CN117095134A - Three-dimensional marine environment data interpolation processing method - Google Patents
Three-dimensional marine environment data interpolation processing method Download PDFInfo
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Abstract
The application provides a three-dimensional marine environment data interpolation processing method, which comprises the steps of establishing a three-dimensional interpolation algorithm model, carrying out adjacent value taking on each direction of a position point of missing data, then carrying out weighted average on the data of the value taking in each direction, and calculating an average value to enable the data to be used as a data value, namely a center point, of the position point of the missing data, so as to realize a three-dimensional marine environment data rapid interpolation function; for the situation that partial data are missing in each direction of a central point, through a partial data missing spatial interpolation algorithm model, the position points of the missing data do not participate in calculation, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participation calculation position, so that the rapid interpolation function of three-dimensional marine environment data is realized.
Description
Technical Field
The application relates to the technical field of data processing, and provides a three-dimensional marine environment data interpolation processing method.
Background
The three-dimensional marine environment data, including temperature, salinity, density, depth, flow velocity and other data, has the characteristics of difficult acquisition, large acquisition area, large data volume and the like, and is easy to cause the problem of partial position or partial area data loss.
The traditional three-dimensional data interpolation is basically based on the same layer of plane data and adopts an adjacent interpolation algorithm to conduct data interpolation, the interpolation efficiency is low, the accuracy of the interpolation data is low, and the error between the interpolation data and actual data is large.
In contrast to the technique of publication CN115690193a, "a rasterization method for non-uniformly distributed chart depth information";
the depth information rasterization method of the patent CN115690193a aims at two-dimensional sea chart depth raster data, and adopts an original depth data rasterization algorithm, a blank row or blank column element processing algorithm and a respective blank element processing algorithm, wherein the used raster processing algorithms are all plane data interpolation processing methods so as to realize a data interpolation function of unevenly distributed sea chart depth information. The patent aims at three-dimensional marine environment data, adopts a three-dimensional interpolation model, not only can process three-dimensional raster data, but also can process two-dimensional raster data, and is different from the data source dimension of the patent CN115690193A in the interpolation mode and the algorithm;
the blank row or blank column element processing algorithm in patent CN115690193a traverses the grid by row, assigns the value to all blank values before the grid when traversing to the first non-blank value element of each row, assigns the value to all blank values after the grid when traversing to the last non-blank value element of each row, and interpolates the blank grid between the traversed two non-blank values according to the equal step length. Performing the same operation according to the column traversal, adding the obtained interpolation grids with the interpolation grids obtained according to the row traversal, and taking an average value; the three-dimensional grid data is traversed by establishing a rapid three-dimensional interpolation model, a rapid plane interpolation model and a high-precision and high-accuracy three-dimensional interpolation model, adjacent value taking is carried out on all directions (6 directions, 8 horizontal directions or 26 directions) of a position point of missing data according to different using scenes, then weighted average is carried out on the data of all the directions, and an average value is obtained to enable the data to be used as center point data of the interpolation model. The patent has essential difference with the principle of a blank row or blank column element processing algorithm in the patent CN 115690193A;
according to the individual blank element processing algorithm in the patent CN115690193A, according to the positions of the blank values, then taking depth average values close to 3, 5 or 8 grids to fill in the positions of the blank values, and finally obtaining a map_recovery grid, wherein the adjacent grid data do not consider the data weight influence of different directions and distances; the fast plane interpolation algorithm model of the patent considers the data weight influence of different directions and distances, sets different weights according to 8 directions around the position point of the missing data and different distances, finally performs weighted average, and simultaneously performs dynamic approach value according to the situation of the data around the position of the missing data through the fast plane interpolation model of the data missing. The rapid plane interpolation algorithm model of the patent has great differences from the adjacent value range of the individual blank element processing algorithm in the patent CN115690193A, and the calculation method and the interpolation mode have essential differences.
Compared with the technology of the open patent CN110956696B 'a submarine topography simulation method based on multi-scale chart data';
patent CN110956696B is directed to a submarine topography simulation, in which an interpolation algorithm (terrestrial DEM interpolation algorithm) is used instead of being directed to an interpolation algorithm, whereas the present patent is directed to a three-dimensional data interpolation algorithm, which is different from the application purpose of patent CN 110956696B;
the land DEM interpolation algorithm in the patent CN110956696B searches for a triangle in which the grid point is positioned for the grid point in the triangle, performs rapid screening through a coordinate range, uses a vector cross product to perform accurate judgment, and finally uses an inverse distance interpolation method to calculate the depth value of the point; for single lattice points outside the triangular net, searching discrete water depth points to the periphery with the size of lattice spacing, if the number of the found points is less than 3, searching with the spacing of 2 times, 3 times or more until the found points are met, finding out 3 points closest to the lattice points from the found points, constructing a plane equation, and performing extrapolation calculation of the lattice depth values. According to the method, a rapid three-dimensional interpolation model, a rapid plane interpolation model, a high-precision and high-accuracy three-dimensional interpolation model are built according to the use scene, three-dimensional raster data are traversed, adjacent value taking is carried out on all directions of position points of missing data, then weighted average is carried out on the data of the values of all directions, and the average value is obtained to enable the data to be used as central point data of the interpolation model. The land DEM interpolation algorithm principle and the calculation method in the patent and the patent CN110956696B are essentially different.
Disclosure of Invention
In order to solve the technical problems, the application provides a three-dimensional marine environment data interpolation processing method, which is used for carrying out data interpolation aiming at the problems of acquisition three-dimensional raster data boundary deletion and middle part data deletion and providing a three-dimensional data interpolation function with higher speed, higher precision and higher accuracy.
In order to achieve the above purpose, the technical scheme adopted by the application is as follows:
a three-dimensional marine environment data interpolation processing method comprises the following steps: firstly, establishing a three-dimensional interpolation algorithm model, carrying out adjacent value taking on all directions of position points of missing data, then carrying out weighted average on the data of the value taking in all directions, and calculating an average value to enable the data to be used as a data value, namely a central point, of the position points of the missing data, so as to realize a three-dimensional marine environment data rapid interpolation function; and under the condition that partial data are missing in each direction of the central point, the position points of the missing data do not participate in calculation through a partial data missing spatial interpolation algorithm model, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation positions, so that the rapid interpolation function of the three-dimensional marine environment data is realized.
As a preferable technical scheme of the application: the three-dimensional interpolation algorithm model comprises a rapid three-dimensional interpolation model, wherein 6 directions of up, down, left, right, front and back of the position point of the missing data are subjected to proximity value taking, then the 6 directions of data are summed to obtain an average value, and the average value is used as a data value at the position point of the missing data, namely a central point, so that the rapid three-dimensional interpolation function of the marine environment data is realized; and for the situation that missing part data exists in the upper direction, the lower direction, the left direction, the right direction, the front direction and the rear direction of the central point, the missing data position does not participate in calculation through a part data missing fast stereo interpolation model, and the data of other position points are weighted and averaged.
As a preferable technical scheme of the application: the rapid stereoscopic interpolation model calculates the position data of the central point, and the formula is as follows:
（1）；
wherein,x、y、zfor the position to be interpolated,for 6 data of up, down, left, right, front and back directions of the position point of the missing data, < >>For the data value after the interpolation,Tcalculating the total number of data for the participation of the fast spatial interpolation model,/->，/>，/>，i、jAnd (3) withkIt is not possible to simultaneously set the values to 0,i、jand (3) withkAny two of the two are required to be 0 at the same time,
expanding the formula (1), wherein the interpolation data of the center point of the fast stereo interpolation model is as follows:
(2)。
as a preferable technical scheme of the application: the rapid stereo interpolation model has the condition of missing part data in the upper, lower, left, right, front and back directions of a central point, the position data of the central point is calculated through the partial data missing rapid stereo interpolation model, the position of missing data does not participate in calculation, the data of the two positions (x+1, y, z) and (x, y, z-1) in the partial data missing rapid stereo interpolation model do not participate in calculation, the weighted average is carried out by the data of other position points,
expanding the formula (1), wherein the interpolation data of the center point of the partial data missing fast stereo interpolation model is as follows:
(3)。
as a preferable technical scheme of the application: the three-dimensional interpolation algorithm model comprises a 3x3 rapid plane interpolation model, 8 horizontal direction data around a missing position point are subjected to proximity value taking, weighted average is carried out on the data around the missing position point as a data value at the position point of the missing data, namely a center point, so that a three-dimensional marine environment data rapid interpolation function is realized, wherein 4 positive direction weights in the 3x3 rapid plane interpolation model are 2,4 diagonal direction weights are 1, and the total weight value is 12; and for the condition that 8 horizontal directions around the central point have missing part data, the position of missing data around the central point does not participate in calculation through a 3x3 rapid plane interpolation model of partial data missing, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation position.
As a preferable technical scheme of the application: the 3x3 rapid plane interpolation model calculates a center point position data formula as follows:
（4），
wherein,xand (3) withyFor the position to be interpolated,data surrounding the location point of missing data，For the data value after the interpolation,W i、j weights for each position of the 3x3 fast planar interpolation model,Wfor the weight sum of each position of the 3x3 fast planar interpolation model,/for>，/>，iAnd (3) withjIt is not possible to simultaneously equal to 0,
4 positive direction weights of the 3x3 rapid plane interpolation model are 2,4 diagonal direction weights of the 3x3 rapid plane interpolation model are 1, the total weight value is 12, the 3x3 rapid plane interpolation model is brought into the formula (4), the formula (4) is expanded, and the center point interpolation data of the 3x3 rapid plane interpolation model are:
(5)。
as a preferable technical scheme of the application: the 3x3 rapid plane interpolation model calculates the position data of the center point through the partial data missing 3x3 rapid plane interpolation model when the 8 horizontal directions around the center point are missing, the position data of the center point is not involved in calculation at the position of missing data around the center point of the partial data missing 3x3 rapid plane interpolation model, the data at the (x+1, y-1) and (x, y+1) positions in the model are not involved in calculation, the data of other position points are weighted and averaged, the total weighted value involved in calculation is 9, the total weighted value is dynamically calculated according to the position involved in calculation,
expanding the formula (4), wherein the interpolation data of the center point of the partial data missing 3x3 rapid plane interpolation model is as follows:
(6)。
as a preferable technical scheme of the application: the three-dimensional interpolation algorithm model comprises a 3x3x3 high-precision three-dimensional interpolation model, 26 direction data around the position point of the missing data are subjected to adjacent value taking, then the 26 direction data are weighted and averaged to serve as the data value at the position point of the missing data, namely a center point, so that the high-precision and high-precision interpolation function of the three-dimensional marine environment data is realized, wherein the weight of the position point nearest to the missing data in the 3x3x3 high-precision three-dimensional interpolation model is highest, the weight of the position point nearest to the missing data in the diagonal position is secondary, the weight of the position of a cube corner point is lowest, the weight of the position point nearest to the 6 position points nearest to the missing data in the 3x3x3 high-precision three-dimensional interpolation model is 3, the weight of the position of the 12 diagonal positions is 2, the weight of the position of the 8 cube corner points is 1, and the total weight value is 50; aiming at the condition that 26 direction data around the central point have missing part data, the position of missing data around the central point does not participate in calculation through a part data missing 3x3x3 high-precision stereo interpolation model, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation position.
As a preferable technical scheme of the application: calculating the position data of the center point according to a 3x3x3 high-precision stereo interpolation model, wherein the formula is as follows:
（7）；
wherein x, y and z are the positions to be interpolated,surrounding data for the location point of missing data, +.>For the data value after the interpolation,W i、j、k weights for each position of the 3x3x3 high precision spatial interpolation model,Wfor the sum of the weights of the positions of the 3x3x3 high-precision stereo interpolation model, +.>，/>，/>，i、 jAnd (3) withkIt is not possible to simultaneously set the values to 0,i、jand (3) withkAny two of the two are required to be 0 at the same time,
the weight of the 6 nearest position points of missing data in the 3x3x3 high-precision stereo interpolation model is 3, the weight of the 12 diagonal positions is 2, the weight of the 8 cube corner positions is 1, the total weight value is 50, the numerator of the formula (7) is unfolded,
the total weighting value of 8 weighting values of 1 in the 3x3x3 high-precision stereo interpolation model is as follows:
（8）；
the total weight value of 12 weights of 2 is:
（9）；
the total weight value of the 6 weights of 3 is:
（10）；
substituting the calculation results of the formulas (8), (9) and (10) into the formula (7), wherein the center point interpolation data are as follows:
（11）。
as a preferable technical scheme of the application: aiming at the condition that 26 direction data around a central point have missing part data, through a part data missing 3x3x3 high-precision stereo interpolation model, the position of missing data around the central point does not participate in calculation, in the part data missing 3x3x3 high-precision stereo interpolation model, data at three positions of (x, y+1, z+1), (x+1, y+1, z+1) and (x+1, y+1, z-1) do not participate in calculation, the data of other position points are weighted and averaged, the total weighted value of the data of other position points is 46 and recorded as W, the total weighted value is dynamically calculated according to the position of participation calculation, the numerator of a formula (7) is unfolded,
the total weighting value of 6 weighting values of 1 in the partial data missing 3x3x3 high-precision stereo interpolation model is as follows:
（12）；
the total weighting value of 11 weights of 2 is:
（13）；
the total weight value of the 6 weights of 3 is:
(14)；
substituting the calculation results of the formulas (12), (13) and (14) into the formula (7), wherein the center point interpolation data is as follows:
(15)。
compared with the prior art, the application has the beneficial effects that:
the three-dimensional marine environment data interpolation algorithm provided by the application is used for carrying out data interpolation aiming at the problems of acquisition of three-dimensional grid data boundary deficiency and middle part data deficiency, and providing a three-dimensional data interpolation function with higher speed, precision and accuracy.
Drawings
FIG. 1 is a schematic block diagram of the present application;
FIG. 2 is a model of the fast stereo interpolation of the present application;
FIG. 3 is a partial data loss fast stereo interpolation model of the present application;
FIG. 4 is a 3x3 fast planar interpolation model in accordance with the present application;
FIG. 5 is a partial data loss 3x3 fast planar interpolation model of the present application;
FIG. 6 is a 3x3x3 high precision and high accuracy spatial interpolation model of the present application;
FIG. 7 is a partial data loss 3x3x3 high precision and high accuracy spatial interpolation model of the present application;
FIG. 8 is the effect before interpolation of 20m marine environmental temperature data in this embodiment;
FIG. 9 is the effect of interpolation of 20m marine environmental temperature data using a fast stereo interpolation model in this embodiment;
FIG. 10 is the effect before interpolation of the 0m marine environmental temperature data in this embodiment;
FIG. 11 is the effect of interpolation of 0m marine environmental temperature data using a 3x3 fast planar interpolation model in this embodiment;
FIG. 12 is the pre-interpolation effect of 40m marine ambient temperature data in this embodiment;
fig. 13 shows the effect of interpolation of 40m marine environmental temperature data using a 3x3x3 high-precision and high-accuracy stereo interpolation model in this embodiment.
Description of the embodiments
The application is described in further detail below with reference to the attached drawings and detailed description:
the application provides a three-dimensional marine environment data interpolation processing method, a principle frame diagram of which is shown in figure 1, comprising the following steps: firstly, establishing a three-dimensional interpolation algorithm model, carrying out adjacent value taking on all directions of position points of missing data, then carrying out weighted average on the data of the value taking in all directions, and calculating an average value to enable the data to be used as a data value, namely a central point, of the position points of the missing data, so as to realize a three-dimensional marine environment data rapid interpolation function; and under the condition that partial data are missing in each direction of the central point, the position points of the missing data do not participate in calculation through a partial data missing spatial interpolation algorithm model, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation positions, so that the rapid interpolation function of the three-dimensional marine environment data is realized.
The three-dimensional interpolation algorithm models comprise three-dimensional interpolation algorithm models applied to different scenes, namely a rapid three-dimensional interpolation model requiring speed priority, a 3x3 rapid plane interpolation model requiring speed and precision, and a 3x3x3 high-precision and high-precision three-dimensional interpolation model requiring precision priority.
And through a rapid three-dimensional interpolation model, as shown in fig. 2, 6 directions of up, down, left, right, front and back of the position point of the missing data are subjected to proximity value taking, and then 6 directions of data are summed to obtain an average value as central point interpolation data, so that a three-dimensional data rapid interpolation function is realized.
Calculating a center point interpolation data value formula:
（1）；
wherein,x、y、zfor the position to be interpolated,for 6 data of up, down, left, right, front and back directions of the position point of the missing data, < >>For the data value after the interpolation,Tcalculating the total number of data for the participation of the fast spatial interpolation model,/->，/>，/>，i、jAnd (3) withkIt is not possible to simultaneously set the values to 0,i、jand (3) withkAny two need to be 0 at the same time.
Expanding the formula (1), wherein the interpolation data of the center point of the fast stereo interpolation model is as follows:
(2)。
for the situation that missing part data exists in the upper direction, the lower direction, the left direction, the right direction, the front direction and the rear direction of the central point, a partial data missing fast stereo interpolation model is used, as shown in fig. 3, the position of missing data does not participate in calculation, the data at the two positions (x+1, y, z) and (x, y, z-1) in the model does not participate in calculation, and the data at other positions are weighted and averaged.
Expanding the formula (1), wherein the interpolation data of the center point of the partial data missing fast stereo interpolation model is as follows:
(3)。
in the 3x3 fast planar interpolation model, as shown in fig. 4, 8 horizontal direction data around the missing position point are adjacent to each other to be valued, and weighted average is performed on the data around the missing position point to be used as the data value at the missing position. In the 3x3 fast plane interpolation model, 4 positive direction weights are 2,4 diagonal direction weights are 1, and the total weight value is 12, which is recorded asW。
Calculating a position point data value formula of missing data:
（4），
wherein,xand (3) withyFor the position to be interpolated,to miss data around the location point of the data,for the data value after the interpolation,W i、j weights for each position of the 3x3 fast planar interpolation model,Wfor the weight sum of each position of the 3x3 fast planar interpolation model,/for>，/>，iAnd (3) withjAnd cannot be equal to 0 at the same time.
4 positive direction weights of the 3x3 rapid plane interpolation model are 2,4 diagonal direction weights of the 3x3 rapid plane interpolation model are 1, the total weight value is 12, the 3x3 rapid plane interpolation model is brought into the formula (4), the formula (4) is expanded, and the center point interpolation data of the 3x3 rapid plane interpolation model are:
(5)。
for the situation that missing part data exists in 8 horizontal directions around a central point, a 3x3 rapid plane interpolation model with partial data missing is adopted, as shown in fig. 5, the position of missing data around the central point does not participate in calculation, data at the two positions (x+1, y-1) and (x, y+1) in the model do not participate in calculation, the data at other positions are weighted and averaged, the total weighted value of participation calculation is 9, and the total weighted value is dynamically calculated according to the participation calculation position.
Expanding the formula (5), wherein the interpolation data of the center point of the partial data missing 3x3 rapid plane interpolation model is as follows:
(6)。
in the 3x3x3 high-precision and high-precision stereo interpolation model, as shown in fig. 6, adjacent values are taken for 26 direction data around the missing position point, then the 26 direction data are weighted and averaged, the weight of the nearest position point in the model is higher, the weight of the diagonal position is secondary, and the weight of the cube corner point position is lowest. The weight of 6 nearest position points in the 3x3x3 high-precision and high-precision stereo interpolation model is 3, the weight of 12 diagonal positions is 2, the weight of 8 cube corner points is 1, the total weight value is 50, and the model is recorded asW。
Calculating a position point data value formula of missing data:
（7）；
wherein x, y and z are the positions to be interpolated,surrounding data for the location point of missing data, +.>For the data value after the interpolation,W i、j、k weights for each position of the 3x3x3 high precision spatial interpolation model,Wfor the sum of the weights of the positions of the 3x3x3 high-precision stereo interpolation model, +.>，/>，/>，i、jAnd (3) withkIt is not possible to simultaneously set the values to 0,i、jand (3) withkAny two need to be 0 at the same time.
And (3) expanding the formula (7) molecules by taking the weight of 6 nearest position point positions in the 3x3x3 high-precision and high-precision stereo interpolation model as 3, the weight of 12 diagonal positions as 2, the weight of 8 cube corner positions as 1 and the total weight value as 50.
The total weighting value of 8 weights 1 in the 3x3x3 high-precision and high-precision stereo interpolation model is as follows:
（8）；
the total weight value of 12 weights of 2 is:
（9）；
the total weight value of the 6 weights of 3 is:
（10）；
substituting the calculation results of the formulas (8), (9) and (10) into the formula (7), wherein the center point interpolation data are as follows:
（11）。
for the situation that 26 direction data around the central point have missing part data, a 3x3x3 high-precision and high-precision stereo interpolation model is used for missing part data, as shown in fig. 7, the position of missing data around the central point does not participate in calculation, data at three positions (x, y+1, z+1), (x+1, y+1, z+1) and (x+1, y+1, z-1) in the model do not participate in calculation, data at other positions are weighted and averaged, the total weighted value of data at other positions is 46 and recorded as W, the total weighted value is dynamically calculated according to the position of participation calculation, and the molecule of the formula (10) is developed.
The total weighting value of 6 weighting values of 1 in the partial data missing 3x3x3 high-precision and high-precision stereo interpolation model is as follows:
（12）；
the total weighting value of 11 weights of 2 is:
（13）；
the total weight value of the 6 weights of 3 is: the method comprises the steps of carrying out a first treatment on the surface of the
(14)；
Substituting the calculation results of the formulas (12), (13) and (14) into the formula (7), wherein the center point interpolation data is as follows:
(15)。
and respectively carrying out interpolation processing on the marine environment temperature data of 0m, 20m and 40m through the three stereo interpolation algorithm models, and rendering a marine environment temperature distribution map.
Fast spatial interpolation model: the display effect of the 20m marine environment temperature data is shown as in fig. 8, the upper, lower, left, right, front and back 6 directions of the position point of the missing data of the 20m marine environment temperature data are subjected to adjacent value taking through a rapid stereo interpolation model, and then the data in the 6 directions are summed and averaged to obtain the data of the position point of the missing data. The effect of interpolation of 20m marine ambient temperature data is shown in figure 9.
3x3 fast planar interpolation model: the display effect of the 0m marine environment temperature data is shown as in fig. 10, 8 horizontal direction data around the missing position point of the 0m marine environment temperature data are nearby valued through a 3x3 rapid plane interpolation model, and weighted average is carried out on the data around the missing position point to be used as the data value at the missing position. The effect of interpolation of the 0m marine ambient temperature data is shown in fig. 11.
3x3x3 high precision and high accuracy stereo interpolation model: the display effect of the 40m marine environment temperature data is as shown in fig. 12, 26 direction data around the missing position point of the 40m marine environment temperature data are subjected to proximity value taking through a 3x3x3 high-precision and high-precision stereo interpolation model, and then the 26 data are weighted and averaged to be used as the data value at the missing position. The effect of interpolation of the 0m marine ambient temperature data is shown in fig. 13.
According to the application, the data interpolation is carried out aiming at the problems of missing boundary and missing middle part data of the acquired three-dimensional raster data, and the three-dimensional data interpolation function with higher speed, higher precision and accuracy is provided.
The above description is only of the preferred embodiment of the present application, and is not intended to limit the present application in any other way, but is intended to cover any modifications or equivalent variations according to the technical spirit of the present application, which fall within the scope of the present application as defined by the appended claims.
Claims (10)
1. The three-dimensional marine environment data interpolation processing method is characterized by comprising the following steps of: firstly, establishing a three-dimensional interpolation algorithm model, carrying out adjacent value taking on all directions of position points of missing data, then carrying out weighted average on the data of the value taking in all directions, and calculating an average value to enable the data to be used as a data value, namely a central point, of the position points of the missing data, so as to realize a three-dimensional marine environment data rapid interpolation function; and under the condition that partial data are missing in each direction of the central point, the position points of the missing data do not participate in calculation through a partial data missing spatial interpolation algorithm model, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation positions, so that the rapid interpolation function of the three-dimensional marine environment data is realized.
2. The method for processing the three-dimensional marine environment data interpolation according to claim 1, wherein the stereo interpolation algorithm model comprises a rapid stereo interpolation model, wherein 6 directions of up, down, left, right, front and back of a position point of missing data are subjected to adjacent value taking, and then 6 directions of data are summed to obtain an average value, and the average value is taken as a data value at the position point of the missing data, namely a central point, so that a rapid three-dimensional marine environment data interpolation function is realized; and for the situation that missing part data exists in the upper direction, the lower direction, the left direction, the right direction, the front direction and the rear direction of the central point, the missing data position does not participate in calculation through a part data missing fast stereo interpolation model, and the data of other position points are weighted and averaged.
3. The method for processing three-dimensional marine environment data interpolation according to claim 2, wherein the fast stereo interpolation model calculates the position data of the central point, and the formula is:
（1）；
wherein,x、y、zfor the position to be interpolated,for 6 data of up, down, left, right, front and back directions of the position point of the missing data, < >>For the data value after the interpolation,Tcalculating the total number of data for the participation of the fast spatial interpolation model,/->，/>，/>，i、jAnd (3) withkIt is not possible to simultaneously set the values to 0,i、jand (3) withkAny two of the two are required to be 0 at the same time,
expanding the formula (1), wherein the interpolation data of the center point of the fast stereo interpolation model is as follows:
(2)。
4. the method for processing the three-dimensional marine environment data interpolation according to claim 2, wherein the rapid stereoscopic interpolation model has the condition of missing part data in the upper, lower, left, right, front and rear directions of a central point, the position data of the central point is calculated through the partial data missing rapid stereoscopic interpolation model, the position of the missing data does not participate in calculation, the data at the two positions (x+1, y, z) and (x, y, z-1) in the partial data missing rapid stereoscopic interpolation model do not participate in calculation, the weighted average is carried out by the data of other position points,
expanding the formula (1), wherein the interpolation data of the center point of the partial data missing fast stereo interpolation model is as follows:
(3)。
5. the method for processing the three-dimensional marine environment data interpolation according to claim 1, wherein the three-dimensional interpolation algorithm model comprises a 3x3 rapid plane interpolation model, 8 horizontal direction data around a missing position point are subjected to adjacent value taking, weighted average is carried out on the data around the position point of the missing data, and the data is taken as a data value at the position point of the missing data, namely a center point, so that the three-dimensional marine environment data rapid interpolation function is realized, wherein 4 positive direction weights in the 3x3 rapid plane interpolation model are 2,4 diagonal direction weights are 1, and the total weight value is 12; and for the condition that 8 horizontal directions around the central point have missing part data, the position of missing data around the central point does not participate in calculation through a 3x3 rapid plane interpolation model of partial data missing, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation position.
6. The method for processing three-dimensional marine environment data interpolation according to claim 5, wherein the 3x3 fast planar interpolation model calculates a center point position data formula as follows:
（4），
wherein,xand (3) withyFor the position to be interpolated,surrounding data for the location point of missing data, +.>For the data value after the interpolation,W i、j weights for each position of the 3x3 fast planar interpolation model,Wfor the weight sum of each position of the 3x3 fast planar interpolation model,/for>，/>，iAnd (3) withjIt is not possible to simultaneously equal to 0,
4 positive direction weights of the 3x3 rapid plane interpolation model are 2,4 diagonal direction weights of the 3x3 rapid plane interpolation model are 1, the total weight value is 12, the 3x3 rapid plane interpolation model is brought into the formula (4), the formula (4) is expanded, and the center point interpolation data of the 3x3 rapid plane interpolation model are:
(5)。
7. the method according to claim 5, wherein the 3x3 fast planar interpolation model has missing part data in 8 horizontal directions around the center point, the center point position data is calculated by the partial data missing 3x3 fast planar interpolation model, the missing data positions around the center point of the partial data missing 3x3 fast planar interpolation model do not participate in calculation, the data at the two positions (x+1, y-1) and (x, y+1) in the model do not participate in calculation, the weighted average of the data at other positions is performed, the total weighted value of participation calculation is 9, the total weighted value is dynamically calculated according to the participation calculation position,
expanding the formula (4), wherein the interpolation data of the center point of the partial data missing 3x3 rapid plane interpolation model is as follows:
(6)。
8. the method for processing the three-dimensional marine environment data interpolation according to claim 1, wherein the stereo interpolation algorithm model comprises a 3x3x3 high-precision stereo interpolation model, 26 direction data around the position point of the missing data are subjected to adjacent value, then the 26 direction data are weighted and averaged to serve as the data value at the position point of the missing data, namely a center point, so that the high-precision and high-precision interpolation function of the three-dimensional marine environment data is realized, wherein the weight at the position point nearest to the missing data in the 3x3x3 high-precision stereo interpolation model is highest, the weight at the diagonal position is secondary, the weight at the position of the cube corner point is lowest, the weight at the position point nearest to the 6 position points of the missing data in the 3x3x3 high-precision stereo interpolation model is 3, the weight at the position of the 12 diagonal positions is 2, the weight at the position of the 8 cube corner point is 1, and the total weight value is 50; aiming at the condition that 26 direction data around the central point have missing part data, the position of missing data around the central point does not participate in calculation through a part data missing 3x3x3 high-precision stereo interpolation model, the data of other position points are weighted and averaged, and the total weighted value is dynamically calculated according to the participating calculation position.
9. The method for processing three-dimensional marine environment data interpolation according to claim 8, wherein the center point position data is calculated according to a 3x3x3 high-precision stereo interpolation model, and the formula is:
（7）；
wherein x, y and z are the positions to be interpolated,to miss data around the location point of the data,for the data value after the interpolation,W i、j、k weights for each position of the 3x3x3 high precision spatial interpolation model,Wfor the sum of the weights of the positions of the 3x3x3 high-precision stereo interpolation model, +.>，/>，，i、jAnd (3) withkIt is not possible to simultaneously set the values to 0,i、jand (3) withkAny two of the two are required to be 0 at the same time,
the weight of the 6 nearest position points of missing data in the 3x3x3 high-precision stereo interpolation model is 3, the weight of the 12 diagonal positions is 2, the weight of the 8 cube corner positions is 1, the total weight value is 50, the numerator of the formula (7) is unfolded,
the total weighting value of 8 weighting values of 1 in the 3x3x3 high-precision stereo interpolation model is as follows:
（8）；
the total weight value of 12 weights of 2 is:
（9）；
the total weight value of the 6 weights of 3 is:
（10）；
substituting the calculation results of the formulas (8), (9) and (10) into the formula (7), wherein the center point interpolation data are as follows:
（11）。
10. the method for processing the three-dimensional marine environment data interpolation according to claim 8, wherein the situation that 26 direction data around a central point has missing part data is characterized in that the position of missing data around the central point does not participate in calculation through a part data missing 3x3x3 high-precision stereo interpolation model, the position of missing data around the central point does not participate in calculation, the data of three positions (x, y+1, z+1), (x+1, y+1, z+1) and (x+1, y+1, z-1) in the part data missing 3x3x3 high-precision stereo interpolation model are not participated in calculation, the data of other position points are weighted and averaged, the total weighted value of the data of other position points is 46 and recorded as W, the total weighted value is dynamically calculated according to the participated calculation position, the formula (7) molecule is developed,
the total weighting value of 6 weighting values of 1 in the partial data missing 3x3x3 high-precision stereo interpolation model is as follows:
（12）；
the total weighting value of 11 weights of 2 is:
（13）；
the total weight value of the 6 weights of 3 is:
(14)；
substituting the calculation results of the formulas (12), (13) and (14) into the formula (7), wherein the center point interpolation data is as follows:
(15)。
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