neighborhood more accurate and reducing carrier distortion. In summary, this invention proposes a global sorting method that transforms the layered image into a one-dimensional sequence, thereby clustering similar pixels in the same neighborhood throughout the image. This increases prediction accuracy, reduces carrier distortion when embedding secret information, and improves the embedding performance of reversible information hiding methods. Attached Figure Description

[0075] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0076] Figure 1 This is a flowchart illustrating a method for reversible information hiding based on global sorting of single pixel values, as described in an embodiment of the present invention.

[0077] Figure 2 This is a schematic diagram of the four-layer division of the carrier image used in this embodiment of the invention;

[0078] Figure 3 This is a schematic diagram of the pixels used in an embodiment of the present invention when calculating the predicted value and complexity of the current layer pixel using pixels from the other three layers;

[0079] Figure 4 This is a schematic diagram showing the change of peak signal-to-noise ratio (PSNR) of the carrier image and the original image with the amount of embedding when comparing the method provided in this embodiment of the invention with the existing traditional single-pixel value sorting method on the Baboon image;

[0080] Figure 5 This is a schematic diagram showing the change of peak signal-to-noise ratio (PSNR) of the carrier image and the original image with the amount of embedding when comparing the method provided in this embodiment of the invention with the existing traditional single-pixel value sorting method on the image Barbara.

[0081] Figure 6 This is a schematic diagram showing the change of peak signal-to-noise ratio (PSNR) of the carrier image and the original image with the amount of embedding when comparing the method provided in this embodiment of the invention with the existing traditional single-pixel value sorting method on the image Lake.

[0082] Figure 7 This is a schematic diagram of a reversible information hiding system based on global sorting of single pixel values, as described in an embodiment of the present invention. Detailed Implementation

[0083] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention; obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0084] Based on the technical solutions disclosed in the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0085] Please see Figure 1 The present invention provides a method for reversible information hiding based on global sorting of single pixel values, comprising the following steps:

[0086] Step 1: Obtain the original carrier image and perform anti-overflow and anti-overflow operations to obtain the processed carrier image; based on the original carrier image, obtain a position array that records the overflow and overflow positions;

[0087] In a specific exemplary technical solution, all pixels of the pre-selected original carrier image except for the first row are traversed according to the raster scanning order. The parameter k is set to an initial value of 1, and the following operation is performed on each pixel:

[0088]

[0089] In formula (1), p represents the pixel value that is traversed; LM is a position array, which is a one-dimensional vector used to record the position of the pixel after the pixel value has been adjusted.

[0090] Furthermore, the LM is arithmetically compressed to reduce the number of bits required by the recorder, resulting in a compressed position array CLM; the CLM is then incorporated into the secret information to be embedded as part of the secret information.

[0091] Step 2: Divide the processed carrier image (excluding the first row) into four pixel layers, calculate the predicted value and complexity of all pixels in each pixel layer in order, and sort the pixels of each pixel layer globally by the predicted value and complexity of the pixels to obtain a one-dimensional pixel sequence.

[0092] Please see Figure 2 , Figure 3 In a specific exemplary technical solution, the portion of the processed carrier image excluding the first row is divided according to... Figure 2 The diagram shows a four-layer layout (i.e., four pixel layers), which are used in sequence. Figure 3 The surrounding pixels are shown. The predicted values ​​and complexity of all pixels in each layer are calculated. The pixels in each pixel layer are globally sorted by the predicted values ​​and complexity of the pixels to obtain the entire one-dimensional pixel sequence.

[0093] In a specific exemplary technical solution, the processed carrier image is divided into four layers; wherein, all pixels with odd horizontal and vertical coordinates form the first layer, all pixels with even horizontal coordinates and odd vertical coordinates form the second layer, all pixels with odd horizontal coordinates and even vertical coordinates form the third layer, and all pixels with even horizontal coordinates and odd vertical coordinates form the fourth layer.

[0094] For a pixel p, use the pixels {x1, x2, ..., x} from the 16 surrounding layers. 16 The geometric similarity parameter A is calculated according to the following formula. i (i∈[1,8]):

[0095]

[0096] In formula (2), τ is the grayscale range, which is 256 for an 8-bit image.

[0097] Then, calculate the twist distance using the following formula:

[0098] D i =d-k1×A i ×d×(d-1)(3)

[0099] In formula (3), k1 = 4 is a coefficient that controls the twist intensity; d = 1 / 2 is the original relative distance between pixel p and its neighboring pixels.

[0100] Then, calculate the distance d1′ from pixel p to the side of the rectangle formed by its adjacent pixels according to the following formula. 80 d9′0, d1′ 35 and d4′5:

[0101]

[0102] The inverse gradient weights in the eight directions are calculated using the following formula:

[0103]

[0104] In formula (5), k2 = 0.2 is a parameter that controls the degree of influence of the gradient on the prediction.

[0105] Then, combining the warp distance and its corresponding inverse gradient weights, the weights of the eight neighboring pixels are calculated according to the following formula:

[0106] U = g 180 (1-d′ 180 )+g0·d′ 180 +g 90 (1-d′ 90 )+g -90 ·d′ 90 +k3·g 135 (1-d′ 135 )+k3·g -45 ·d′ 135 +k3·g 45 (1-d' 45 )+k3·g -135 ·d′ 45 (6)

[0107] In formula (6), It is a parameter for adjusting spatial distance.

[0108] Then, these weights are assigned to the corresponding neighboring pixels, and the predicted value of the center pixel p is calculated according to the following formula.

[0109] In formula (7), [·] represents the rounding function.

[0110] The pixel complexity is calculated using the 8 pixels adjacent to the center pixel p according to the following formula:

[0111] C=|x5-x2|+|x2-x6|+|x6-x3|+|x3-x7|+|x7-x4|+|x4-x8|+|x8-x1|+|x1-x5| (8)

[0112] For all pixels in each layer, first sort them in ascending order using their predicted values, then sort the pixels with the same predicted values ​​in the entire pixel sequence in ascending order alternately in ascending and descending order to obtain the globally sorted sequence.

[0113] Step 3: Based on the one-dimensional pixel sequence, for all pixel segment sizes within the selected range, according to the relationship between the preset complexity threshold and the complexity of each pixel segment, guide whether the pixel to be embedded in each pixel segment uses the single pixel value sorting method to embed secret information.

[0114] In a specific exemplary technical solution, the size of the pixel segment is set to s, where s∈{4,7,10,13,16}; for a pixel segment, the pixels {p,z1,z2,…,z} are obtained according to the global sorting order. s-1}, where p represents the pixel to be embedded, z1, z2, ..., z s-1 The predicted pixels are used to predict p; all pixel segments are obtained sequentially at one-pixel intervals according to the global sort order.

[0115] For each pixel segment {p, z1, z2, ..., z} s-1}, using the predicted pixels {z1,z2,…,z} according to the following formula s-1} Obtain the sorted predicted values ​​of the two single pixel values ​​of pixel p and

[0116]

[0117] For each pixel segment {p, z1, z2, ..., z} s-1 The complexity C of this pixel segment is calculated according to the following formula. Seq :

[0118]

[0119] In formula (10), These are the calculated pixel values ​​p, z1, z2...z s-1 The pixel complexity.

[0120] For each pixel segment {p, z1, z2, ..., z} s-1 The predicted values ​​are sorted using the single pixel values ​​according to the following formula. and Calculate the prediction error e:

[0121]

[0122] In formula (11), This indicates that there is no prediction error.

[0123] For each pixel segment {p, z1, z2, ..., z} s-1}, and combine the pre-selected complexity threshold T with the complexity C of each pixel segment. Seq Compare, if C SeqIf >T, skip the current pixel segment; if C Seq If the value is less than or equal to T, then check the prediction error of the pixel to be embedded in that pixel segment. If the error does not exist, skip the current pixel segment; otherwise, embed the secret information into pixel p according to the following formula:

[0124]

[0125] In formula (12), Let sdA{0,1} represent the modified pixel p, where sdA{0,1} are the embedded secret information bits.

[0126] In addition, the step of embedding the auxiliary information required for restoring the carrier image and extracting information into the first row of pixels of the processed carrier image includes: for a carrier image of size H×W, recording the first row of pixels... The least significant bit of each pixel is merged into the secret information; the original first row is then merged into the secret information. The least significant bit is replaced with auxiliary information;

[0127] The auxiliary information includes: the pixel segment size s used, occupying 3 bits; the complexity threshold T of the four layers, occupying 4×12=48 bits; and the last position P of the four-layer embedding. end Occupy Bit, Indicates rounding up; the length l of the compressed position array CLM. CLM Occupy Bit.

[0128] Step 4: Compare the distortion levels of the dense carrier images at different pixel segment sizes, and select the dense carrier image with the least distortion compared to the original carrier image as the final dense carrier image.

[0129] In this embodiment of the invention, the performance of the final method can be measured by the embedding capacity-peak signal-to-noise ratio curve, that is, the carrier image quality under a specific amount of embedding information.

[0130] In summary, this invention discloses a reversible information hiding method based on global sorting of single pixel values ​​for covert communication. The method includes: performing anti-overflow / underflow operations on the carrier image and recording the corresponding information for image recovery; dividing the carrier image into four layers, calculating the pixel prediction value and complexity of each layer, and performing global sorting; controlling the embedding operation of each pixel segment sequentially according to the relationship between complexity and complexity threshold; and embedding the auxiliary information required for decoding into the image.

[0131] Please see Figures 4 to 6 The technical solution of this invention can improve the embedding performance of the reversible information hiding algorithm based on pixel value sorting, and the effectiveness of the method has been verified through experiments. Figure 4 , Figure 5 and Figure 6 It can be seen that the reversible information hiding method based on global sorting of single pixel values ​​in the embodiments of the present invention can effectively improve the embedding performance of pixel value sorting algorithms. Furthermore, by comparing the embedding performance of the reversible information hiding method based on traditional block-based single pixel value sorting with the algorithm of the present invention on standard test images Baboon, Barbara, and Lake—that is, the PSNR curves corresponding to the embedding amount starting from 5,000 bits and increasing in 1,000-bit steps to the maximum embedding capacity of the algorithm of the present invention—it can be seen that the method proposed in the present invention has a significant improvement in carrier distortion performance. Furthermore, the adaptive global sorting method proposed in the embodiments of the present invention is not only applicable to the single pixel value sorting method mentioned in the embodiments of the present invention, but also applicable to various other pixel value sorting methods, all of which can reduce carrier distortion.

[0132] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0133] Please see Figure 7 In this embodiment of the invention, a reversible information hiding system based on global sorting of single pixel values ​​is provided, comprising:

[0134] The preprocessing module is used to acquire the original carrier image and perform anti-overflow and anti-overflow operations to obtain the processed carrier image; based on the original carrier image, it acquires a position array that records the overflow and overflow positions;

[0135] The global sorting module is used to divide the processed carrier image (excluding the first row) into four pixel layers, calculate the predicted value and complexity of all pixels in each pixel layer in order, and sort the pixels of each pixel layer globally based on the predicted value and complexity of the pixels to obtain a one-dimensional pixel sequence.

[0136] The prediction and embedding module is used to guide whether to embed secret information in each pixel segment based on a one-dimensional pixel sequence and for all pixel segment sizes within a selected range, according to the relationship between a preset complexity threshold and the complexity of each pixel segment. Specifically, for the selected current pixel segment size, the module calculates the pixel segment complexity and the single pixel value sorting prediction error of each pixel segment. Based on the relationship between pixel segment complexity and the complexity threshold, it guides whether to use the pixels to be embedded in each pixel segment for embedding secret information. The module embeds the secret information into the processed carrier image according to the prediction error value. Then, it embeds the auxiliary information required for restoring the carrier image and extracting information into the first row of pixels of the processed carrier image to obtain a secret-containing carrier image. The auxiliary information includes a position array recording overflow and overflow positions, pixel segment size, and complexity threshold.

[0137] The final dense carrier image acquisition module is used to compare the degree of distortion of the dense carrier image with the original carrier image under different pixel segment sizes, and select the dense carrier image with the lowest degree of distortion as the final dense carrier image.

[0138] In one embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment can be used to execute the operation of a reversible information hiding method based on global sorting of single pixel values.

[0139] In one embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the operating system of the terminal. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM (Random Access Memory) or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the reversible information hiding method for single-pixel value sorting based on global sorting in the above embodiments.

[0140] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, etc.) containing computer-usable program code.

[0141] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0142] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0143] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A reversible information hiding method based on global sorting of single pixel values, characterized in that, Includes the following steps: The original carrier image is acquired and anti-overflow operations are performed to obtain the processed carrier image; based on the original carrier image, a position array recording the overflow and overflow positions is obtained. The processed carrier image, excluding the first row, is divided into four pixel layers. The predicted values ​​and complexity of all pixels in each pixel layer are calculated in sequence. The pixels in each pixel layer are then globally sorted based on the predicted values ​​and complexity of the pixels to obtain a one-dimensional pixel sequence. Based on a one-dimensional pixel sequence, for all pixel segment sizes within the selected range, the relationship between a preset complexity threshold and the complexity of each pixel segment guides whether to embed secret information in each pixel segment. Specifically, for the selected current pixel segment size, the pixel segment complexity and the single pixel value sorting prediction error of each pixel segment are calculated. Based on the relationship between pixel segment complexity and the complexity threshold, the relationship between the pixel segment complexity and the complexity threshold guides whether to use the pixel to embed secret information in each pixel segment. The secret information is then embedded into the processed carrier image based on the prediction error value. Finally, the auxiliary information required for restoring the carrier image and extracting information is embedded into the first row of pixels of the processed carrier image to obtain a secret-containing carrier image. The auxiliary information includes a position array recording overflow and overflow positions, pixel segment size, and complexity threshold. The distortion levels of the dense carrier image obtained at different pixel segment sizes are compared with those of the original carrier image, and the dense carrier image with the lowest distortion level is selected as the final dense carrier image.

2. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 1, characterized in that, In the step of dividing the processed carrier image (excluding the first row) into four pixel layers, calculating the predicted value and complexity of all pixels in each pixel layer in sequence, and then globally sorting the pixels of each pixel layer based on the predicted values ​​and complexity to obtain a one-dimensional pixel sequence, The steps to divide the processed carrier image, excluding the first row, into four pixel layers are as follows: all pixels with odd horizontal and vertical coordinates form the first pixel layer; all pixels with even horizontal coordinates and odd vertical coordinates form the second pixel layer; all pixels with odd horizontal coordinates and even vertical coordinates form the third pixel layer; and all pixels with even horizontal coordinates and odd vertical coordinates form the fourth pixel layer. The steps for calculating the predicted value and complexity of all pixels in each pixel layer in the order of the first pixel layer, the second pixel layer, the third pixel layer, and the fourth pixel layer are as follows: for each pixel in each pixel layer, the predicted value is calculated using the pixels of the 16 other pixel layers surrounding the pixel, and the complexity is calculated using the 8 pixels adjacent to the pixel. The steps for globally sorting pixels in each pixel layer based on their predicted values ​​and complexity are as follows: For all pixels in each pixel layer, first sort them in ascending order using their predicted values. Then, sort the pixels with the same predicted values ​​in the entire pixel sequence in ascending order alternately in ascending and descending order to obtain the globally sorted sequence.

3. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 2, characterized in that, The step of calculating the predicted values ​​and complexity of all pixels in each pixel layer in the order of the first pixel layer, the second pixel layer, the third pixel layer, and the fourth pixel layer is as follows: For each pixel in each pixel layer, the predicted value is calculated using the pixels of the 16 other pixel layers surrounding the pixel, and the complexity is calculated using the 8 pixels adjacent to the pixel. For a selected pixel, use the pixels {x1, x2, ..., x} from the 16 other pixel layers surrounding that pixel. 16 The geometric similarity parameter A is calculated according to the following formula. i (i∈[1,8]), the calculation expression is: In the formula, τ is the grayscale range; The twist distance is calculated using the following formula: D i =d-k1×A i ×d×(d-1); In the formula, k1 = 4 is a coefficient controlling the twist intensity; d = 1 / 2 is the original relative distance between a pixel and its neighboring pixels; the distance d′ from a pixel to the edge of the rectangle formed by its neighboring pixels is calculated according to the following formula. 180 ,d′ 90 ,d′ 135 and d′ 45 : The inverse gradient weights in the eight directions are calculated using the following formula: In the formula, k2 = 0.2 is a parameter that controls the degree of influence of the gradient on the prediction; Combining the warp distance and the corresponding inverse gradient weights, the weights of the eight neighboring pixels are calculated using the following formula: U=g 180 (1-d′ 180 )+g0·d′ 180 +g 90 (1-d′ 90 )+g -90 ·d′ 90 +k3·g 135 (1-d′ 135 )+k3·g -45 ·d′ 135 +k3·g 45 (1-d' 45 )+k3·g -135 ·d′ 45 ; In the formula, These are parameters for adjusting spatial distance; The weights are assigned to the corresponding neighboring pixels, and the predicted value of the center pixel is calculated according to the following formula. In the formula, [·] represents the rounding function; The pixel complexity C is calculated using the 8 pixels adjacent to the center pixel according to the following formula: C=|x5-x2|+|x2-x6|+|x6-x3|+|x3-x7|+|x7-x4|+|x4-x8|+|x8-x1|+|x1-x5|.

4. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 1, characterized in that, In the step of determining whether to embed secret information in each pixel segment based on a one-dimensional pixel sequence, for all pixel segments within the selected range, the relationship between a preset complexity threshold and the complexity of each pixel segment is used. Set the size of the pixel segment to s; For a pixel segment, obtain the pixels {p, z1, z2, ..., z} in the order of global sorting. s-1 }, where p represents the pixel to be embedded, z1, z2, ..., z s-1 This represents the predicted pixels used to predict p; all pixel segments are obtained sequentially in global sorting order, with an interval of one pixel. Calculate the single-pixel sorting prediction value of the pixel p to be embedded in each pixel segment; The computational complexity of calculating each pixel segment is C. Seq ; For each obtained pixel segment, the prediction error of the pixel to be embedded, p, is calculated sequentially; the complexity threshold T is then compared with the complexity C of each pixel segment. Seq Compare, if C Seq >T then skips the pixel segment; if C Seq If the value is less than or equal to T, then secret information is embedded into the pixel segment.

5. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 4, characterized in that, The step of calculating the single-pixel sorting prediction value of the pixel to be embedded p in each pixel segment is as follows: for each pixel segment {p, z1, z2, ..., z...} s-1 }, using the predicted pixels {z1,z2,…,z} according to the following formula s-1 } Obtain the sorted prediction values ​​of the two single pixel values ​​of the pixel to be embedded, p. and The computational complexity C for each pixel segment is... Seq In the steps, for each pixel segment {p,z1,z2,…,z} s-1 The complexity C of calculating a pixel segment is given by the following formula. Seq : In the formula, C p , These are the calculated pixel values ​​p, z1, z2...z s-1 pixel complexity; For each pixel segment obtained by sequential access, the prediction error of the pixel to be embedded, p, is calculated; the complexity threshold T is then compared with the complexity C of each pixel segment. Seq Compare, if C Seq >T then skips the pixel segment; if C Seq The specific steps for embedding secret information into pixel segments ≤T are as follows: for each pixel segment {p,z1,z2,…,z…} s-1 The predicted values ​​are sorted using the single pixel values ​​according to the following formula. and Calculate the prediction error e: In the formula, This indicates that there is no prediction error; For each pixel segment {p, z1, z2, ..., z} s-1 }, compare the complexity threshold T with the complexity C of each pixel segment. Seq Compare, if C Seq If > T, skip the current pixel segment; if C Seq If the value is less than or equal to T, then check the prediction error of the pixel to be embedded in the pixel segment. If the error does not exist, skip the current pixel segment; otherwise, embed the secret information into pixel p according to the following formula: In the formula, This represents the modified pixel; sd∈{0,1} represents the embedded secret information bits.

6. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 1, characterized in that, In the steps of acquiring the original carrier image and performing anti-overflow operations to obtain the processed carrier image; and based on the original carrier image, acquiring a position array that records the overflow and underflow positions, Traverse all pixels of the original carrier image except the first row in raster scan order, set the parameter k to an initial value of 1, and perform the following operation on each pixel: In the formula, p represents the pixel value that is traversed; LM is a position array, a one-dimensional vector used to record the position of pixels whose pixel values ​​have been adjusted; Arithmetic compression of the LM is performed to reduce the number of bits required by the recorder, resulting in the compressed position array CLM.

7. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 6, characterized in that, The step of embedding the auxiliary information required for restoring the carrier image and extracting information into the first row of pixels of the processed carrier image is as follows: For a carrier image of size H×W, record the first row of pixels. The least significant bits of each pixel are combined with the secret information; the original first row is then merged with the first significant bits of each pixel. The least significant bit is replaced by auxiliary information; the auxiliary information includes the pixel segment size s used, occupying 3 bits; the complexity threshold T of the four layers, occupying 4×12=48 bits; and the last position P of the four-layer embedding. end Occupy Bit, Indicates rounding up; the length l of the compressed position array CLM. CLM Occupy Bit.

8. The method for reversible information hiding based on global sorting of single pixel values ​​according to claim 7, characterized in that, After obtaining the final encrypted carrier image, a decoding step is also included; among which, The decoding step includes: reading the first line of the final encrypted carrier image. The least significant bit of each pixel is used to obtain auxiliary information for decoding; wherein, the auxiliary information for decoding includes the pixel segment size s, the complexity threshold T of the four layers, and the last position P of the four-layer embedding. end and the length l of the compressed position array CLM CLM ; The decoding sequence is the reverse of the embedding stage; For decoding each pixel layer, perform a global sort in the same manner as during embedding, calculate the complexity of all pixel segments of size s, and then start from the last embedding position P of the pixel layer. end Initially, a pixel segment of size s is acquired, and the relationship between the pixel segment's complexity and the complexity threshold T guides the pixel segment to be decoded or skipped. After decoding a pixel segment, the next pixel segment is acquired at one-pixel intervals in the opposite direction to the embedding stage, and the next pixel segment is attempted to be decoded, until all pixel segments are decoded. The least significant bit corresponding to the first row of the decoded secret information. Bit secret information and the current first line The least significant bit of the pixel is replaced; The corresponding CLM l CLM The secret information of the bits is extracted and decompressed to obtain the position array LM. The pixel values ​​that were originally protected against overflow are restored using LM.

9. A reversible information hiding system based on global sorting of single-pixel values, characterized in that, include: The preprocessing module is used to acquire the original carrier image and perform anti-overflow operations to obtain the processed carrier image; Based on the original carrier image, obtain a position array that records the overflow and overflow positions; The global sorting module is used to divide the processed carrier image (excluding the first row) into four pixel layers, calculate the predicted value and complexity of all pixels in each pixel layer in order, and sort the pixels of each pixel layer globally based on the predicted value and complexity of the pixels to obtain a one-dimensional pixel sequence. The prediction and embedding module is used to guide whether to embed secret information in each pixel segment based on a one-dimensional pixel sequence and for all pixel segment sizes within a selected range, according to the relationship between a preset complexity threshold and the complexity of each pixel segment. Specifically, for the selected current pixel segment size, the module calculates the pixel segment complexity and the single pixel value sorting prediction error of each pixel segment. Based on the relationship between pixel segment complexity and the complexity threshold, it guides whether to use the pixels to be embedded in each pixel segment for embedding secret information. The module embeds the secret information into the processed carrier image according to the prediction error value. Then, it embeds the auxiliary information required for restoring the carrier image and extracting information into the first row of pixels of the processed carrier image to obtain a secret-containing carrier image. The auxiliary information includes a position array recording overflow and overflow positions, pixel segment size, and complexity threshold. The final dense carrier image acquisition module is used to compare the degree of distortion of the dense carrier image with the original carrier image under different pixel segment sizes, and select the dense carrier image with the lowest degree of distortion as the final dense carrier image.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the reversible information hiding method based on global sorting of single pixel values ​​as described in any one of claims 1 to 8.

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