Method, device, equipment and storage medium for joining edge of DOM data

Abstract

The present application provides a method, device, equipment and storage medium for joining DOM data. It relates to the field of map joining technology. The method includes: pre-coding pixels whose edges are offset from the map range into a pre-coding matrix; vectorizing the pixel values ​​in the pre-coding matrix and converting them into a binary sequence, hiding information in the binary sequence starting from the identification bit to obtain a secret data set; extracting the identification bit and the map size based on the secret data set, using the identification bit and the map size to organize the pre-coding matrices of the upper, lower, left and right edges respectively, and extracting the hidden information starting from the identification bit, using the inverse operation of information hiding to extract the hidden information and fill it into the pre-coding matrix; using the filled pre-coding matrix to perform non-overlapping joining according to the spatial relationship between the maps, and fill in the missing pixel information. The present application solves the problem of incomplete data in the splicing of adjacent maps after the geometric accuracy of DOM data is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of image sheet splicing, and in particular to a method, device, equipment and storage medium for splicing DOM data. Background Art

[0002] Due to the large storage requirements of DOM data, it is typically segmented and stored according to the extent of the map frame. Each frame represents a relatively small area, facilitating data management and processing. To facilitate wide-scale applications, these frames are often spliced ​​together to produce large-scale image products. When the geometric accuracy of segmented DOM data is reduced, the edge pixels of each frame will shift outside the frame extent. During splicing, these pixels cannot be restored due to the lost pixel information, resulting in incomplete data at the edge of the spliced ​​frames. As the scale of geometric reduction increases, the number of missing pixels in the edge region increases, affecting the usability and integrity of the spliced ​​DOM data. During the geometric reduction process, some pixels are lost at the edges of the image, including at the top, bottom, left, and right edges. The number of pixels that shift outside the frame extent varies from region to region, necessitating encoding methods to organize the pixels in these regions. Information hiding technology can hide pixels that are offset from the image range. When splicing is required, the corresponding hidden pixel information is taken from the carrier image and filled into the edge area to reconstruct the missing information in the edge area.

[0003] Information hiding involves hiding secret information within a hidden carrier to conceal and transmit confidential information. Information hiding is crucial for digital signatures, authentication, and integrity protection. With the advancement of technology, information hiding can be embedded in a variety of carriers, such as images. Image information hiding, which uses images as carriers, is a key area of ​​research. This technique leverages image characteristics such as color, depth, and storage method to hide secret information within the image, effectively transmitting the secret information.

[0004] In image information hiding, there are two main methods: spatial domain and transform domain. The transform domain involves transforming an image from the spatial domain to another transform domain, then modifying or compressing the coefficients in that domain to achieve information hiding. Common transforms include discrete cosine transform, discrete wavelet transform, and discrete Fourier transform. These transforms essentially convert an image from the spatial domain to a corresponding transform domain, hide the secret information in the transform domain coefficients, and then convert it back to the spatial domain, hiding the secret information without significantly altering the image's visual appearance. The spatial domain hides information by directly modifying the image's pixel values. Spatial domain information hiding algorithms operate directly on the spatial domain of the image, without requiring frequency domain conversion. Spatial domain algorithms generally have high hiding capacity and good invisibility. Both transform and spatial domain information hiding are relatively mature technologies. The transform domain is highly resilient, resisting attacks such as rotation, scaling, and shearing. However, the transform domain has a lower hiding capacity and is therefore more commonly used in scenarios where the security of the hidden information is critical. Spatial domain transformation is relatively simple and intuitive, the hiding process is relatively easy to implement, and the hiding capacity is very high. The quality of the hidden image is also relatively high, but the data security after hiding is not high. It is suitable for scenarios with high requirements for hiding capacity. Summary of the Invention

[0005] The present application provides a method, apparatus, device and storage medium for joining framed DOM data edges, so as to solve the problem that, during the process of processing DOM data with reduced geometric precision, some edge pixel information is offset outside the image frame, resulting in information loss. After the framed DOM data edges are joined, the information of these lost pixels becomes incomplete in the joined area.

[0006] In a first aspect, the present application provides a method for joining edge portions of DOM data, comprising:

[0007] Acquire the frame DOM data, use the frame length and frame width of the frame DOM data to precode the offset pixel information respectively, and precode the pixels whose edges are offset from the frame range into a precoding matrix;

[0008] Vectorizing the pixel values ​​in the precoding matrix and converting them into a binary sequence, performing information hiding on the binary sequence starting from the identification bit to obtain a encrypted data set;

[0009] Extracting a flag bit and an image size based on the encrypted data set, organizing precoding matrices for the upper, lower, left, and right edges using the flag bit and the image size, extracting hidden information starting from the flag bit, and extracting the hidden information using an inverse information hiding operation and filling the hidden information into the precoding matrix;

[0010] The filled precoding matrix is ​​used to perform non-overlapping edge joining according to the spatial relationship between the image sheets, fill in the missing pixel information, and obtain the edge-joined data.

[0011] In a possible design, the image sheet length and image sheet width of the DOM data are used to precode the offset pixel information respectively, and the pixels whose edges are offset from the image sheet range are precoded into a precoding matrix, including:

[0012] Obtain the pixel widths that exceed the range in four directions of the map sheet during the geometric accuracy reduction process and the width of the range to be hidden; wherein the width of the range to be hidden is the maximum pixel width that deviates from the map sheet range in the upward, downward, left, and right directions during the geometric accuracy reduction process;

[0013] Based on the pixel widths that exceed the range in four directions of the map during the geometric accuracy reduction process, the pixels that exceed the map range in the top, bottom, left, and right directions are sequentially encoded into a first matrix; wherein the first matrix includes encoding matrices for the top, bottom, left, and right regions;

[0014] The uniform size of the precoding matrix is ​​determined based on the width of the range to be hidden, the image length, and the image width, and the first matrix is ​​filled to obtain multiple precoding matrices.

[0015] In one possible design, the sizes of the coding matrices of the upper, lower, left, and right regions are expressed as:

[0016] ;

[0017] Where, H Indicates the length of the image. W Indicates the width of the image, max indicates the maximum value function, 、 、 、 Respectively represent the pixel widths that are out of range in the left, right, up, and down directions. Matrix left,c 、 Matrix right,c 、 Matrix top,c and Matrix bottom,c They represent the left region coding matrix, the right region coding matrix, the upper region coding matrix and the lower region coding matrix respectively.

[0018] In one possible design, the uniform size of the precoding matrix is or , L is the width of the range to be hidden, and the first matrix is ​​filled using the following formula to obtain multiple precoding matrices:

[0019] ;

[0020] Where, represents the precoding matrix, represents the encoding matrix after filling, ( x , y ) represents the filled matrix Index position, represents the encoding matrix before padding, represents the precoding matrix The index position of represents the precoding matrix The index position of the precoding matrix is ​​mapped as follows:

[0021] Left edge: ;

[0022] Right edge: ;

[0023] Top edge: ;

[0024] Bottom edge: ;

[0025] in, x,y Represents each edge matrix after filling The matrix size of .x represents the matrix width and y represents the matrix length.

[0026] In one possible design, information hiding is performed on the binary sequence starting from the identification bit to obtain a encrypted data set, including:

[0027] generating hidden information based on the binary sequence;

[0028] Determine the hidden information embedding area and the starting position of the identification bit according to the size of the DOM data;

[0029] Based on the starting position of the identification bit, the hidden information is hidden in the frame DOM data in a set order to obtain a encrypted data set.

[0030] In one possible design, the binary sequence includes hidden carrier pixel values as well as The binary sequence is used to generate hidden information, including:

[0031] Get the hidden vector pixel value as well as Bit binary information to be hidden;

[0032] Will The bit binary information to be hidden is converted into Base digits ;

[0033] According to the following formula Base digits Hide to hide the carrier pixel value :

[0034] ;

[0035] Where, f Represents an intermediate value calculated by the above formula, indicating that the carrier pixel value will be hidden After adding the adjustment amount k, Modulo result, k Represents an adjustment amount, whose value is ,when When the hidden pixel value , using the hidden pixel value as the hidden information.

[0036] In a possible design, the hidden information embedding area is determined according to the size of the DOM data frame by the following formula:

[0037] ;

[0038] Where, Indicates the hidden information embedding area, Represents the pixel value matrix of DOM data after geometric precision reduction, i represents the matrix row index, j represents the matrix column index, , , H Indicates the length of the image. W Indicates the width of the image. Indicates the identification bit, which is the maximum value of all edge retraction widths in the DOM data of the frame;

[0039] The identification bit is determined by the following formula M Starting position:

[0040] ;

[0041] Where, location M Indicates the flag M The starting position, The pixel value matrix representing the DOM data after geometric precision reduction is used to extract hidden information.

[0042] In a second aspect, the present application provides a device for joining edge portions of DOM data, the device comprising:

[0043] The hidden information preprocessing module is configured to obtain the frame DOM data, precode the offset pixel information using the frame length and frame width of the frame DOM data, and precode the pixels whose edges are offset from the frame range into a precoding matrix;

[0044] an edge information hiding module configured to vectorize the pixel values ​​in the pre-coding matrix and convert them into a binary sequence, and perform information hiding on the binary sequence starting from the identification bit to obtain a encrypted data set;

[0045] an edge information extraction module configured to extract a marker and an image size based on the encrypted data set, organize precoding matrices for the upper, lower, left, and right edges using the marker and image size, extract hidden information starting from the marker, and extract the hidden information using an inverse information hiding operation and fill the precoding matrix with the hidden information;

[0046] The image splicing module is configured to use the filled precoding matrix to perform non-overlapping splicing according to the spatial relationship between the image sheets, fill in the missing pixel information, and obtain the spliced ​​data.

[0047] In a third aspect, an embodiment of the present application provides an electronic device, comprising: at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the method for joining edge portions of DOM data as described in the first aspect and various possible designs of the first aspect.

[0048] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When a processor executes the computer-executable instructions, the method for joining edge portions of DOM data as described in the first aspect and various possible designs of the first aspect is implemented.

[0049] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for joining edge portions of DOM data as described in the first aspect and various possible designs of the first aspect is implemented.

[0050] The method, device, equipment, and storage medium for joining DOM data frames provided in this application have at least the following beneficial effects:

[0051] This application uses information hiding technology to hide information about missing pixels at the edges of DOM data. When the images meet, this hidden information is extracted and used to fill in the edge regions, thereby maintaining the integrity and usability of the data in these regions. Experiments have shown that this application effectively maintains the integrity of the data in these regions while ensuring the invisibility of the information hiding. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0053] Figure 1 A local diagram of the edge region according to the prior art;

[0054] Figure 2 The process of a method for joining edge of DOM data provided in the embodiment of the present application is as follows Figure 1 ;

[0055] Figure 3 The process of a method for joining edge of DOM data provided in the embodiment of the present application is as follows Figure 2 ;

[0056] Figure 4 A schematic diagram of the lower edge matrix encoding method provided in an embodiment of the present application;

[0057] Figure 5 This is a flowchart of information hiding in the framed DOM data edge joining method provided in an embodiment of the present application;

[0058] Figure 6 A flowchart of embedding hidden information in the framed DOM data edge joining method provided in an embodiment of the present application;

[0059] Figure 7 This is a flowchart of hidden information extraction in the framed DOM data edge joining method provided in an embodiment of the present application;

[0060] Figure 8 A schematic diagram of the filling area provided in an embodiment of the present application;

[0061] Figure 9 This is a flowchart of the image splicing method in the frame DOM data edge joining method provided in an embodiment of the present application;

[0062] Figure 10 This is a schematic diagram of 9 frames of experimental data provided in the embodiments of the present application;

[0063] Figure 11 A comparison diagram before and after splicing provided in the embodiment of the present application;

[0064] Figure 12 This is a structural diagram of the device for joining edge portions of DOM data provided in an embodiment of the present application.

[0065] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0066] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0067] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of information such as financial data or user data involved comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0068] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0069] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0070] When the geometric accuracy of the DOM data is reduced, some edge pixels will be offset from the map range. When these pixels are offset from the map range, the lost pixel information cannot be restored during splicing, resulting in incomplete data in the edge area of ​​the spliced ​​map. Figure 1 shown.

[0071] The key to maintaining data integrity in the adjacent DOM data splicing areas after geometric accuracy is reduced lies in whether the lost pixel information can be restored. Based on this, the embodiment of the present application provides a method for splicing DOM data in separate frames. This method uses information hiding technology to hide the pixel information that is offset from the image frame range when geometric accuracy is reduced into the data after the geometric accuracy is reduced. When splicing is required, the hidden information is extracted from the data to complete the splicing, thereby maintaining the integrity and availability of adjacent DOM data. Figure 1 The figure shows the process of the method for joining the edge of the DOM data provided by the embodiment of the present application. Figure 1 This method, used to process DOM data, consists of three parts: hidden information preprocessing, edge information hiding and extraction, and map stitching. In the hidden information preprocessing, the acquired DOM data undergoes geometric precision reduction, over-limit pixel acquisition, over-limit pixel quantization encoding, and precoding matrix filling, resulting in a regular matrix that facilitates information hiding and extraction. The second part includes an edge information hiding process and an edge information extraction process. The edge information hiding process obtains a classified dataset through matrix vectorization, identification bit acquisition, and SB information hiding. The edge information extraction process is the inverse of the edge information hiding process. Based on the classified dataset, identification bit acquisition and SB inverse operations are performed to construct a precoding matrix, and the missing pixel information is determined based on the precoding matrix. In the map stitching process, based on the determined missing pixel information, the missing pixel information is filled through the operations of determining the spatial relationship of the map, determining the index relationship of the sub-frames, filling the dataless area, and then stitching the map.

[0072] Specifically, if Figure 3 The figure shows the process of the method for joining the edge of the DOM data provided by the embodiment of the present application. Figure 2 The method for joining edge portions of DOM data includes the following steps S100-S400.

[0073] S100: Obtaining frame DOM data, pre-coding offset pixel information using the frame length and frame width of the frame DOM data, and pre-coding pixels whose edges are offset from the frame range into a pre-coding matrix.

[0074] In this embodiment, step S100 preprocesses edge loss pixel information. To address the issue of inconsistent pixel counts due to reduced geometric accuracy in DOM data, the length and width of the image sheet are used to precode the offset pixel information. Each pixel with an edge offset outside the image sheet is precoded into a regular matrix (i.e., a precoding matrix) to facilitate concealment and extraction.

[0075] In some embodiments, due to the loss of some edge information during the geometric precision reduction process, information loss may occur at the top, bottom, left, and right edges. However, not all information at each edge will be offset outside the image frame; it may retract into the image, resulting in no data values ​​at the retracted portion.

[0076] Therefore, the pixel width that exceeds the range in the four directions of the map during the process of reducing geometric accuracy is set to 、 、 、 . Assume the width of the range to be hidden is , The value is taken as the maximum pixel width that is offset from the map range in the process of reducing geometric accuracy, that is, .

[0077] Since the amount of offset in each area is different, in order to facilitate hiding and extraction, the data needs to be encoded. First, the data that exceeds the map size is counted, and then the pixels that exceed the map range in the top, bottom, left, and right directions are encoded in order into the first matrix. , .

[0078] The sizes of the coding matrices for the upper, lower, left, and right regions are shown in the following formula:

[0079] ;

[0080] Where, H Indicates the length of the image. W Indicates the width of the image, max indicates the maximum value function, 、 、 、 Respectively represent the pixel widths that are out of range in the left, right, up, and down directions. Matrix left,c 、 Matrix right,c 、 Matrix top,c and Matrix bottom,c They represent the left region coding matrix, the right region coding matrix, the upper region coding matrix and the lower region coding matrix respectively.

[0081] Encoded matrix The size may not be satisfied If there are pixels that are offset out of range, set the pixel value at that position to the original pixel value of the offset pixel. If there are no pixels that are offset out of range, set the pixel value to 0. After filling, ensure that the matrix has a uniform size of or , the matrix after filling is or , that is, The matrix after filling a certain edge of a band. The filling formula is:

[0082] ;

[0083] Where, represents the precoding matrix, represents the encoding matrix after filling, ( x , y ) represents the filled matrix Index position, represents the encoding matrix before padding, is the encoding matrix Index position.

[0084] The index mapping rules are:

[0085] Left edge: ;

[0086] Right edge: ;

[0087] Top edge: ;

[0088] Bottom edge: ;

[0089] in, x,y Represents each edge matrix after filling The matrix size of .x represents the matrix width and y represents the matrix length.

[0090] Taking the lower edge as an example, the area where the lower edge exceeds the image frame is , the filled matrix , R is a set of real numbers, and the filling method is as follows:

[0091] ;

[0092] Combined with images where the lower edge is arranged as Figure 4 shown. Figure 4 The circled area on the left is the data that is offset from the map range, and the circled area on the right is the retraction area, with a length of , with a width of The order of is encoded as a regular matrix, In the matrix, the missing positions are filled with 0.

[0093] S200: Vectorize the pixel values ​​in the pre-coding matrix and convert them into a binary sequence. Hide the binary sequence starting from the identification bit to obtain a encrypted data set.

[0094] In some embodiments, as Figure 5 FIG. 2 is a flowchart of information hiding in the method for joining edge portions of DOM data provided by an embodiment of the present application. Step S200 can be implemented through the following steps S210 to S230.

[0095] S210: Generate hidden information based on the binary sequence.

[0096] In DOM data, pixels display color information through pixel values. Each pixel in each band channel has a pixel value information, which is generally 0-255. If the pixel value is directly hidden, the data usability will be greatly reduced or even unusable. Therefore, the value needs to be converted into a binary sequence. For example, if a pixel value is 36, the binary sequence is In order to facilitate hiding and extraction, the six-bit binary data is converted into an eight-bit binary sequence. . Convert the eight-bit binary sequence Split, split into , , , Four sets of binary sequences.

[0097] Exemplarily, hidden information can be generated by the following steps:

[0098] S211: Input 1 hidden carrier pixel value , Bits of binary information to be hidden.

[0099] S212: The bit binary information to be hidden is converted into Base digits .

[0100] S213: According to formula 4.2, Base digits Hide into 1 hidden carrier pixel value In the formula (2-4):

[0101] ;

[0102] In the formula f Represents an intermediate value calculated by the above formula, indicating that the carrier pixel value will be hidden After adding the adjustment amount k, Modulo result, k Represents an adjustment amount, whose value is ,when When the hidden pixel value , using the hidden pixel value as the hidden information.

[0103] S220: Determine the hidden information embedding area and the starting position of the identification bit according to the size of the frame DOM data.

[0104] After the hidden information is encoded in step S210, it is necessary to select a hidden area for the DOM data after the geometric accuracy is reduced. The hidden information embedding area is determined according to the following formula based on the size of the DOM data:

[0105] ;

[0106] Where, Indicates the hidden information embedding area, Represents the pixel value matrix of DOM data after geometric precision reduction, i represents the matrix row index, j represents the matrix column index, , , identification bit The maximum value of all edge retraction widths in the image.

[0107] In order to perform blind extraction, it is necessary to extend the width of each edge beyond the image range. To hide, As a flag, its function is to hide Extract the value of The starting position calculation formula is:

[0108] ;

[0109] Where, location M Indicates the flag M The starting position, The pixel value matrix representing the DOM data after geometric precision reduction is used to extract hidden information.

[0110] S230: Based on the starting position of the identification bit, the hidden information is hidden in the DOM data in a set order to obtain a encrypted data set.

[0111] For example, from the identification bit Start by hiding in the image in reverse order. Convert it into an 8-bit binary sequence and hide it in the image using the SB information hiding algorithm.

[0112] In an exemplary embodiment, Figure 6The figure shows a flowchart for embedding hidden information in the method for joining framed DOM data provided by an embodiment of the present application. Based on the original data (DOM data), the image size is first obtained and the geometric precision is reduced to obtain framed DOM data. Based on this framed DOM data, a padded encoding matrix is ​​obtained by obtaining over-limit pixels, organizing them in sequence, setting flags, and constructing a pre-coding matrix. It should be noted that the geometric precision reduction algorithm used to obtain the framed DOM data can be a known algorithm and will not be elaborated on in detail in this embodiment. However, obtaining the padded encoding matrix has been described in step S100 above and will not be repeated here. After obtaining the padded encoding matrix, the encoding matrix is ​​vectorized. The vectorized encoding matrix and flags are converted to decimal to obtain a hidden information embedding area and a flag embedding area, respectively. Further, using SB information hiding, the hidden information is embedded into the framed DOM data (e.g., a framed image) using either sequential or reverse embedding. Ultimately, data containing hidden information is obtained. Multiple hidden information data sets constitute a coded data set.

[0113] S300: Extract the identification bit and image size based on the encrypted data set, use the identification bit and image size to organize the precoding matrices of the upper, lower, left, and right edges respectively, and extract the hidden information starting from the identification bit. Use the inverse operation of information hiding to extract the hidden information and fill it into the precoding matrix.

[0114] In this embodiment, the purpose of step S300 is to extract hidden information. The hidden information extraction process is the inverse process of the hiding process.

[0115] In an exemplary embodiment, Figure 7 The figure shows a flowchart of hidden information extraction in the DOM data edge joining method provided by the embodiment of the present application. According to the encrypted data set obtained in step S200, taking a data containing hidden information in the encrypted data set as an example, the precoding matrix is ​​reconstructed by obtaining the image size, obtaining the area without data value, extracting the identification bit and constructing the precoding matrix. While extracting the identification bit, the hidden information is extracted through hidden information extraction, that is, SB information hiding inverse operation, grouping, binary conversion and vectorization of hidden information. The hidden information is then sequentially filled into the reconstructed precoding matrix, and finally the hidden pixel information can be obtained. In the specific implementation, the maximum width of the invalid pixel value in the image is first obtained. , find the starting position of the marker from the map , then starting from the flag bit, extract the hidden range width in reverse order , then according to the size of the map and the width of the range Calculate the number of bits of hidden information corresponding to the top, bottom, left, and right of the image. Then Start extracting information from the pixel, and each pixel can extract two bits Sequence, every eight bits The sequence can be converted back to the hidden pixel value through the inverse operation of the SB algorithm, and the extracted upper and lower, left and right pixel values ​​are converted according to and The size of is reorganized into a matrix in the order of arrangement . That is, the extraction of hidden information is completed.

[0116] For example, the process of extracting hidden information using the inverse operation of information hiding can be: obtaining the hidden pixel value , according to the formula Calculate Base digits ,Will Base digits Convert to Hidden information in binary.

[0117] S400: Using the filled pre-coding matrix, performing non-overlapping edge joining according to the spatial relationship between the image sheets, filling in the missing pixel information, and obtaining the edge-joined data.

[0118] In the process of splicing the images, it is necessary to judge the spatial relationship between the images, and then extract information from the corresponding adjacent images according to the location of the invalid pixel values ​​in the images to fill the invalid pixel values. Figure 8 As shown, Figure 8 The pixel information needed for region 1 is extracted from the hidden information in the adjacent data piece above it. Region 2 is extracted from the data piece below it. Region 3 is extracted from the data piece adjacent to the left. Region 4 is extracted from the data piece adjacent to the right. The extracted information is then used to fill in the areas corresponding to invalid pixel values.

[0119] In an exemplary embodiment, Figure 9 The figure shows a flow chart for splicing frames in the method for joining framed DOM data provided in an embodiment of the present application. When performing frame splicing, framed data containing hidden information (data processed in step S200) is obtained. A coordinate range is obtained based on the basic information of the framed data. Based on the coordinate range, result data R (such as a pixel information matrix) is generated. Based on the pixel information of the framed data, result data R1 (including missing pixel information or pixel information to be filled) is obtained. Furthermore, identification bits are extracted, hidden information is extracted, and a precoding matrix is ​​obtained. Subsequently, spatial position arrangement is performed, and the frame intersection area is determined based on the frame index matrix. The precoding matrix is ​​used to fill in result data R1 to obtain result data R2. Result data R2 is then formatted, such as by converting the matrix format to an image format. This results in the obtained joined data, completing the entire frame splicing process.

[0120] The feasibility and progress of the method proposed in this application will be further demonstrated by combining specific experiments below.

[0121] The data A used in this embodiment is divided into 9 frames, and the 9 frames are numbered as b_0, b_1, b_2, b_3, b_4, b_5, b_6, b_7, b_8. The experiment is carried out with the geometric accuracy reduced to 10m. After processing, the experimental data is as follows Figure 10 Based on the data A, the information hiding results, information hiding extraction results and image splicing results are used to prove that the present application can achieve significant results.

[0122] This embodiment uses invisibility to evaluate information hiding results. In information hiding, invisibility is a very important evaluation metric. In DOM data, quantitative evaluation methods can be used, such as mean square error (MSE), peak signal-to-noise ratio (PSNR), and structure similarity index measure (SSIM). The mean square error and peak signal-to-noise ratio are commonly used. The mean square error is usually calculated as the difference between corresponding pixels in two images. Its calculation formula is:

[0123] ;

[0124] Where, 、 The first one among the original carrier and the hidden carrier Row and The pixel value of the column.

[0125] The smaller the value, the smaller the change in pixel value in the image, and the higher the image quality. However, this value is greatly affected by outliers and may not accurately evaluate the overall image. To evaluate the image quality.

[0126] The calculation formula is as follows:

[0127] ;

[0128] In the formula Indicates the maximum value of the pixel value in the image. The unit of is decibel (dB). The higher the decibel, the more similar the original carrier is to the hidden carrier, and the smaller the difference between the pixel values. When the value is not less than 30dB, the human visual perception system cannot perceive the difference.

[0129] For 9-frame images and The evaluation results are shown in Table 1:

[0130] Table 1 Evaluation table of mean square error and peak signal-to-noise ratio for 9 frames

[0131]

[0132] Similarly, in the nine-frame image, the mean square error (MSE) ranges from 1.2522 to 1.2710, indicating similarly small image differences. The PSNR is around 47dB, also greater than 30dB, indicating high image quality. Furthermore, because each image is smaller in the nine-frame image compared to the four-frame image, the mean square error and PSNR decrease somewhat. However, the average MSE per image is below 1.27, and the average PSNR is greater than 47dB. Overall, regardless of whether the image is framed in four or nine frames, the image quality after information embedding is high. The invisibility of the image hiding is excellent.

[0133] For the information hiding extraction results, first determine the extracted area according to the maximum width of the invalid pixel value in the map, and then obtain the hidden flag from the extracted area The position of the extraction area is extracted from the first pixel in the lower right corner, and the flag bit is extracted in reverse order. , that is, the maximum width , according to the maximum width and the length of the image He Kuan , arrange the matrices of each edge, then extract the hidden information according to the previous embedding order, and fill it into the arranged matrix in order to obtain the hidden information.

[0134] The bit error rate (BER) is the ratio of the number of bits that are erroneous during signal transmission to the total number of bits transmitted. Errors may occur during data transmission, resulting in incorrect secret information being extracted. Therefore, the accuracy of secret information extraction can also be evaluated using the BER. Its calculation formula is:

[0135] ;

[0136] Where, Indicates the number of bits in error, is the total number of bits.

[0137] Using the bit error rate evaluation index, the 4-frame and 9-frame images of this section are combined into data Data1 and Data2 for overall analysis. Using the bit error rate evaluation index, the bit error rate of the hidden information extracted is shown in Table 2:

[0138] Table 2 Data1 and Data2 bit error rates

[0139]

[0140] When detecting embedded information, operations are performed directly from the pixel values ​​without any attacks. When extracting information arranged in this way, the pixel value information can be correctly extracted, and the extracted information can be used for map splicing.

[0141] For the image splicing results, the spatial relationship between adjacent images is determined based on the extracted hidden information, and then the framed images are spliced. The 9 images in the frame are spliced ​​separately, and the splicing results are compared. Figure 11 As shown in the figure, after zooming in on some of the spliced ​​areas to show details, the terrain and roads can be well matched without any splits or breaks, and the visual effect of the map splicing is good.

[0142] Judging from the overall visual effect of the 9 images after splicing, the visual features at all the edge positions of the images are good, the roads and landforms at the seams can be well spliced, the continuity at the image seams is good, and there is no big difference in the images after splicing. The visual effect is good. It can be considered that the use of information hiding for image edge splicing is highly feasible.

[0143] The experiments above demonstrate that the proposed method, based on edge information hiding technology, uses a precoding mechanism and information hiding to hide the information of pixels that have shifted outside the map frame during the geometric precision reduction process of DOM data. This hidden information and the spatial relationship matrix are then used to fill in missing areas when the map frames are joined. The experiments demonstrate that the hidden data is highly invisible, and the information in the joined regions is complete. This solves the problem of data incompleteness when joining adjacent map frames after the geometric precision of DOM data has been reduced.

[0144] The embodiment of the present application also provides a device for joining edge of DOM data. Figure 12 As shown, the DOM data edge joining device includes:

[0145] The hidden information preprocessing module 1201 is configured to obtain the frame DOM data, precode the offset pixel information using the frame length and frame width of the frame DOM data, and precode the pixels whose edges are offset from the frame range into a precoding matrix;

[0146] The edge information hiding module 1202 is configured to vectorize the pixel values ​​in the pre-coding matrix and convert them into a binary sequence, and perform information hiding on the binary sequence starting from the identification bit to obtain a encrypted data set;

[0147] The edge information extraction module 1203 is configured to extract the identification bit and the image size based on the encrypted data set, organize the precoding matrices of the upper, lower, left, and right edges respectively using the identification bit and the image size, and extract the hidden information starting from the identification bit, extract the hidden information using the inverse information hiding operation, and fill the hidden information into the precoding matrix;

[0148] The image splicing module 1204 is configured to use the filled pre-coding matrix to perform non-overlapping splicing according to the spatial relationship between the image sheets, fill in the missing pixel information, and obtain the spliced ​​data.

[0149] In some embodiments, the hidden information preprocessing module is further configured to:

[0150] Obtain the pixel widths that exceed the range in four directions of the map sheet during the geometric accuracy reduction process and the width of the range to be hidden; wherein the width of the range to be hidden is the maximum pixel width that deviates from the map sheet range in the upward, downward, left, and right directions during the geometric accuracy reduction process;

[0151] Based on the pixel widths that exceed the range in four directions of the map during the geometric accuracy reduction process, the pixels that exceed the map range in the top, bottom, left, and right directions are sequentially encoded into a first matrix; wherein the first matrix includes encoding matrices for the top, bottom, left, and right regions;

[0152] The uniform size of the precoding matrix is ​​determined based on the width of the range to be hidden, the image length, and the image width, and the first matrix is ​​filled to obtain multiple precoding matrices.

[0153] In some embodiments, the sizes of the coding matrices of the upper, lower, left, and right regions are expressed as:

[0154] ;

[0155] Where, H Indicates the length of the image. W Indicates the width of the image, max indicates the maximum value function, 、 、 、 Respectively represent the pixel widths that are out of range in the left, right, up, and down directions. Matrix left,c 、 Matrix right,c 、 Matrix top,c and Matrix bottom,c They represent the left region coding matrix, the right region coding matrix, the upper region coding matrix and the lower region coding matrix respectively.

[0156] In some embodiments, the uniform size of the precoding matrix is or , L is the width of the range to be hidden, and the hidden information preprocessing module is further configured to fill the first matrix according to the following formula to obtain multiple precoding matrices:

[0157] ;

[0158] Where, represents the precoding matrix, represents the encoding matrix after filling, ( x , y ) represents the filled matrix Index position, represents the encoding matrix before padding, represents the precoding matrix The index position of the precoding matrix is ​​mapped as follows:

[0159] Left edge: ;

[0160] Right edge: ;

[0161] Top edge: ;

[0162] Bottom edge: ;

[0163] in, x,y Represents each edge matrix after filling The matrix size of .x represents the matrix width and y represents the matrix length.

[0164] In some embodiments, the edge information hiding module is further configured to:

[0165] generating hidden information based on the binary sequence;

[0166] Determine the hidden information embedding area and the starting position of the identification bit according to the size of the DOM data;

[0167] Based on the starting position of the identification bit, the hidden information is hidden in the frame DOM data in a set order to obtain a encrypted data set.

[0168] In some embodiments, the binary sequence includes hidden carrier pixel values as well as The edge information hiding module is further configured as follows:

[0169] Get the hidden vector pixel value as well as Bit binary information to be hidden;

[0170] Will The bit binary information to be hidden is converted into Base digits ;

[0171] According to the following formula Base digits Hide to hide the carrier pixel value :

[0172] ;

[0173] Where, f Represents an intermediate value calculated by the above formula, indicating that the carrier pixel value will be hidden After adding the adjustment amount k, Modulo result, k Represents an adjustment amount, whose value is, ,when When the hidden pixel value , using the hidden pixel value as the hidden information.

[0174] In some embodiments, the edge information hiding module is further configured to determine the hidden information embedding area according to the size of the framed DOM data using the following formula:

[0175] ;

[0176] Where, Indicates the hidden information embedding area, Represents the pixel value matrix of DOM data after geometric precision reduction, i represents the matrix row index, j represents the matrix column index, , , H Indicates the length of the image. W Indicates the width of the image. Indicates the identification bit, which is the maximum value of all edge retraction widths in the DOM data of the frame;

[0177] The identification bit is determined by the following formula M Starting position:

[0178] ;

[0179] Where, location M Indicates the flag M The starting position, The pixel value matrix representing the DOM data after geometric precision reduction is used to extract hidden information.

[0180] An embodiment of the present application provides an electronic device, which may include a processor and a memory, wherein the processor and the memory can communicate with each other; illustratively, the processor and the memory communicate with each other via a communication bus.

[0181] The processor executes the computer-executable instructions stored in the memory, so that the processor implements the solutions in the above embodiments. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0182] The communication bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. System buses can be categorized as address buses, data buses, and control buses. Transceivers facilitate communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) or non-volatile memory.

[0183] The electronic device provided in the embodiment of the present application may be the terminal device of the above embodiment.

[0184] The embodiment of the present application further provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a computer, the computer executes the technical solution of the method for joining edge portions of DOM data in the above embodiment.

[0185] An embodiment of the present application further provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, the technical solution of the method for joining edge portions of DOM data in the above embodiment can be implemented.

[0186] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or module, which can be electrical, mechanical or other forms.

[0187] Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of these modules may be selected to implement the solution of this embodiment based on actual needs.

[0188] In addition, the functional modules in the various embodiments of the present application may be integrated into a single processing unit, or each module may exist physically separately, or two or more modules may be integrated into a single unit. The above-mentioned modules may be implemented in the form of hardware or hardware plus software functional units.

[0189] The integrated modules implemented in the form of software function modules can be stored in a computer-readable storage medium. The software function modules stored in a storage medium include a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute some of the steps of the methods of various embodiments of the present application.

[0190] It should be understood that the processor described above may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0191] The memory may include a high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk.

[0192] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be divided into address buses, data buses, and control buses.

[0193] The storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0194] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a main control device.

[0195] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0196] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for joining edges of DOM data, characterized in that: The method comprises: Acquire the frame DOM data, use the frame length and frame width of the frame DOM data to precode the offset pixel information respectively, and precode the pixels whose edges are offset from the frame range into a precoding matrix; Vectorizing the pixel values ​​in the precoding matrix and converting them into a binary sequence, performing information hiding on the binary sequence starting from the identification bit to obtain a encrypted data set; Extracting a flag bit and an image size based on the encrypted data set, organizing precoding matrices for the upper, lower, left, and right edges using the flag bit and the image size, extracting hidden information starting from the flag bit, and extracting the hidden information using an inverse information hiding operation and filling the hidden information into the precoding matrix; The filled pre-coding matrix is ​​used to perform non-overlapping edge joining according to the spatial relationship between the image sheets, filling in the missing pixel information and obtaining the edge-joined data; The offset pixel information is pre-coded using the image sheet length and image sheet width of the DOM data, and pixels whose edges are offset from the image sheet range are pre-coded into a pre-coding matrix, including: Obtain the pixel widths that exceed the range in four directions of the map sheet during the geometric accuracy reduction process and the width of the range to be hidden; wherein the width of the range to be hidden is the maximum pixel width that deviates from the map sheet range in the upward, downward, left, and right directions during the geometric accuracy reduction process; Based on the pixel widths that exceed the range in four directions of the map during the geometric accuracy reduction process, the pixels that exceed the map range in the top, bottom, left, and right directions are sequentially encoded into a first matrix; wherein the first matrix includes encoding matrices for the top, bottom, left, and right regions; Determining a uniform size of a precoding matrix based on the width of the range to be hidden, the image length, and the image width, and filling the first matrix to obtain a plurality of precoding matrices; The size of the coding matrix of the upper, lower, left and right regions is expressed as: ； Where, H Indicates the length of the image. W Indicates the width of the image, max indicates the maximum value function, 、 、 、 Respectively represent the pixel widths that are out of range in the left, right, up, and down directions. Matrix left,c 、 Matrix right,c 、 Matrix top ,c and Matrix bottom,c They represent the left region coding matrix, the right region coding matrix, the upper region coding matrix, and the lower region coding matrix respectively; The uniform size of the precoding matrix is or , L is the width of the range to be hidden, and the first matrix is ​​filled using the following formula to obtain multiple precoding matrices: ； Where, represents the precoding matrix, represents the encoding matrix after filling, ( x , y ) represents the filled matrix Index position, represents the encoding matrix before padding, represents the precoding matrix The index position of the precoding matrix is ​​mapped as follows: Left edge: ; Right edge: ; Top edge: ; Bottom edge: ; in, x,y Represents each edge matrix after filling The matrix size is x, which represents the matrix width and y, which represents the matrix length.

2. The method for joining edge portions of DOM data according to claim 1, wherein: The binary sequence is subjected to information hiding starting from the identification bit to obtain a encrypted data set, including: generating hidden information based on the binary sequence; Determine the hidden information embedding area and the starting position of the identification bit according to the size of the DOM data; Based on the starting position of the identification bit, the hidden information is hidden in the frame DOM data in a set order to obtain a encrypted data set.

3. The method for joining edge portions of DOM data according to claim 2, wherein: The binary sequence includes hidden carrier pixel values as well as The binary sequence is used to generate hidden information, including: Get the hidden vector pixel value as well as Bit binary information to be hidden; Will The bit binary information to be hidden is converted into Base digits ; According to the following formula Base digits Hide to hide the carrier pixel value : ； Where, f Represents an intermediate value calculated by the above formula, indicating that the carrier pixel value will be hidden After adding the adjustment amount k, Modulo result, k Represents an adjustment amount, whose value is ,when When the hidden pixel value , using the hidden pixel value as the hidden information.

4. The method for joining edge portions of DOM data according to claim 2, wherein: According to the size of the DOM data, the hidden information embedding area is determined by the following formula: ； Where, Indicates the hidden information embedding area, Represents the pixel value matrix of DOM data after geometric precision reduction, i represents the matrix row index, j represents the matrix column index, , , H Indicates the length of the image. W Indicates the width of the image. Indicates the identification bit, which is the maximum value of all edge retraction widths in the DOM data of the frame; The identification bit is determined by the following formula M Starting position: ； Where, location M Indicates the flag bit M The starting position, The pixel value matrix representing the DOM data after geometric precision reduction is used to extract hidden information.

5. A device for joining DOM data based on the method according to any one of claims 1 to 4, characterized in that: The device comprises: The hidden information preprocessing module is configured to obtain the frame DOM data, precode the offset pixel information using the frame length and frame width of the frame DOM data, and precode the pixels whose edges are offset from the frame range into a precoding matrix; an edge information hiding module configured to vectorize the pixel values ​​in the pre-coding matrix and convert them into a binary sequence, and perform information hiding on the binary sequence starting from the identification bit to obtain a encrypted data set; an edge information extraction module configured to extract a marker and an image size based on the encrypted data set, organize precoding matrices for the upper, lower, left, and right edges using the marker and image size, extract hidden information starting from the marker, and extract the hidden information using an inverse information hiding operation and fill the precoding matrix with the hidden information; The image splicing module is configured to use the filled precoding matrix to perform non-overlapping splicing according to the spatial relationship between the image sheets, fill in the missing pixel information, and obtain the spliced ​​data.

6. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method for joining edge portions of DOM data according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method for joining edge portions of DOM data according to any one of claims 1 to 4 when executed by a processor.

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