Image processing method, device and electronic equipment

Abstract

The embodiment of the present application provides an image processing method, device and electronic device, wherein the image processing method includes: performing image slicing processing on the initial image data; performing tile merging processing step by step based on the highest level tile set; for each pixel point in each low-level tile set, determining a target pixel point from the pixel matrix corresponding to the pixel point, and updating the height value of the target pixel point to the height value of the pixel point; wherein all the determined target pixel points are not the pixel points with the maximum height value at the same time. In this way, the initial image data can be sliced ​​into tile sets of different resolutions, and the height value of each pixel point in the low-level tile set is the height value of the target pixel point determined in the pixel matrix of the corresponding higher-level tile set, and all the determined target pixel points are not the pixel points with the maximum height value at the same time, so that the height values ​​of the pixel points of each level of tile set are evenly distributed, thereby improving the image rendering effect.

Description

Technical Field

[0001] The present application relates to the field of image data processing, and in particular to an image processing method, device and electronic equipment. Background Art

[0002] Image rendering in the prior art needs to rely on image cutting processing technology. For example, agricultural plant planting requires watering operations. The prior art can use the computer's graphics rendering capabilities to present the ups and downs of the land that needs watering, and use flooding rendering analysis to simulate the flooding effect of the land at different watering heights. The terrain tiles in the existing flooding rendering analysis technology are obtained by resampling the original digital surface model (DSM) data using maximum, average, nearest neighbor, minimum and other resampling algorithms. When performing flooding rendering analysis using resampling algorithms such as average, nearest neighbor, and minimum, the image may appear vague at different three-dimensional viewing angles or three-dimensional camera heights. The image slicing in the prior art has the problem of poor slicing effect. Summary of the invention

[0003] In order to solve the above technical problems, the embodiments of the present application provide an image processing method, device and electronic device.

[0004] In a first aspect, an embodiment of the present application provides an image processing method, the method comprising:

[0005] Performing image slicing processing on the initial image data to obtain a highest-level tile set with the highest resolution, wherein each pixel point of each tile in the highest-level tile set has a corresponding height value;

[0006] Based on the highest-level tile set, tile merging processing is performed level by level to obtain at least one low-level tile set with different resolutions, wherein different pixel points in the low-level tile set are formed by different pixel matrices in a relatively higher-level tile set;

[0007] For each pixel point in each low-level tile set, a target pixel point is determined from the pixel matrix corresponding to the pixel point, and the height value of the target pixel point is updated to the height value of the pixel point; wherein all the determined target pixel points are not simultaneously the pixel points with the maximum height value.

[0008] In a second aspect, an embodiment of the present application provides a method for generating a patrol mission, including:

[0009] Acquire a tile set of a target area; wherein the tile set is obtained based on the method according to any one of claims 1 to 9;

[0010] Determine a region of interest in the target area according to the tile set of the target area;

[0011] A patrol mission is generated according to the region of interest.

[0012] In a third aspect, an embodiment of the present application provides an image processing device, the device comprising:

[0013] A first processing module is used to perform image slicing processing on the initial image data to obtain a highest-level tile set with the highest resolution, wherein each pixel point of each tile in the highest-level tile set has a corresponding height value;

[0014] A second processing module is used to perform tile merging processing level by level based on the highest-level tile set to obtain at least one low-level tile set with different resolutions, wherein different pixel points in the low-level tile set are formed by different pixel matrices in a relatively higher-level tile set;

[0015] A determination module is used to determine a target pixel point from the pixel matrix corresponding to each pixel point in each low-level tile set, and update the height value of the target pixel point to the height value of the pixel point; wherein all the determined target pixel points are not the pixels with the maximum height value at the same time.

[0016] In a fourth aspect, an embodiment of the present application provides a device for generating a patrol mission, the device comprising:

[0017] An acquisition module, used to acquire a tile set of a target area; wherein the tile set is obtained based on the method described in the first aspect;

[0018] A determination module, configured to determine an area of ​​interest in the target area according to a tile set of the target area;

[0019] A generation module generates a patrol mission according to the area of ​​interest.

[0020] In a fifth aspect, an embodiment of the present disclosure provides a smart agriculture system, which includes the above-mentioned image processing device and / or a device for generating patrol missions.

[0021] In a sixth aspect, an embodiment of the present disclosure provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program runs on the processor, the computer program executes the image processing method provided in the first aspect, or executes the method for generating a patrol mission provided in the second aspect.

[0022] In the seventh aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run on a processor, it executes the image processing method provided in the first aspect, or executes the method for generating a patrol mission provided in the second aspect.

[0023] The image processing method provided by the present application is to perform a slice process on the initial image data to obtain the highest-level tile set with the highest resolution, and each pixel of each tile in the highest-level tile set has a corresponding height value; based on the highest-level tile set, tile merging is performed step by step to obtain at least one low-level tile set with different resolutions, wherein different pixels in the low-level tile set are formed by different pixel matrices in a relatively high-level tile set; for each pixel in each low-level tile set, a target pixel is determined from the pixel matrix corresponding to the pixel, and the height value of the target pixel is updated to the height value of the pixel; wherein all the determined target pixels are not pixels with the maximum height value at the same time. In this way, the initial image data can be sliced ​​into tile sets with different resolutions, and the height value of each pixel in the low-level tile set is the height value of the target pixel determined in the pixel matrix of the corresponding higher-level tile set, and all the determined target pixels are not pixels with the maximum height value at the same time, so that the height values ​​of the pixels in each level of tile set are evenly distributed, thereby improving the image rendering effect.

[0024] In addition, the method for generating a patrol mission provided by the present application above obtains a tile set of the target area; wherein the tile set is obtained based on the method described in the first aspect; the region of interest in the target area is determined based on the tile set of the target area; and the patrol mission is generated based on the region of interest. In this way, the region of interest in the target area is determined based on the tile set of the high target area, and the corresponding patrol mission is obtained based on the region of interest, thereby improving the effectiveness and accuracy of the patrol mission and better completing the patrol operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present application and should not be regarded as limiting the scope of protection of the present application. In each of the drawings, similar components are numbered similarly.

[0026] Figure 1 A schematic diagram of a process of an image processing method provided by an embodiment of the present application is shown;

[0027] Figure 2 A schematic diagram of a pixel matrix provided in an embodiment of the present application is shown;

[0028] Figure 3 A schematic diagram of a three-dimensional flood rendering provided by an embodiment of the present application is shown;

[0029] Figure 4 A schematic diagram of a process of generating a patrol mission provided by an embodiment of the present application is shown;

[0030] Figure 5 A schematic diagram of the structure of an image processing device provided in an embodiment of the present application is shown;

[0031] Figure 6 A structural schematic diagram of a device for generating a patrol mission provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0033] The components of the embodiments of the present application generally described and shown in the drawings herein may be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0034] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present application, are intended only to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing items or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations of the foregoing items.

[0035] Furthermore, the terms “first”, “second”, “third”, etc. are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0036] Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meanings as those generally understood by those skilled in the art to which the various embodiments of the present application belong. The terms (such as those defined in generally used dictionaries) will be interpreted as having the same meanings as the contextual meanings in the relevant technical field and will not be interpreted as having idealized meanings or overly formal meanings unless clearly defined in the various embodiments of the present application.

[0037] Example 1

[0038] An embodiment of the present disclosure provides an image processing method.

[0039] Specifically, Figure 1 As shown, the image processing method includes:

[0040] Step S101 , performing image slicing processing on the initial image data to obtain a highest-level tile set with the highest resolution, wherein each pixel point of each tile in the highest-level tile set has a corresponding height value.

[0041] In this embodiment, the initial image data may be image data acquired by a camera device carried by an unmanned device. For example, the initial image data may be a digital surface model (DSM), and the accuracy of DSM data is relatively high. DSM data is a raster map, and the raster map has many grids, and there are many pixels in the grids. The initial image data contains relatively rich content. For example, the initial image data may be obtained by photographing the terrain, or may be obtained by photographing crops, and there is no limitation here.

[0042] It is further explained that the highest level tile set includes multiple tiles, each tile includes multiple pixels, and each pixel has a corresponding height value.

[0043] There are many ways to perform image slicing on the initial image. In one embodiment, the maximum sampling algorithm is used to perform image slicing on the initial image data to obtain the highest-level tile set with the highest resolution. Specifically, Cesium's image slicing tool Cesium Terrain Build can be used to perform image slicing using the maximum sampling algorithm. The image slicing tool uses the maximum sampling algorithm to perform image slicing on the DSM data to obtain multiple tiles of the highest level, and the resolution of the highest-level tiles is the highest. For example, each tile of the highest level includes N×N pixels, and each pixel includes a corresponding height value. Among them, N can be taken as 65, and accordingly, the N×N height values ​​included in each tile of the highest level can be 65×65 height values.

[0044] In this way, it can be ensured that when the image is cut to obtain the maximum level tile set, the height value of each pixel is relatively accurate, thereby improving the accuracy of the height value of each pixel of the highest level tile set with the highest resolution.

[0045] Step S102, performing tile merging processing level by level based on the highest level tile set to obtain at least one low-level tile set with different resolutions, wherein different pixel points in the low-level tile set are formed by different pixel matrices in a relatively higher level tile set.

[0046] In this embodiment, a tile merging processing rule may be preset, and tile merging processing may be implemented based on the preset tile merging processing rule. Further, the preset tile merging processing rule may be a tile matrix for setting tile merging, and tile merging may be performed based on the tile matrix. When performing tile merging based on the tile matrix, multiple pixels may be fused into one pixel according to a pixel fusion technology, thereby completing the process of merging a tile matrix into one tile. For example, after averaging the pixel values ​​of four adjacent pixels, the average pixel value is used as the pixel value of the fused pixel of the four adjacent pixels.

[0047] In one embodiment, step S102 may include the following steps: for each low-level tile set, merging each tile array in the tile set of the previous level of the low-level tile set to form the low-level tile set.

[0048] For example, if the tile matrix is ​​a 2×2 tile matrix and the highest level tile set has 4×4 tiles, the highest level tile set is divided into 2×2 tile arrays to obtain 4 2×2 tile arrays, and each 2×2 tile array is merged to obtain a tile corresponding to the next level tile set.

[0049] If the highest level tile set is merged level by level to obtain 21 low level tile sets, the highest level tile set and the remaining low level tile sets are set to have 0 to 22 level tile sets in total, 22 is the highest level, and 0-21 are the remaining low level tile sets. Level 22 is the previous level of level 21, and level 21 is the previous level of level 20. The 22-level tile set is obtained by cutting the DSM data using the maximum sampling algorithm, and obtaining multiple tiles of the highest level. Assuming that the highest level tile set has 10,000 tiles, the 21-level has 10,000 / 4 tiles, that is, 2,500 tiles. Assuming that the tile range at level 22 is a rectangular area with a length and width of 1 meter (M), that is, the tile area is 1M×1M, then the 21-level tile set is obtained by merging the 2×2 tile arrays of each level 22, and the rectangular area corresponding to each tile is 2M×2M. If each tile at level 22 has 65×65 pixels, and each pixel has a corresponding height value, and the tiles at level 21 are obtained by merging the 2×2 tile arrays corresponding to level 22, then in order to obtain a tile set at level 21, the 65×65×2×2 pixels corresponding to the 2×2 tile array at level 22 can be divided into 65×65 2×2 pixel matrices, and the 4 pixels of each 2×2 pixel matrix are fused to obtain the pixel values ​​of the pixels of each tile at level 21 accordingly.

[0050] Level 21 is the previous level of level 20, and level 20 has 2500 / 4 tiles, that is, 625 tiles. Based on the tile set of level 21, a similar processing process from level 22 to level 21 is performed to obtain a tile set of level 20. You can also refer to the aforementioned processing process to obtain more low-level tile sets, which will not be repeated here.

[0051] It should also be noted that, although the above examples indicate that each level of tile set can be generated based on its upper level tile set, each level of tile set can also be generated based on other tile sets of higher level than its level. It can be understood that the higher level tile set mentioned above can be understood as any level of tile set higher than the level of the current tile set. For example, a relatively higher level tile set of the 18-level tile set can be any one of the 19-22-level tile sets. Selecting one of them to generate the 18-level tile set can also ensure the consistency of tile features at each level to a certain extent.

[0052] Since each level of tile set is generated based on a tile set of a higher level (including the previous level), the correlation between tile sets of different levels can be guaranteed. Compared with the related art in which multiple level tile sets are generated based on the initial image data, the consistency of tile features of each level can be guaranteed. Step S103: for each pixel point in each low-level tile set, a target pixel point is determined from the pixel matrix corresponding to the pixel point, and the height value of the pixel point is updated to the height value of the target pixel point; wherein all the determined target pixel points are not simultaneously the pixel points with the maximum height value.

[0053] In this embodiment, each pixel of each low-level tile set is determined by the pixel matrix corresponding to the higher-level tile set. The pixel of the higher-level tile set can be divided according to the pixel matrix of preset rows and columns to obtain multiple pixel matrices. Each pixel matrix of the higher-level tile set corresponds to each pixel of the lower-level tile set. Therefore, the pixel of the lower-level tile set can be determined accordingly according to each pixel matrix of the higher-level tile set. In addition, the height value of the pixel of the lower-level tile set needs to be set. Specifically, one of the height values ​​of each pixel of each pixel matrix of the higher-level tile set can be determined.

[0054] In one embodiment, in order to make the height values ​​of the pixels at the lower level distributed reasonably and evenly, the highest height value of each pixel matrix of the higher level tile set is not determined as the height of the pixel of the lower level tile set at the same time, wherein the following processing process can be used to implement the processing of the height of each pixel in the lower level tile set:

[0055] Numbering each pixel point in each pixel matrix; wherein different pixel points in the same pixel matrix have different numbers, the numbers of the pixel points in any two pixel matrices correspond one to one, and the numbers of the two pixel points with corresponding numbers are the same;

[0056] For each pixel point in each low-level tile set, a pixel point with a set number is determined as a target pixel point from a pixel matrix corresponding to the pixel point.

[0057] For example, see Figure 2 , Figure 2 The 2×2 pixel matrix shown includes 4 pixels, and the height values ​​of each pixel are respectively the first height value, the second height value, the third height value, and the fourth height value. The four pixels are numbered in a clockwise direction, and are numbered 1, 2, 3, and 4 respectively. The same numbering process is performed on other 2×2 pixel matrices. The set number can be any number in the number corresponding to the 2×2 height value, which can be understood as setting the number to any one of 1, 2, 3, and 4, for example, setting the number to 2. Based on this example, Figure 2 The pixel numbered 2 in the 2×2 pixel matrix shown is used as the target pixel. Similarly, the pixel numbered 2 in other 2×2 pixel matrices are used as the remaining target pixel points.

[0058] In this way, based on a large number of pixels, by setting the encoding to obtain the target pixel point, the height value of the target pixel point can be different from the pixel point with the highest height value in the pixel matrix at the same time, thereby ensuring that the height values ​​of the pixels in each tile set at a lower level can be reasonably distributed.

[0059] In other embodiments, the following processing may be used to process the height of each pixel in a lower-level tile set:

[0060] For each pixel point in each low-level tile set, a pixel point located in a set row and column is determined as a target pixel point from a pixel matrix corresponding to the pixel point.

[0061] For example, see again Figure 2 , instead of numbering the 2×2 pixel matrix, the pixels can be located by the number of rows and columns of the pixel matrix. For example, Figure 2 The pixel matrix shown and the pixel points in the first row and the first column in other pixel matrices are used as target pixel points.

[0062] In this way, the numbering process of the pixels in the pixel matrix can be reduced, and the corresponding target pixels can be directly selected, thus saving computing resources and improving processing efficiency.

[0063] In this embodiment, after obtaining the tile sets of each level, the following steps may be further included:

[0064] When receiving an instruction to display a target image, determining a zoom level of the target image according to the image zoom ratio corresponding to the instruction;

[0065] Determine a target tile set of a corresponding resolution level according to the zoom level;

[0066] Image rendering processing is performed based on the target tile set to obtain a three-dimensional rendering image of the target image.

[0067] In this embodiment, since the highest level tile set has the highest resolution and the lower level tile sets have lower resolutions, the corresponding relationship between the resolution and each level of tile sets can be obtained in advance, and the relationship between the zoom level and the resolution level can be pre-set, so that the target tile set can be determined from each level of tile sets based on the zoom level, and the rendering of the target tile set is completed to obtain the corresponding three-dimensional rendering. Since the initial image data contains different contents, the three-dimensional rendering rendered by the target tile set of the initial image data can also represent different meanings. The target image includes at least one of the following: a three-dimensional terrain rendering of the target area, a three-dimensional flooding rendering of the target area, and a three-dimensional plant growth rendering of the target area, but is not limited thereto.

[0068] Specifically, there may be different processing steps based on the above-mentioned various target images, which are described in detail below.

[0069] When the target image is a three-dimensional flood rendering of the target area, the method may further include the following steps:

[0070] Determining a water level change in the target area according to the irrigation amount and / or rainfall amount and / or soil infiltration rate of the target area;

[0071] Image rendering processing is performed based on the target tile set and the water level change to obtain a three-dimensional flood rendering image of the target area.

[0072] See also Figure 3 , Figure 3 The following is a 3D flood rendering obtained by using a cutting tool. The cutting tool may be a Cesium cutting tool. Figure 3 The three-dimensional flood rendering shown includes information such as high pier area 301, low-lying area 302, water surface 303 and ground plane 304, which can facilitate the location of high pier area and low-lying area in the target area.

[0073] In the above implementation, the water level change of the target area is determined by fully combining the irrigation amount and / or rainfall amount and / or soil infiltration rate of the target area, which is consistent with the actual situation and can improve the accuracy of the three-dimensional flood rendering of the target area.

[0074] The following is an example of the process of determining the water level change in the target area based on the irrigation volume, rainfall and soil infiltration rate of the target area: first, the water inflow of the target area can be determined based on the irrigation volume and rainfall of the target area, and then according to the water inflow, soil infiltration rate and terrain conditions of the target area, the location point can be used as a unit, or the target area can be divided into multiple sub-areas, and then the flooding situation of each location point or each sub-area can be determined in units of sub-areas. For example, the current water level height at each location point / each sub-area can be determined based on the water inflow and soil infiltration rate, and then based on the current water level height and the height of each location point / the average height of each sub-area, it can be determined whether each location point / each sub-area is in a flooded state or in a non-flooded state, and then a three-dimensional flooding rendering of the target area can be obtained, for example, Figure 3 shown.

[0075] It should be noted that some calculation methods involved in the above-mentioned flooding determination process can be known based on some technical principles related to physics, so this application will not go into details.

[0076] In order to improve data processing efficiency to a certain extent, in other embodiments, the three-dimensional flooding rendering of the target area can also be obtained by other methods, as follows:

[0077] Get the current flood height value of the target area;

[0078] Image rendering processing is performed based on the target tile set and the current flood height value to obtain a three-dimensional flood rendering image of the target area.

[0079] In the above implementation, there is no need to consider soil infiltration rate, irrigation amount, and rainfall amount. Instead, the three-dimensional flood rendering image of the target area can be directly acquired based on the obtained flood height value and the target tile set. For example, the area or position point in the target area that is lower than the flood height value can be displayed as being flooded, and the area or position point in the target area that is higher than the flood height value can be displayed as not being flooded; thereby greatly simplifying the amount of calculation and improving the calculation processing speed.

[0080] It should be noted that the water flooding height value can be directly input by the user or obtained through aerial survey images. In the scenario where the user inputs the water flooding height value, the water flooding height value input by the user can be expressed as the actual water flooding height in the target area, or it can be expressed as a value entered by the user according to his or her own needs when the user wants to understand the status of the target area under different degrees of water flooding, which is not necessarily the actual water flooding height.

[0081] In this embodiment, since the lower-level tile sets are generated based on the higher-level tile sets, the correlation between the tile sets at each level can be guaranteed. Compared with generating multiple levels of tile sets based on the initial image data, such as based on DSM data, this embodiment can ensure the consistency of tile features at each level, avoid the height values ​​of the remaining low-level tiles being the maximum height values ​​determined by the maximum value algorithm, and is more in line with the principle of large and small objects when the human eye actually views the scene, so that the characteristics of each pixel in each level of tile set correspond to its resolution level (which can also be understood as the zoom level), and all meet the principle of large and small objects when the human eye views the scene, thereby improving the effect of the final rendered image, and preventing some areas from being vague. For example, for a flood analysis scenario, after obtaining a low-level tile set with different resolutions, the height of the pixels in the low-level tile set is updated again so that the height value of each pixel is not the maximum height value in the corresponding pixel matrix at the same time. This ensures that the flood effect will not be vague. Since the resolution of the lower-level tile set is lower than that of the higher-level tile set, and the scaling ratio is larger than that of the higher-level tile set, it can be understood that when the target plot is displayed on a screen of the same size, the plot range displayed by the image displayed on the screen based on the lower-level tile set is , which is larger than the plot range displayed by the image displayed on the screen based on the higher-level tile set, can be understood as: the "distance" between the scenery displayed by the lower-level tile set and the user is farther, so by re-updating the height of the pixels in the low-level tile set after obtaining the low-level tile set, so that the height value of each pixel is not the maximum height value in the corresponding pixel matrix at the same time, some feature information that can only be seen at a close distance or is more obvious at a close distance can be blurred, so that the image generated based on the pixels in the lower-level tile set can be more in line with the criterion of far big and near small for human eyes.

[0082] In one embodiment, the terrain conditions of the target area can also be analyzed based on the obtained tile set of any level. For example, the high mounds and low-lying conditions of the target area can be analyzed. Based on this, the method can also include the following steps: obtaining the reference horizontal height value of the target area; determining the high mound area and low-lying area in the target area based on the reference horizontal height value and any level tile set. Among them, any level tile set can be selected, and the average height of each pixel point or each tile therein can be compared with the reference horizontal height value, and then the pixel points or tiles with a height higher than the reference horizontal height value are used as high mound areas, the pixel points or tiles with a height lower than the reference horizontal height value are used as low-lying areas, and the pixel points or tiles with a height equal to the reference horizontal height value are used as ground plane areas. In this way, the high mound area, low-lying area and ground plane area of ​​the target area can be obtained.

[0083] In the above, the reference horizontal height value of the target area may be obtained in a variety of ways, for example, it may be set by a user input, or it may be calculated based on the height value of the pixel point.

[0084] Specifically, obtaining the reference horizontal height value of the target area may include the following steps:

[0085] Determine a reference horizontal height value of the target area based on the initial image data or the height values ​​of all pixels in any level of tile set; or

[0086] The pre-input set level value is used as the reference level value of the target area.

[0087] For example, the median, average, or weighted average of the height values ​​of all pixels in the highest-level tile set can be taken as the reference horizontal height value, or the height values ​​of all pixels in the highest-level tile set can be clustered by a clustering algorithm, and then the height values ​​of a class with a larger cardinality can be selected as the reference horizontal height value. There are other ways, which are not limited here. Here, if you choose to determine the reference horizontal height value based on the pixels of the highest-level tile set, the obtained horizontal height value can have higher accuracy due to the large number of pixels; in addition, if you need to reduce the amount of calculation, you can use the pixels of a lower-level tile set to determine the reference horizontal height value as needed.

[0088] Example 2

[0089] In addition, an embodiment of the present disclosure provides a method for generating a patrol mission.

[0090] Specifically, Figure 4 As shown, the generation method of the patrol mission includes:

[0091] Step S401, obtaining a tile set of a target area; wherein the tile set is obtained based on the method described in any example in Embodiment 1.

[0092] In this embodiment, the tile set of the target area can be obtained in a variety of ways. The target area can be determined from the displayed image based on the touch instruction by receiving a user's touch instruction, and the corresponding tile set can be obtained based on the target area. It can be understood that the tile set can be pre-acquired by the method provided in Example 1 at each level, and then the tile sets at each level are stored. The corresponding tile set can be directly read based on the target area later. This method can improve the processing speed and save time. In another embodiment, the corresponding tile set can be generated for the target area by the image processing method provided in Example 1. This processing method can be used as a supplementary method for not pre-storing the corresponding tile set, and the corresponding tile set can be generated in real time to meet the use requirements.

[0093] Step S402: determining an area of ​​interest in the target area according to the tile set of the target area.

[0094] In this embodiment, the process of determining the region of interest in the target area can be determined by user selection to meet user customization requirements, or the region of interest can be determined based on the analysis results of the pixel points of the tile set of the target area. The region of interest is an area used for further application analysis and has a certain type of obvious characteristics. Different regions of interest can be set for different application analyses. For example, in the application of flooding analysis, the region of interest can be a high pier area or a low-lying area. In the application of plant growth analysis, the region of interest can be a plant planting area, etc., which is not limited here.

[0095] Specifically, step S402 may include the following steps:

[0096] According to the height values ​​of the pixels in the tile set of the target area and the reference horizontal height value, the high mound area and / or the low-lying area in the target area are determined, wherein the reference horizontal height value can be obtained based on the method mentioned in Example 1; or, a three-dimensional flooded rendering corresponding to the tile set of the target area is obtained by the method described in Example 1, and the three-dimensional flooded rendering is displayed; according to the touch information input by the user based on the three-dimensional flooded rendering, the high mound area and / or the low-lying area in the target area are determined;

[0097] The high pier area and / or low-lying area are taken as the area of ​​interest.

[0098] In the above implementation, to meet the user's customized needs, the user can determine the area of ​​interest that needs to be inspected from the high pier area and low-lying area of ​​the plot in the displayed three-dimensional flood rendering. To improve processing efficiency and timeliness, the system can also automatically determine the location information corresponding to the high pier area and the low-lying area based on the high pier area and low-lying area of ​​the plot in the three-dimensional flood rendering, and generate the area of ​​interest.

[0099] It should be noted that in the tillage and farming stage of agriculture, high areas and low-lying areas may be formed in the fields due to the failure of agricultural machinery to level the land. In the field irrigation management stage, it is necessary to conduct focused inspections at the locations of high areas and low-lying areas. Generate an area of ​​interest based on the high area information and / or low-lying area information of the three-dimensional flood rendering, collect image data for the area of ​​interest, and after obtaining the image data, you can view the growth of crops or the environment in which crops are located based on the image data, such as whether the crop growth is normal and whether weeds appear; you can also view whether the farmland tasks have been completed or the completion status based on the image data, for example, check whether water supply, water conservation, and drainage are in place.

[0100] Step S403: Generate a patrol mission according to the region of interest.

[0101] In this embodiment, after the region of interest is determined, the location information of the region of interest may be determined, and a patrol mission for arranging patrol operations may be generated based on the location information.

[0102] In order to improve the execution efficiency of the patrol mission, points of interest can be determined in the area of ​​interest, and the corresponding patrol operation can be performed by hovering at the points of interest. In one embodiment, step S403 can also include the following steps:

[0103] determining at least one point of interest based on the region of interest;

[0104] generating a patrol mission according to the at least one point of interest;

[0105] Wherein, determining at least one point of interest according to the region of interest includes:

[0106] When the area of ​​the region of interest is less than or equal to the preset area, any position point in the region of interest is selected as the point of interest;

[0107] When the area of ​​the region of interest is larger than a preset area, the region of interest is divided into a plurality of first sub-regions whose areas are less than or equal to the preset area, and a position point in each first sub-region is randomly selected as a point of interest; or, it is determined whether there are other regions of interest in the target area that are within a preset range with the region of interest, and when there are other regions of interest, the point of interest is determined based on the region of interest and the other regions of interest.

[0108] In this embodiment, in order to capture complete image data of the area of ​​interest, it is necessary to determine the corresponding points of interest. In one embodiment, the number of points of interest can be one or more. When there are multiple points of interest, the multiple points of interest can be divided into groups of points of interest, and a patrol mission is generated based on the groups of points of interest. In another embodiment, patrol parameters are set for the points of interest, and a group of points of interest is generated based on the multiple points of interest, and the patrol mission is generated based on the groups of points of interest and the patrol parameters.

[0109] In this embodiment, the interest point grouping may include multiple interest points corresponding to multiple low-lying areas, and / or multiple interest points corresponding to multiple high pier areas. The interest point grouping can be understood as dividing all interest points within a preset range into one interest point group. The patrol parameters include position, altitude, pitch angle, heading angle, speed, etc., and the patrol attitude, altitude, speed, etc. of the drone can be controlled by the patrol parameters. The patrol mission is generated according to the interest point grouping and the patrol parameters, which can improve the patrol efficiency.

[0110] In this way, setting the patrol parameters for the points of interest makes it easier to control the patrol attitude and altitude of the drone, and helps the drone obtain clear image data when performing patrol missions. Generating patrol missions based on the groups of points of interest can save patrol time and improve patrol efficiency.

[0111] It should be noted that this embodiment may further include the following steps:

[0112] The patrol mission is sent to the drone, so that the drone generates a corresponding patrol route according to the patrol mission.

[0113] In this embodiment, a patrol mission can be sent to the drone according to a received user instruction, or after a patrol mission is generated, the drone is automatically sent to the drone. The drone automatically plans a route according to the location of the point of interest in the patrol mission, and hovers at the point of interest to take pictures. Before taking pictures, the shooting position, lens direction, drone height, pitch angle and heading angle can be adjusted to collect image data of the area of ​​interest.

[0114] It is further explained that this embodiment may also include the following steps:

[0115] Receiving image data collected by the drone;

[0116] Identify whether the image data contains preset abnormal information.

[0117] In this embodiment, the image data collected by the drone is received, and the image analysis capability of the AI ​​assistant is applied to identify whether there is an abnormality at the location, such as identifying whether there are weeds at the high mounds in the area of ​​interest through object detection. Image segmentation technology is used to identify whether there are missing seedlings or abnormal seedling colors in high mound areas and low-lying areas. It should be supplemented that the AI ​​assistant can be understood as a system-provided function that uses AI to implement image processing. This embodiment does not limit the form of expression of this function, as long as image processing can be achieved.

[0118] In this embodiment, the drone performs a patrol mission, collects image data, and sends the image data. The preset abnormal information may include abnormal information of the area of ​​interest identified by object detection. For example, when the area of ​​interest is a high mound area, it is identified whether there are weeds in the high mound area. For another example, when the area of ​​interest is a high mound area and a low-lying area, image segmentation is used to identify whether there are missing seedlings or abnormal seedling color in the high mound area and the low-lying area, so as to assist farmers in making relevant and accurate decisions quickly and maximize the utilization of resources such as manpower and material resources.

[0119] In this embodiment, the preset area can be determined according to the shooting range of the drone, and the preset area can be set to a value smaller than the shooting range of the drone. When the area of ​​the region of interest is less than or equal to the preset area, the drone's shooting range above the region of interest can cover the region of interest, and any point in the region of interest can be used as a point of interest. When the area of ​​the region of interest is larger than the preset area, several more points of interest can be set, and each point of interest is responsible for patrolling the corresponding shooting area. Specifically, when the area of ​​the region of interest is larger than the preset area, the region of interest can be divided into multiple first sub-areas, and the area of ​​the first sub-area is less than or equal to the preset area. Since the first sub-area satisfies the smaller area, when any position point is taken as a point of interest, a relatively comprehensive image can be captured, and any position point in the first sub-area can be taken as a point of interest. In a preferred manner, the center point of the first sub-area can be used as a point of interest.

[0120] In this embodiment, if the region of interest is far away from other regions of interest, or the area of ​​other regions of interest is large, after the region of interest is fused and corrected with the other regions of interest, the points of interest determined based on the corrected regions of interest will not reduce the inspection workload. In these cases, the fusion correction process of the region of interest and the other regions of interest is not performed. If the region of interest is close to other regions of interest, or the area of ​​other regions of interest is small, after the region of interest is fused and corrected with the other regions of interest, the points of interest determined based on the corrected regions of interest can effectively reduce the inspection workload. In these cases, the fusion correction process of the region of interest and the other regions of interest can be performed.

[0121] In this embodiment, determining a point of interest according to the region of interest and the other regions of interest includes:

[0122] When the area of ​​the other regions of interest is smaller than the preset area, generating a revised region of interest according to the region of interest and the other regions of interest;

[0123] The modified region of interest is divided into a plurality of second sub-regions whose areas are less than or equal to the preset area, and a position point is randomly selected in each second sub-region as a point of interest.

[0124] In this embodiment, the region of interest is divided into multiple smaller sub-regions, and any point in the sub-region is used as the point of interest, so that corresponding images of the sub-regions can be captured respectively, and the images corresponding to the sub-regions can be aggregated to obtain the image of the region of interest.

[0125] In this way, the number of patrol points can be reduced and the patrol efficiency can be improved to a certain extent.

[0126] It is further explained that, in another embodiment, the method may further include:

[0127] When the area of ​​the region of interest is larger than a preset area, taking the center point of the region of interest as the point of interest;

[0128] The drone patrol altitude corresponding to the point of interest is set so that the photographing range of the drone when it is at the drone patrol altitude can cover the area of ​​interest.

[0129] In this embodiment, when the area of ​​the region of interest is larger than the preset area, the effect of capturing a panoramic image of the region of interest can be achieved by adjusting the height of the drone.

[0130] The method for generating a patrol mission provided in this embodiment obtains a tile set of a target area; wherein the tile set is obtained based on the method described in Embodiment 1; a region of interest in the target area is determined based on the tile set of the target area; and a patrol mission is generated based on the region of interest. In this way, the region of interest in the target area is determined based on the tile set of the target area, and the corresponding patrol mission is obtained based on the region of interest, which can improve the accuracy of the patrol mission and better complete the patrol operation.

[0131] Example 3

[0132] In addition, an embodiment of the present disclosure provides an image processing device.

[0133] Specifically, Figure 5 As shown, the image processing device 500 includes:

[0134] The first processing module 501 is used to perform image slicing processing on the initial image data to obtain a highest-level tile set with the highest resolution, where each pixel point of each tile in the highest-level tile set has a corresponding height value;

[0135] A second processing module 502 is configured to perform tile merging processing level by level based on the highest level tile set to obtain at least one low-level tile set with different resolutions, wherein different pixel points in the low-level tile set are formed by different pixel matrices in a relatively higher level tile set;

[0136] The determination module 503 is used to determine a target pixel point from the pixel matrix corresponding to each pixel point in each low-level tile set, and update the height value of the target pixel point to the height value of the pixel point; wherein all the determined target pixel points are not the pixels with the maximum height value at the same time.

[0137] In one embodiment, the first processing module 501 is further configured to perform image cutting processing on the initial image data by using a maximum sampling algorithm.

[0138] In one embodiment, the image processing apparatus 500 further includes:

[0139] A module is set to number each pixel point in each pixel matrix; wherein different pixel points in the same pixel matrix have different numbers, the numbers of the pixel points in any two pixel matrices correspond one to one, and the numbers of the two pixel points with corresponding numbers are the same;

[0140] The determination module 503 is further configured to determine, for each pixel point in each low-level tile set, a pixel point with a set number from a pixel matrix corresponding to the pixel point as a target pixel point.

[0141] In one embodiment, the determination module 503 is further configured to determine, for each pixel point in each low-level tile set, a pixel point located in a set row and column from a pixel matrix corresponding to the pixel point as a target pixel point.

[0142] In one embodiment, the second processing module 502 is further configured to merge each tile array in a previous level tile set of each low-level tile set to form the low-level tile set.

[0143] In one embodiment, the image processing apparatus 500 further includes:

[0144] A third processing module is used to determine the zoom level of the target image according to the image zoom ratio corresponding to the instruction when receiving the instruction to display the target image;

[0145] Determine a target tile set of a corresponding resolution level according to the zoom level;

[0146] Image rendering processing is performed based on the target tile set to obtain a three-dimensional rendering image of the target image.

[0147] In one embodiment, the target image includes at least one of the following: a three-dimensional terrain rendering of the target area, a three-dimensional flood rendering of the target area, and a three-dimensional plant growth rendering of the target area;

[0148] The third processing module is further configured to determine the water level change of the target area according to the irrigation amount and / or rainfall amount and / or soil infiltration rate of the target area when the target image is a three-dimensional flood rendering of the target area;

[0149] Image rendering processing is performed based on the target tile set and the water level change to obtain a three-dimensional flood rendering image of the target area.

[0150] In one embodiment, the third processing module is further used to obtain a current flood height value of the target area when the target image is a three-dimensional flood rendering of the target area; and perform image rendering processing based on the target tile set and the flood height value to obtain a three-dimensional flood rendering of the target area.

[0151] In one embodiment, the third processing module can also be used to analyze the terrain of the target area. Accordingly, the third processing module can also be used to: obtain a reference horizontal height value of the target area; and determine high pier areas and low-lying areas in the target area based on the reference horizontal height value and any level of tile set.

[0152] In one embodiment, the manner in which the third processing module obtains the baseline horizontal height value of the target area may include: a first manner, determining the baseline horizontal height value of the target area based on the initial image data or the height values ​​of all pixels in any level of tile set; a second manner, using a pre-input set horizontal height value as the baseline horizontal height value of the target area.

[0153] It should be noted that the specific implementation steps of the image processing device of this embodiment can refer to the relevant description of the image processing method in the above-mentioned embodiment 1, and will not be repeated here.

[0154] Example 4

[0155] In addition, an embodiment of the present disclosure provides a device for generating a patrol mission.

[0156] Specifically, Figure 6 As shown, the generation device 600 of the patrol mission includes:

[0157] An acquisition module 601 is used to acquire a tile set of a target area; wherein the tile set is obtained based on the method described in Embodiment 1;

[0158] A determination module 602, configured to determine an area of ​​interest in the target area according to a tile set of the target area;

[0159] The generation module 603 is used to generate a patrol mission according to the area of ​​interest.

[0160] In this embodiment, the determination module 602 is further used to determine the high mound area and / or low-lying area in the target area according to the height value of the pixel point in the tile set of the target area and the reference horizontal height value, wherein the reference horizontal height value is obtained based on the method described in Example 1; or, obtain the three-dimensional flooded rendering corresponding to the tile set of the target area through the method described in Example 1, and display the three-dimensional flooded rendering; determine the high mound area and / or low-lying area in the target area according to the touch information input by the user based on the three-dimensional flooded rendering;

[0161] The high pier area and / or low-lying area are taken as the area of ​​interest.

[0162] In this embodiment, the generating module 603 is further configured to determine at least one point of interest according to the region of interest;

[0163] generating a patrol mission according to the at least one point of interest;

[0164] Wherein, determining at least one point of interest according to the region of interest includes:

[0165] When the area of ​​the region of interest is less than or equal to the preset area, any position point in the region of interest is selected as the point of interest;

[0166] When the area of ​​the region of interest is larger than a preset area, the region of interest is divided into a plurality of first sub-regions whose areas are less than or equal to the preset area, and a position point in each first sub-region is randomly selected as a point of interest; or, it is determined whether there are other regions of interest in the target area that are within a preset range with the region of interest, and when there are other regions of interest, the point of interest is determined based on the region of interest and the other regions of interest.

[0167] In this embodiment, the generation module 603 also generates a correction region of interest based on the region of interest and the other regions of interest when the area of ​​the other regions of interest is smaller than the preset area; divides the correction region of interest into a plurality of second sub-regions whose areas are smaller than or equal to the preset area, and selects any position point in each second sub-region as a point of interest.

[0168] It should be noted that the specific implementation steps of the device for generating the patrol mission of this embodiment can refer to the relevant description of the method for generating the patrol mission in the above-mentioned embodiment 2, and will not be repeated here.

[0169] Example 5

[0170] In addition, an embodiment of the present disclosure provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program runs on the processor, it executes the image processing method provided in any example of the above-mentioned method embodiment 1, and / or, executes the method for generating a patrol mission provided in any example of the above-mentioned embodiment 2.

[0171] It should be noted that the specific implementation steps of the electronic device of this embodiment can refer to the relevant description of the image processing method provided in the above method embodiment 1 and the method for generating the patrol mission in the above embodiment 2, and will not be repeated here.

[0172] Example 6

[0173] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run on a processor, it executes the image processing method provided in any example of the above method embodiment 1, and / or the method for generating a patrol mission provided in any example of the above embodiment 2.

[0174] In this embodiment, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0175] It should be noted that the specific implementation steps of the computer-readable storage medium of this embodiment can refer to the relevant description of the image processing method provided in the above method embodiment 1 and the method for generating the patrol mission in the above embodiment 2, and will not be repeated here.

[0176] Example 7

[0177] The present application also provides a smart agriculture system, which includes the image processing device provided in any example in Example 3 and / or the generation device for the patrol mission provided in any example in Example 4.

[0178] Among them, the smart agriculture system can be understood as a software product, which can include the program corresponding to the image processing method provided in any example of the above-mentioned Embodiment 1 and / or the program corresponding to the method for generating a patrol mission provided in any example of Embodiment 2 in the form of a software installation package. Therefore, by installing the software installation package of the smart agriculture system in an electronic device, the electronic device can be enabled to have the functions corresponding to the image processing method and / or the method for generating a patrol mission provided in this application.

[0179] Of course, the smart agriculture system can also be understood as a hardware product. It can be a platform equipped with smart agriculture management functions, or it can be a systematic product that includes the above platform, agricultural machinery and equipment, field sensors, irrigation systems, etc., and can also realize the functions corresponding to the image processing method and / or patrol mission generation method provided in this application.

[0180] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0181] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0182] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. An image processing method, characterized in that: include: Performing image slicing processing on the initial image data to obtain a highest-level tile set with the highest resolution, wherein each pixel point of each tile in the highest-level tile set has a corresponding height value; Based on the highest-level tile set, tile merging processing is performed level by level to obtain at least one low-level tile set with different resolutions, wherein different pixel points in the low-level tile set are formed by different pixel matrices in a relatively higher-level tile set; For each pixel point in each low-level tile set, determine a target pixel point from the pixel matrix corresponding to the pixel point, and update the height value of the pixel point to the height value of the target pixel point; wherein all the determined target pixel points are not simultaneously the pixel points with the maximum height value; Numbering each pixel point in each pixel matrix; wherein different pixel points in the same pixel matrix have different numbers, the numbers of the pixel points in any two pixel matrices correspond one to one, and the numbers of the two pixel points with corresponding numbers are the same; The step of determining, for each pixel point in each low-level tile set, a target pixel point from a pixel matrix corresponding to the pixel point comprises: For each pixel point in each low-level tile set, a pixel point with a set number is determined as a target pixel point from a pixel matrix corresponding to the pixel point.

2. The method according to claim 1, characterized in that The step of performing image cutting processing on the initial image data comprises: The initial image data is subjected to image cutting processing by adopting a maximum sampling algorithm.

3. The method according to claim 1, characterized in that The step of determining, for each pixel point in each low-level tile set, a target pixel point from a pixel matrix corresponding to the pixel point comprises: For each pixel point in each low-level tile set, a pixel point located in a set row and column is determined as a target pixel point from a pixel matrix corresponding to the pixel point.

4. The method according to any one of claims 1 to 3, characterized in that: The step of performing tile merging processing level by level based on the highest level tile set to obtain at least one low-level tile set with different resolutions includes: For each low-level tile set, each tile array in the tile set at the previous level of the low-level tile set is merged to form the low-level tile set.

5. The method according to any one of claims 1 to 3, characterized in that: Also includes: When receiving an instruction to display a target image, determining a zoom level of the target image according to the image zoom ratio corresponding to the instruction; Determine a target tile set of a corresponding resolution level according to the zoom level; Image rendering processing is performed based on the target tile set to obtain a three-dimensional rendering image of the target image.

6. The method according to claim 5, characterized in that The target image includes at least one of the following: a three-dimensional terrain rendering of the target area, a three-dimensional flood rendering of the target area, and a three-dimensional plant growth rendering of the target area; When the target image is a three-dimensional flood rendering of the target area, the method further includes: Determining a water level change in the target area according to the irrigation amount and / or rainfall amount and / or soil infiltration rate of the target area; The performing image rendering processing based on the target tile set to obtain a three-dimensional rendering of the target image includes: Image rendering processing is performed based on the target tile set and the water level change to obtain a three-dimensional flood rendering image of the target area.

7. The method according to claim 5, characterized in that The target image includes at least one of the following: a three-dimensional terrain rendering of the target area, a three-dimensional flood rendering of the target area, and a three-dimensional plant growth rendering of the target area; When the target image is a three-dimensional flood rendering of the target area, the method further includes: Obtaining the current flood height value of the target area; The performing image rendering processing based on the target tile set to obtain a three-dimensional rendering of the target image includes: Image rendering processing is performed based on the target tile set and the current flood height value to obtain a three-dimensional flood rendering image of the target area.

8. The method according to claim 6, characterized in that The method further comprises: Obtaining a reference horizontal height value of the target area; Based on the reference level value and any level tile set, a high pier area and a low-lying area in the target area are determined.

9. The method according to claim 8, characterized in that The step of obtaining a reference horizontal height value of the target area includes: Determine the reference horizontal height value of the target area based on the height values ​​of all pixels in the initial image data or any level of tile set; or The pre-input set level value is used as the reference level value of the target area.

10. A method for generating a patrol mission, characterized in that: include: Acquire a tile set of a target area; wherein the tile set is obtained based on the method according to any one of claims 1 to 9; Determine a region of interest in the target area according to the tile set of the target area; A patrol mission is generated according to the region of interest.

11. The method according to claim 10, characterized in that The determining the region of interest in the target area according to the tile set of the target area comprises: Determine the high mound area and / or low-lying area in the target area according to the height value of the pixel point in the tile set of the target area and the reference horizontal height value, wherein the reference horizontal height value is obtained based on the method of claim 9; or obtain the three-dimensional flooding rendering corresponding to the tile set of the target area by the method of any one of claims 5 to 7, and display the three-dimensional flooding rendering; determine the high mound area and / or low-lying area in the target area according to the touch information input by the user based on the three-dimensional flooding rendering; The high pier area and / or low-lying area are taken as the area of ​​interest.

12. The method according to claim 10, characterized in that Generating a patrol mission according to the area of ​​interest includes: determining at least one point of interest based on the region of interest; generating a patrol mission according to the at least one point of interest; Wherein, determining at least one point of interest according to the region of interest includes: When the area of ​​the region of interest is less than or equal to the preset area, any position point in the region of interest is selected as the point of interest; When the area of ​​the region of interest is larger than a preset area, the region of interest is divided into a plurality of first sub-regions whose areas are less than or equal to the preset area, and a position point in each first sub-region is randomly selected as a point of interest; or, it is determined whether there are other regions of interest in the target area that are within a preset range with the region of interest, and when there are other regions of interest, the point of interest is determined based on the region of interest and the other regions of interest.

13. The method according to claim 12, characterized in that The determining of the point of interest according to the region of interest and the other regions of interest includes: When the area of ​​the other regions of interest is smaller than the preset area, generating a revised region of interest according to the region of interest and the other regions of interest; The modified region of interest is divided into a plurality of second sub-regions whose areas are less than or equal to the preset area, and a position point is randomly selected in each second sub-region as a point of interest.

14. An image processing device, characterized in that: include: A first processing module is used to perform image slicing processing on the initial image data to obtain a highest-level tile set with the highest resolution, wherein each pixel point of each tile in the highest-level tile set has a corresponding height value; A second processing module is used to perform tile merging processing level by level based on the highest-level tile set to obtain at least one low-level tile set with different resolutions, wherein different pixel points in the low-level tile set are formed by different pixel matrices in a relatively higher-level tile set; A determination module, for determining a target pixel point from a pixel matrix corresponding to each pixel point in each low-level tile set, and updating the height value of the target pixel point to the height value of the pixel point; wherein all the determined target pixel points are not simultaneously the pixel points with the maximum height value; A setting module is used to number each pixel point in each pixel matrix; wherein different pixel points in the same pixel matrix have different numbers, the numbers of the pixel points in any two pixel matrices correspond one to one, and the numbers of the two pixel points with corresponding numbers are the same; The determination module is further configured to determine, for each pixel point in each low-level tile set, a pixel point with a set number from a pixel matrix corresponding to the pixel point as a target pixel point.

15. A device for generating a patrol mission, characterized in that: include: An acquisition module, used to acquire a tile set of a target area; wherein the tile set is obtained based on the method according to any one of claims 1 to 9; A determination module, configured to determine an area of ​​interest in the target area according to a tile set of the target area; A generation module is used to generate a patrol mission according to the area of ​​interest.

16. A smart agricultural system, characterized in that: It includes the image processing device described in claim 14 and / or the generation device of the patrol mission described in claim 15.

17. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program, and when the computer program is run by the processor, the computer program executes the image processing method described in any one of claims 1 to 9, and / or executes the method for generating a patrol mission described in any one of claims 10 to 13.

18. A computer-readable storage medium, characterized in that: It stores a computer program, which, when running on a processor, executes the image processing method described in any one of claims 1 to 9, and / or executes the method for generating a patrol mission described in any one of claims 10 to 13.

Images