A method and system for smoothing contour lines and a computer-readable storage medium

Abstract

The present invention discloses a method, system and computer-readable storage medium for smoothing contour lines, the method comprising: obtaining grid data; the grid data comprising a plurality of node data; interpolating the grid data column by column and / or row by row through cubic convolution interpolation to obtain encrypted data; and performing contour line tracing on the encrypted data row by row or column by column to smooth the contour lines. The above method enables the contour lines after smoothing to satisfy the above-mentioned characteristics without the occurrence of contour line intersection.

Description

Technical Field

[0001] The present invention relates to the field of geophysical data processing, and in particular to a contour line smoothing method, system and computer-readable storage medium. Background Art

[0002] Contour lines are used to represent linear features with continuous distribution in space. They provide many conveniences for the identification of spatial data and can more intuitively grasp the spatial variation characteristics of data. They have been widely used in surveying and mapping, geology, hydrology, meteorology, geophysics and other fields. Common names include isotherms, isobars, contour lines, equipotential lines, etc. From the perspective of computer graphics, they have the following characteristics: 1) They are usually smooth continuous curves; 2) They generally do not intersect each other.

[0003] With the refinement of spatial data processing, the requirements for contour line drawing are getting higher and higher. In order to make the contour line more beautiful and present a more perfect data form while ensuring data accuracy. Most contour line tracking is based on grid data. It is connected according to the spatial characteristics of points, so that the formed graphics are expressed as broken lines in space, and they will appear spike-like locally. To make it more in line with the actual situation and more beautiful, contour line smoothing is an indispensable step. Commonly used contour line smoothing methods can be divided into two categories: line smoothing method and data smoothing method. Line smoothing method mainly fits the characteristic points of contour lines by selecting corresponding functions on the basis of existing contour lines, that is, it directly smoothes on the basis of existing contour lines. Commonly used functions include tension spline function, Bezier function, etc. Most of them solve the slope of the broken line segment based on adjacent points, and then construct polynomials for fitting, curve interpolation or tangent smoothing method to make the contour lines smoother. Although this method can smooth the contour lines, the contour lines may intersect during the processing. Therefore, it is more suitable for situations where the original data quality is high, the spatial distribution of contour lines is sparse, and the processing results are not strict enough. Figure 1A is the contour line of normal tracking, Figure 1B For smoothed contour lines, there are local intersections of contour lines. Although the parameters of the function can be adjusted to ensure local non-intersection, there will still be intersections for large-scale data, and the workload of data processing will increase. The data smoothing method mainly starts with the original data and processes the original data through filtering, such as mean filtering, median filtering and other methods, to make the original data smoother and flatter, and then track the contour lines. That is, contour line smoothing is achieved by smoothing the original data. Although this method can achieve the effect of data smoothing, it damages local details and affects the distribution of contour lines in space, thereby reducing the accuracy of subsequent data interpretation and processing. Therefore, it is more suitable for situations where the processing accuracy requirements are not high, that is, the original data is smoothed and then the contour lines are tracked. Figure 2A is the contour line of normal tracking, Figure 2B The contour lines are drawn after a mean filter. The contour lines are smoother overall. The more filtering times, the smoother the data will be. However, it can be seen that Figure 2B There is an obvious lack of an area in the image. This is because the filtering will flatten the area with large local gradient, which will lead to the missing contour lines.

[0004] Therefore, it is necessary to invent a new contour line smoothing method so that the smoothed contour lines can satisfy the above-mentioned characteristics without the occurrence of contour line missing.

[0005] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the invention

[0006] The object of the present invention is to provide a method, system and computer-readable storage medium for smoothing contour lines, which can ensure that the contour lines after smoothing satisfy the above-mentioned characteristics without the occurrence of contour line missing.

[0007] To achieve the above object, the present invention provides a method for smoothing contour lines, the method comprising:

[0008] Acquire grid data; the grid data includes a plurality of node data;

[0009] Performing column-by-column interpolation and / or row-by-row interpolation on the grid data by cubic convolution interpolation to obtain encrypted data;

[0010] Contour lines are traced on the encrypted data row by row or column by column to smooth the contour lines.

[0011] Preferably, the step of performing column-by-column interpolation and / or row-by-row interpolation on the grid data by cubic convolution interpolation to obtain the encrypted data comprises:

[0012] Obtaining the points to be interpolated row by row and / or column by column;

[0013] Obtaining node data in one or more directions of the neighborhood of the to-be-interpolated point;

[0014] Positioning the to-be-interpolated point according to the node data to determine the interpolation position;

[0015] The encrypted data is obtained; wherein the encrypted data is a collection of node data and points to be interpolated.

[0016] Preferably, calculating the to-be-interpolated point according to the node data comprises:

[0017]

[0018] Among them, h represents the sampling spacing of the points to be interpolated, x is the point to be interpolated, and x k represents the kth node data, u represents the convolution interpolation kernel, g is the interpolation function, c k is the parameter value that depends on the data of the kth node.

[0019] Preferably, the method further comprises:

[0020] Get edge threshold;

[0021] Determine whether the distance between the point to be interpolated and the node data of the field is greater than the edge threshold;

[0022] If so, the convolution interpolation kernel u is 0.

[0023] Preferably, the method further comprises:

[0024] The convolution interpolation kernel is located between (-2, 2), and the interpolation range s is divided into 4 parts (-2, -1), (-1, 0), (0, 1), (1, 2), then the function expression of the convolution interpolation kernel is:

[0025]

[0026] Preferably, the node data in one or more directions of the neighborhood of the point to be interpolated come from four directions of the point to be interpolated, wherein the angle between any two adjacent directions is the same.

[0027] Preferably, the point to be interpolated is affected by 16 node data in four directions.

[0028] In one embodiment of the present invention, a contour smoothing system is provided, the system comprising:

[0029] An acquisition unit, used for acquiring grid data; the grid data includes a plurality of node data;

[0030] An interpolation unit, used for performing column-by-column interpolation and / or row-by-row interpolation on the grid data through cubic convolution interpolation to obtain encrypted data;

[0031] The tracking unit is used to track the contour lines of the encrypted data row by row or column by column to smooth the contour lines.

[0032] Preferably, the interpolation unit further includes:

[0033] An interpolation point acquisition module is used to acquire the points to be interpolated row by row and / or column by column;

[0034] A pixel point acquisition unit is used to acquire node data in one or more directions of the neighborhood of the to-be-interpolated point;

[0035] A position acquisition unit, used for locating the to-be-interpolated point according to the node data to determine the interpolation position;

[0036] The encrypted data acquisition unit is used to acquire the encrypted data; wherein the encrypted data is a collection of node data and points to be interpolated.

[0037] In one embodiment of the present invention, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the contour line smoothing method as described in any one of the above items are implemented.

[0038] Compared with the prior art, the contour line smoothing method according to the present invention can make the contour lines after smoothing satisfy the above-mentioned characteristics without the occurrence of contour line missing. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1A and 1B They are comparative schematic diagrams before and after the application of the centerline smoothing method in the prior art;

[0040] Figure 2A and 2B They are respectively comparative schematic diagrams before and after the application of the data smoothing method in the prior art;

[0041] Figure 3 is a flow chart of a method for smoothing contour lines according to an embodiment of the present invention;

[0042] Figure 4 is a flow chart of a method for smoothing contour lines according to an embodiment of the present invention;

[0043] Figure 5 is a structural diagram of a contour smoothing system according to an embodiment of the present invention;

[0044] Figures 6A-6D They are respectively schematic diagrams after smoothing of a method for smoothing contour lines in one embodiment of the present invention;

[0045] Figure 7A-7B They are schematic diagrams after smoothing of a method for smoothing contour lines in one embodiment of the present invention. DETAILED DESCRIPTION

[0046] The specific implementation modes of the present invention are described in detail below in conjunction with the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific implementation modes.

[0047] Unless explicitly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising”, etc., will be understood to include the stated elements or components but not to exclude other elements or components.

[0048] like Figure 3 to Figure 4 As shown, according to a preferred embodiment of the present invention, a method for smoothing contour lines comprises:

[0049] Step 100, obtaining grid data; the grid data includes a plurality of node data. In the embodiment of the present invention, the original data is divided into a plurality of grids of the same size to form grid data, the grid data includes a plurality of node data, and these known pixel points are the pixel points corresponding to the contour lines in the original data.

[0050] Step 200, interpolate the grid data column by column and / or row by row through cubic convolution interpolation to obtain encrypted data. Specifically, the cubic convolution interpolation algorithm is a commonly used algorithm for image scaling and image distortion correction in high-end visualization software. In an embodiment of the present invention, the grid data is calculated through cubic convolution interpolation to obtain encrypted data. Specifically, the grid data can be interpolated column by column through cubic convolution interpolation to encrypt each column of the grid data pixel by pixel, or the grid data can be interpolated row by row to encrypt each row of the grid data pixel by pixel. In a preferred embodiment of the present invention, the grid data is encrypted column by column and then row by row through cubic convolution interpolation to obtain encrypted data. The specific encryption method is based on the actual situation required, and different encryption methods obtain different data densities.

[0051] Step 300, trace the contour lines of the encrypted data row by row or column by column to smooth the contour lines. Specifically, with the row by row or column by column contour line tracing algorithm as the core, the contour lines are obtained row by row or column by column based on the encrypted data, and the related characteristics of the contour lines are used to connect the contour lines of different rows, thereby completing the tracing and smoothing of the contour lines formed by the entire encrypted data.

[0052] In an embodiment of the present invention, grid data is used as a data source, and the grid data is interpolated and encrypted through cubic convolution interpolation to form encrypted data. The encrypted data is then processed row by row or column by column to obtain contour lines, and then the contour lines are tracked according to a row-by-row tracking algorithm to achieve the goal of smoothing the contour lines.

[0053] In a preferred embodiment, in step 200, interpolating the grid data column by column and / or row by row by cubic convolution interpolation to obtain encrypted data includes:

[0054] Step 201, obtaining the points to be interpolated row by row and / or column by column. Depending on the method of obtaining the encrypted data, the points to be interpolated are obtained row by row or column by column, or first column by column and then row by row.

[0055] Step 202, obtaining node data in one or more directions of the neighborhood of the point to be interpolated. Specifically, after obtaining the point to be interpolated, the specific position of the point to be interpolated is calculated according to the position of the node data in one or more directions of the neighborhood of the point to be interpolated.

[0056] Step 203, locate the point to be interpolated according to the node data to determine the interpolation position. In the embodiment of the present invention, the specific interpolation position of the point to be interpolated is affected by one or more node data. Generally, the more node data that affects the point to be interpolated, the more accurate the interpolation position obtained, so it can be determined according to the required accuracy and computing power. The accuracy of cubic convolution interpolation is between linear interpolation and cubic spline algorithm, but the interpolation algorithm is separable in two dimensions of the image and is more suitable for regularized grid data.

[0057] Step 204, obtaining the encrypted data; wherein the encrypted data is a set of node data and points to be interpolated. In a specific embodiment, after obtaining the interpolation position of the points to be interpolated based on the node data and performing interpolation, new grid data, i.e., a set of all points to be interpolated, is formed. Then, the original node data and the set of interpolated points to be interpolated are uniformly regarded as encrypted data, i.e., the encrypted data is the overall data obtained after performing interpolation operation on the grid data.

[0058] The method for smoothing contour lines described in the embodiment of the present invention preferably comprises: calculating the to-be-interpolated points according to the node data:

[0059]

[0060] Among them, h represents the sampling spacing of the points to be interpolated, x is the point to be interpolated, and x k represents the kth node data, u represents the convolution interpolation kernel, g is the interpolation function, c k is the parameter value that depends on the data of the kth node. Specifically, based on the above interpolation function, the specific position of each point to be interpolated can be calculated and interpolation can be performed at the specific position.

[0061] The contour line smoothing method described in the embodiment of the present invention is preferably, in the specific data processing process, for the boundary data, the data outside the range is calculated according to u=0 based on the interpolation algorithm. If it is false value data, it is also processed as u=0, thereby ensuring the integrity of the entire data processing.

[0062] In a specific embodiment, an edge threshold is obtained; the edge threshold represents the minimum value of the distance between a pixel point and an edge.

[0063] Determine whether the distance between the interpolation point and the node data of the field is greater than the edge threshold. When the distance between the interpolation point and the node data of the field is less than the edge threshold, that is, the interpolation point has exceeded the range where the edge is located, then the convolution interpolation kernel u is set to 0.

[0064] The method for smoothing contour lines described in the embodiment of the present invention preferably further comprises:

[0065] The convolution interpolation kernel is located between (-2, 2), and the interpolation range s is divided into 4 parts (-2, -1), (-1, 0), (0, 1), (1, 2), then the function expression of the convolution interpolation kernel is:

[0066]

[0067] Specifically, the convolution interpolation kernel obtained according to the above formula has symmetry.

[0068] In the contour smoothing method described in the embodiment of the present invention, preferably, the node data in one or more directions of the neighborhood of the to-be-interpolated point come from four directions of the to-be-interpolated point, wherein the angle between any two adjacent directions is the same. Specifically, the four directions are symmetrical.

[0069] In a specific embodiment of the present invention, the grid data is encrypted column by column and then row by row through cubic convolution interpolation to perform smoothing, combined with a row-by-row contour line tracking algorithm to improve the efficiency of the entire model operation. The entire model is as follows:

[0070] C i =[c i1 ,c i2 ,.....,c in ]

[0071] Let C i is the i-th row of data in the tracked grid data, then c i1 to c in is the column-by-column data of the i-th row, where n represents the number of columns of the grid data. The grid data is encrypted by z times by setting the interpolation coefficient z. Finally, the data rows and columns of the encrypted new grid composed of the interpolation points are:

[0072]

[0073] Assume the interpolation coefficient is z, m is the number of rows of the original grid data, n is the number of columns, then R is the number of rows of the encrypted new grid, C is the number of columns, and the relationship is shown in the following formula. The encryption algorithm calculates the row and column data based on the number of rows and columns. The final column data is:

[0074] C i =[ci1 ,c i2 ,.....,c i(n-1)z ]

[0075] Let C i is the i-th row of data after cubic convolution interpolation, and the entire set of encrypted data columns becomes from 1 to (n-1)*z.

[0076] From the 1st row to the (m-1)*zth row, encrypt each column of each row point by point. Assuming the interpolation coefficient z=2, it means that a point needs to be inserted between the corresponding spacing steps for each row and column. A point (i, j+1) needs to be inserted between the i-th row, j-th column and the i-th row, j+1-th column of the original grid data. At this time, the change of row coefficient is not considered. The value of this point is formed by cubic convolution interpolation, which is the 2j+1th value in the encrypted row data. The above interpolation steps can be cycled to obtain the entire row of data. The operation for other rows can be repeated in this way to form all the data of the entire new grid, and then the contour line tracking is realized according to the row-by-row tracking algorithm model to achieve the goal of contour line smoothing.

[0077] In the contour smoothing method described in the embodiment of the present invention, preferably, the interpolation point is affected by 16 node data in four directions. Specifically, in the embodiment of the present invention, not only the influence of the 4 node data closest to the interpolation point is considered, but also the influence of the pixel change rate in four directions is fully considered, so that the algorithm is more accurate.

[0078] The embodiment of the present invention also provides a contour line smoothing system, such as Figure 5 As shown, the system comprises:

[0079] The acquisition unit 500 is used to acquire grid data; the grid data includes a plurality of node data;

[0080] An interpolation unit 600, configured to perform column-by-column interpolation and / or row-by-row interpolation on the grid data by cubic convolution interpolation to obtain encrypted data;

[0081] The tracking unit 700 is used to track the contour lines of the encrypted data row by row or column by column to smooth the contour lines.

[0082] In the contour line smoothing system in the embodiment of the present invention, the interpolation unit further includes:

[0083] An interpolation point acquisition module is used to acquire the points to be interpolated row by row and / or column by column;

[0084] A pixel point acquisition unit is used to acquire node data in one or more directions of the neighborhood of the to-be-interpolated point;

[0085] A position acquisition unit, used for locating the to-be-interpolated point according to the node data to determine the interpolation position;

[0086] The encrypted data acquisition unit is used to acquire the encrypted data; wherein the encrypted data is a collection of node data and points to be interpolated.

[0087] An embodiment of the present invention further provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the steps of the contour line smoothing method described in any of the above specific embodiments are implemented.

[0088] In a specific embodiment of the present invention, plug-in technology is applied to realize the development of contour line cubic convolution smoothing function module based on GeoProbe platform. The entire function module uses VS2013 C# language for form design, the core algorithm is developed using C++ language, and the contour line data is stored in Shapefile file, which is finally integrated into the comprehensive geophysical data processing and interpretation system.

[0089] Specifically, the quality of the contour smoothing algorithm is mainly evaluated by its tracking efficiency and smoothing effect. The efficiency is mainly determined by the time required for the entire tracking, while the smoothing effect is based on the comparison with the original contour line. While ensuring data integrity, there is no data intersection after smoothing.

[0090] The measured grid data (1732 rows × 1049 columns) is used. The minimum value of the grid data is -513, the maximum value is 932, and the contour line tracking interval is 5, that is, the contour line tracking is performed every 5 from -510 to 930. The test is conducted on a laptop W520 (4GB memory, Win7 32-bit operating system). The tracking time and file size of the cubic convolution interpolation corresponding to different interpolation coefficients are shown in Table 1:

[0091] Table 1 Comparison of results of different interpolation coefficients

[0092]

[0093] The number of rows and columns to be processed after interpolation is different for different interpolation coefficients. The larger the interpolation coefficient, the longer the tracking time and the lower the efficiency. The file size also fully reflects the relationship between the interpolation coefficients. The larger the interpolation coefficient, the more points on the contour line.

[0094] Comparison Figure 2A The contour line tracking area, through the method described in the embodiment of the present invention, the graphics formed according to different interpolation coefficients are as follows Figures 6A-6D :

[0095] Using the cubic convolution interpolation smoothing method, when the interpolation coefficient is 2, the contour line in the lower left corner has a certain sharp corner. When the interpolation coefficient is 3, 5, and 8, the contour line is still relatively smooth when the figure has been scaled to a large scale. Of course, the larger the coefficient, the smoother it is, but the lower the processing efficiency. The data test results show that when the interpolation coefficient is 5, it can meet both efficiency and effect requirements.

[0096] Re-compare Figure 1A The contour line tracking area is set to 5 and 8 respectively, and the following is obtained by the method described in the present invention: Fig. 7A and 7B The results in the figure show that the result after applying the cubic convolution interpolation smoothing method fully meets the characteristics of the contour line.

[0097] As the basic map for spatial data processing, contour maps play an increasingly important role in all walks of life. Based on the analysis of traditional contour smoothing methods, the cubic convolution interpolation algorithm is applied, combined with the line-by-line contour tracking algorithm model, and the cubic convolution contour smoothing model is constructed. The contour smoothing design is completed, and the plug-in technology is applied. It is integrated based on the GeoProbe platform. The functional design is reasonable, and the smoothing efficiency and effect meet the design requirements. The actual measured data was used for testing. The test results show that the interpolation coefficient of 5 is the optimal value of the algorithm, which provides a reference for actual production.

[0098] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0099] The present application is described with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, and the combination of the process and / or box in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for realizing the function specified in one process or multiple processes in the flowchart and / or one box or multiple boxes in the block diagram.

[0100] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0102] The foregoing description of specific exemplary embodiments of the present invention is for the purpose of illustration and demonstration. These descriptions are not intended to limit the present invention to the precise form disclosed, and it is clear that many changes and variations can be made based on the above teachings. The purpose of selecting and describing the exemplary embodiments is to explain the specific principles of the present invention and its practical application, so that those skilled in the art can realize and utilize various different exemplary embodiments of the present invention and various different selections and changes. The scope of the present invention is intended to be limited by the claims and their equivalents.

Claims

1. A method for smoothing contour lines, characterized in that: The method comprises: Obtaining grid data; dividing the original data into a plurality of grids of the same size to form grid data, wherein the original data is geophysical data, and the grid data includes a plurality of node data; Performing column-by-column interpolation and / or row-by-row interpolation on the grid data by cubic convolution interpolation to obtain encrypted data; Performing contour tracing on the encrypted data row by row or column by column to smooth the contour lines; The step of performing column-by-column interpolation and / or row-by-row interpolation on the grid data by cubic convolution interpolation to obtain the encrypted data comprises: Obtaining the points to be interpolated row by row and / or column by column; Obtaining node data in one or more directions of the neighborhood of the to-be-interpolated point; Positioning the to-be-interpolated point according to the node data to determine the interpolation position; Acquire the encrypted data; wherein the encrypted data is a set of node data and points to be interpolated; Calculating the to-be-interpolated point according to the node data includes: Among them, h represents the sampling spacing of the point to be interpolated, x is the point to be interpolated, xk represents the kth node data, u represents the convolution interpolation kernel, g is the interpolation function, c k is the parameter value that depends on the kth node data; The method further comprises: Get edge threshold; Determine whether the distance between the point to be interpolated and the node data of the field is greater than the edge threshold; If so, the convolution interpolation kernel u is 0; The method further comprises: The convolution interpolation kernel is located between (-2, 2), and the interpolation range s is divided into 4 parts (-2, -1), (-1, 0), (0, 1), (1, 2), then the function expression of the convolution interpolation kernel is:

2. The method for smoothing contour lines according to claim 1, characterized in that: The node data in one or more directions of the neighborhood of the to-be-interpolated point come from four directions of the to-be-interpolated point, wherein the angles between any two adjacent directions are the same.

3. The method for smoothing contour lines according to claim 2, characterized in that: The point to be interpolated is affected by 16 node data in four directions.

4. A contour line smoothing system of the contour line smoothing method according to claim 1, characterized in that: The system comprises: An acquisition unit, used for acquiring grid data; the grid data includes a plurality of node data; An interpolation unit, used for performing column-by-column interpolation and / or row-by-row interpolation on the grid data through cubic convolution interpolation to obtain encrypted data; The tracking unit is used to track the contour lines of the encrypted data row by row or column by column to smooth the contour lines.

5. The contour line smoothing system according to claim 4, characterized in that: The interpolation unit further includes: An interpolation point acquisition module is used to acquire the points to be interpolated row by row and / or column by column; A pixel point acquisition unit is used to acquire node data in one or more directions of the neighborhood of the to-be-interpolated point; A position acquisition unit, used for locating the to-be-interpolated point according to the node data to determine the interpolation position; The encrypted data acquisition unit is used to acquire the encrypted data; wherein the encrypted data is a collection of node data and points to be interpolated.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the contour line smoothing method according to any one of claims 1 to 3 are implemented.

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