CN116468737A - Rainfall information acquisition method and device - Google Patents
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Abstract
The application provides a rainfall information acquisition method and device, and relates to the technical field of meteorological data monitoring. The method comprises the following steps: acquiring a first rainfall pattern of a first area; dividing the first rainfall pattern by using a region growing algorithm according to the colors of all pixel points in the first rainfall pattern to obtain a second rainfall pattern; wherein different colors in the second rainfall pattern represent different rainfall; and obtaining rainfall information of the first area according to the second rainfall graph and the actual area corresponding to the unit pixel point. According to the method and the device, the first rainfall image is subjected to relevant treatment through the area growth algorithm, so that accurate rainfall information of the first area can be obtained, the manpower and material resources and the time cost can be saved, the problem that the rainfall information of partial areas which are difficult to monitor by remote sensing stations is blank is solved to a certain extent, and the follow-up flood forecasting and other works are facilitated.
Description
Technical Field
The application relates to the technical field of meteorological data monitoring, in particular to a rainfall information acquisition method and device.
Background
In meteorological data, precipitation information is an important parameter reflecting the surface environmental condition and global water circulation, and is also an important index for representing climate change. Extreme weather and climatic events (floods, drought, etc.) caused by precipitation anomalies cause great harm to human production and life. Therefore, the method has great significance for the collection and analysis of meteorological data such as rainfall.
Disclosure of Invention
The present application aims to solve, at least to some extent, one of the technical problems in the related art.
To this end, a first aspect of the present application proposes a rainfall information acquisition method, including:
acquiring a first rainfall pattern of a first area;
dividing the first rainfall map by using a region growing algorithm according to the colors of all pixel points in the first rainfall map to obtain a second rainfall map; wherein different colors in the second rainfall pattern represent different rainfall;
and obtaining rainfall information of the first area according to the second rainfall graph and the actual area corresponding to the unit pixel point.
In some embodiments of the present application, the dividing the first rainfall map by a region growing algorithm according to the color of each pixel point in the first rainfall map to obtain a second rainfall map includes: according to the colors of all the pixel points in the first rainfall graph, determining a first pixel point in the first area as a seed point, wherein the first pixel point is a pixel point with a first color difference value smaller than a first threshold value with a designated color; wherein different ones of the specified colors represent different rainfall; obtaining a second color difference value between the color of the pixel point in the neighborhood range of the seed point and the designated color through a color difference formula; responsive to the second color difference value being less than a second threshold, generalizing pixels within the seed point neighborhood range to a growth region; obtaining a third color difference value between the color of the pixel point in the neighborhood of the growing area and the designated color, responding to the third color difference value being smaller than the second threshold value, inducing the pixel point in the neighborhood to the growing area so as to enlarge the growing area, and continuing to compare the color difference between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color until the color difference value between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color is larger than or equal to the second threshold value; dividing the enlarged growth area from the first rainfall pattern, and determining the growth area obtained after division as the second rainfall pattern.
In some embodiments of the present application, the rainfall information includes at least an average rainfall; the obtaining rainfall information of the first area according to the second rainfall map and the actual area corresponding to the unit pixel point includes: summing the rainfall in different rainfall areas according to the second rainfall map and the actual area corresponding to the unit pixel points to obtain a first value; and dividing the first numerical value by the actual area of the first area to obtain the average rainfall of the first area.
In some embodiments of the present application, the acquiring a first rainfall pattern of the first area includes: acquiring a third rainfall pattern of a second area, wherein the area range of the second area is larger than or equal to the area range of the first area; extracting an ROI region in the second region based on an ROI of interest extraction algorithm; and determining a rainfall pattern of the ROI area as a first rainfall pattern of the first area.
A second aspect of the present application proposes a rainfall information acquisition device, including:
the first acquisition module is used for acquiring a first rainfall pattern of the first area;
the second acquisition module is used for dividing the first rainfall graph through a region growing algorithm according to the colors of all pixel points in the first rainfall graph to obtain a second rainfall graph; wherein different colors in the second rainfall pattern represent different rainfall;
and the third acquisition module is used for acquiring the rainfall information of the first area according to the second rainfall graph and the actual area corresponding to the unit pixel point.
In some embodiments of the present application, the second obtaining module is specifically configured to: according to the colors of all the pixel points in the first rainfall graph, determining a first pixel point in the first area as a seed point, wherein the first pixel point is a pixel point with a first color difference value smaller than a first threshold value with a designated color; wherein different ones of the specified colors represent different rainfall; obtaining a second color difference value between the color of the pixel point in the neighborhood range of the seed point and the designated color through a color difference formula; responsive to the second color difference value being less than a second threshold, generalizing pixels within the seed point neighborhood range to a growth region; obtaining a third color difference value between the color of the pixel point in the neighborhood of the growing area and the designated color, responding to the third color difference value being smaller than the second threshold value, inducing the pixel point in the neighborhood to the growing area so as to enlarge the growing area, and continuing to compare the color difference between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color until the color difference value between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color is larger than or equal to the second threshold value; dividing the enlarged growth area from the first rainfall pattern, and determining the growth area obtained after division as the second rainfall pattern.
In some embodiments of the present application, the rainfall information includes at least an average rainfall; the third obtaining module is specifically configured to: summing the rainfall in different rainfall areas according to the second rainfall map and the actual area corresponding to the unit pixel points to obtain a first value; and dividing the first numerical value by the actual area of the first area to obtain the average rainfall of the first area.
In some embodiments of the present application, the first obtaining module is specifically configured to: acquiring a third rainfall pattern of a second area, wherein the area range of the second area is larger than or equal to the area range of the first area; extracting an ROI region in the second region based on an ROI of interest extraction algorithm; and determining a rainfall pattern of the ROI area as a first rainfall pattern of the first area.
A third aspect of the present application proposes an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the method according to the first aspect is implemented when the processor executes the program.
A fourth aspect of the present application proposes a computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to the first aspect.
According to the rainfall information acquisition method, the first rainfall image of the first area is acquired, the first rainfall image is subjected to related processing through the area growth algorithm, so that accurate rainfall information of the first area can be obtained, manpower and material resources and time cost can be saved, the problem that part of area rainfall information which is difficult to monitor by a remote sensing station is blank is solved to a certain extent, and follow-up flood forecasting and other works are facilitated.
Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.
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The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
fig. 1 is a flow chart of a rainfall information acquisition method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a rainfall radar chart of a first area according to an embodiment of the present application;
fig. 3 is a schematic diagram of dividing a first rainfall pattern by using a region growing algorithm provided in an embodiment of the present application to obtain a second rainfall pattern;
fig. 4 is a flow chart of another rainfall information obtaining method according to the embodiment of the present application;
FIG. 5 is a schematic diagram of extracting an ROI region in a rainfall radar chart of a second region based on an ROI extraction algorithm according to an embodiment of the present application;
fig. 6 is a schematic diagram of dividing a first rainfall pattern to obtain a second rainfall pattern according to the embodiment of the present application;
FIG. 7 is a schematic diagram of extracting an ROI region in a rainfall prediction graph of a second region based on an ROI extraction algorithm according to an embodiment of the present application;
fig. 8 is a schematic diagram of a first rainfall pattern divided to obtain a second rainfall pattern according to another embodiment of the present application;
fig. 9 is a schematic diagram of a rainfall information obtaining device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
The combination of weather and water conservancy is advanced, the field of weather water conservancy service is widened continuously, and the loss caused by extreme weather is reduced for society from the most basic weather forecast to the existing professional special service, disaster prevention and disaster reduction. In hydrological water regime forecasting work, precipitation data in a part of areas are mainly obtained by measurement by means of remote measuring stations. However, because the area of a partial area is wide, or because of the topography reason, the remote measuring stations are difficult to arrange, the monitoring of the area is difficult to fully cover, the incomplete monitoring can cause errors in the calculation of the total rainfall, and the follow-up flood forecast and other works are influenced.
Therefore, the application provides a rainfall information acquisition method and device. Specifically, a rainfall information acquisition method and device according to the embodiments of the present application are described below with reference to the accompanying drawings.
Fig. 1 is a flow chart of a rainfall information acquisition method according to an embodiment of the present application. As shown in fig. 1, the rainfall information acquisition method includes the steps of:
step 101, a first rainfall pattern of a first area is obtained.
Alternatively, in some embodiments of the present application, the first rainfall pattern may be a rainfall radar pattern of a grabbed weather department, and may also be a rainfall prediction pattern. Fig. 2 is a schematic diagram of a rainfall radar chart of a first area according to an embodiment of the present application. As shown in fig. 2, the rainfall radar map of the first area may be regarded as a first rainfall map of the first area.
Step 102, dividing the first rainfall pattern by using a region growing algorithm according to the colors of all pixel points in the first rainfall pattern, and obtaining a second rainfall pattern. Wherein different colors in the second rainfall pattern represent different rainfall amounts.
It should be noted that, the region growing algorithm can segment the connected regions with the same characteristics, and can provide good boundary information and segmentation results. The region growing algorithm may achieve better performance when no a priori knowledge is available.
As a possible implementation manner, the color of each pixel point in the first rainfall map (refer to fig. 2) may be compared with a preset specified color. Note that different specified colors represent different rainfall information, such as rainfall. And determining a first pixel point in the first area as a seed point, wherein the first pixel point is a pixel point with a first color difference value with the designated color smaller than a first threshold value. Wherein the first threshold may be a smaller threshold.
And obtaining a second color difference value between the color of the pixel point in the neighborhood range of the seed point and the designated color through a color difference formula. And if the second color difference value is smaller than the second threshold value, the pixel points in the neighborhood range of the seed point are summarized in the growing area. Wherein the second threshold may be greater than the first threshold. And continuously acquiring a third color difference value between the color of the pixel point in the neighborhood range of the growing area and the designated color, and if the third color difference value is smaller than a second threshold value, inducing the pixel point in the neighborhood range into the growing area to expand the growing area, and further continuously comparing the color difference between the color of the pixel point in the neighborhood range of the expanded growing area and the designated color until the color difference value between the color of the pixel point in the neighborhood range of the expanded growing area and the designated color is larger than or equal to the second threshold value. The enlarged growth region is divided from the first rainfall pattern, and the growth region obtained after division is determined as a second rainfall pattern (refer to fig. 3).
As one example, the neighborhood range may be designated as an 8-neighborhood.
In order to improve the accuracy of obtaining the second rainfall pattern, in some embodiments of the present application, the first color difference value, the second color difference value, and the third color difference value may be obtained by using a CIEDE2000 color difference formula. The CIEDE2000 is used as a color space uniformity correction function of brightness difference and hue difference, and the CIEDE2000 is used as a color difference calculation formula in the segmentation process, so that the segmentation accuracy can be improved, and the possibility that the segmentation generates holes or is overspecified due to noise or uneven gray scale is reduced.
And step 103, obtaining rainfall information of the first area according to the second rainfall map and the actual area corresponding to the unit pixel points.
Alternatively, the rainfall information may include key parameters in the subsequent rainfall forecast, such as total rainfall, average rainfall, etc. for the first zone. In some embodiments of the present application, after obtaining the rainfall information of the first area, the rainfall information may be used as a subsequent input parameter, and input into a hydrologic prediction model such as a SWAT to perform flood prediction.
In some embodiments of the present application, the rainfall information may include at least an average rainfall. Taking rainfall information as an example of average rainfall, the rainfall in different rainfall areas can be summed according to the second rainfall map and the actual area corresponding to the unit pixel points to obtain a first value. And dividing the first numerical value by the actual area of the first area to obtain the average rainfall of the first area. Reference may be made to the following formula:
wherein p is the average rainfall of the first region, sq p Is the actual area corresponding to the unit pixel point, i the number of pixel points corresponding to the area of the ith rainfall area, p i And n is the total number of pixel points of the first area, wherein the rainfall is the rainfall corresponding to the ith rainfall area in the second rainfall graph.
Note that, the actual area sq corresponding to the unit pixel point p Ratio of dpi of passable image and GIS mapThe rule is set, and the following formula can be referred to:
LS is the map scale of the first rainfall map, dpi is the number of pixel points in unit inch, and sq is the actual area of the first area.
According to the rainfall information acquisition method, the first rainfall image of the first area is acquired, the first rainfall image is subjected to related processing through the area growth algorithm, so that accurate rainfall information of the first area can be obtained, manpower and material resources and time cost can be saved, the problem that part of area rainfall information which is difficult to monitor by a remote sensing station is blank is solved to a certain extent, and follow-up flood forecasting and other works are facilitated.
In the collected rainfall map, the important attention is often paid to the rainfall condition in a specific drainage basin, rather than the total rainfall condition of each region in the rainfall map. And processing all areas in the rainfall graph, wherein the obtained rainfall information possibly comprises unnecessary data, and the processing time is increased. Fig. 4 is a flow chart of another rainfall information obtaining method according to the embodiment of the present application. As shown in fig. 4, the rainfall information acquisition method includes the steps of:
step 401, obtaining a third rainfall pattern of the second area, wherein the area range of the second area is greater than or equal to the area range of the first area.
The third rainfall pattern can be a rainfall radar pattern of a grabbed weather department and can also be a rainfall prediction pattern.
At step 402, an ROI region is extracted in the second region based on the ROI of interest extraction algorithm.
It should be noted that the ROI area may be an area set manually, for example, a specific drainage basin. As an example, as shown in fig. 5, ROI areas are extracted in the rainfall radar map of the second area based on the ROI of interest extraction algorithm, i.e., the ROI is used to delineate the areas of important interest.
Step 403, determining a rainfall pattern of the ROI area as a first rainfall pattern of the first area.
And step 404, dividing the first rainfall pattern by a region growing algorithm according to the colors of all pixel points in the first rainfall pattern to obtain a second rainfall pattern. Wherein different colors in the second rainfall pattern represent different rainfall amounts.
Fig. 6 is a schematic diagram of dividing a first rainfall pattern to obtain a second rainfall pattern according to an embodiment of the present application. As shown in fig. 6, the first rainfall pattern of the first region extracted from the third rainfall pattern of the second region is divided by a region growing algorithm, so as to obtain a second rainfall pattern.
As yet another example, taking a third rainfall pattern as an example of a rainfall prediction pattern, fig. 7 is a schematic diagram of extracting ROI areas in the rainfall prediction pattern of the second area based on the ROI extraction algorithm, and determining the rainfall pattern of the ROI areas as the first rainfall pattern of the first area. Fig. 8 is a schematic diagram of a first rainfall pattern divided to obtain a second rainfall pattern according to another embodiment of the present application.
And step 405, obtaining rainfall information of the first area according to the second rainfall map and the actual area corresponding to the unit pixel points.
It should be noted that, the method disclosed by the embodiment of the application can form a complete hydrological data after the analysis and recording of the picture data are accumulated, and has reference significance for the working research of the related aspects of future flood prediction.
In this embodiment of the present application, step 405 may be implemented in any manner in each embodiment of the present application, which is not specifically limited and will not be described herein.
According to the rainfall information acquisition method, the third rainfall image of the second region is acquired, the ROI region is extracted through the ROI extraction algorithm of interest, the important attention region is defined, and then the rainfall image of the ROI region is subjected to relevant processing through the region growing algorithm, so that accurate rainfall information of the ROI region (the first region) can be obtained, manpower and material resources can be further saved, the processing time is further shortened, the problem that the rainfall information of partial regions which are difficult to monitor by a remote sensing station is blank is solved to a certain extent, and the follow-up flood forecasting and other works are facilitated.
Fig. 9 is a schematic diagram of a rainfall information obtaining device according to an embodiment of the present application. As shown in fig. 9, the rainfall information acquisition device includes: a first acquisition module 901, a second acquisition module 902, and a third acquisition module 903. Wherein, the liquid crystal display device comprises a liquid crystal display device,
a first obtaining module 901, configured to obtain a first rainfall pattern of a first area;
the second obtaining module 902 is configured to segment the first rainfall pattern according to the color of each pixel point in the first rainfall pattern by using a region growing algorithm, so as to obtain a second rainfall pattern; wherein different colors in the second rainfall pattern represent different rainfall;
the third obtaining module 903 is configured to obtain rainfall information of the first area according to the second rainfall map and the actual area corresponding to the unit pixel point.
In some embodiments of the present application, the second obtaining module 902 is specifically configured to: according to the colors of all the pixel points in the first rainfall graph, determining a first pixel point in a first area as a seed point, wherein the first pixel point is a pixel point with a first color difference value smaller than a first threshold value with a designated color; wherein different specified colors represent different rainfall; obtaining a second color difference value between the color of the pixel point in the neighborhood range of the seed point and the designated color through a color difference formula; responsive to the second color difference value being less than a second threshold, generalizing pixels within the neighborhood of the seed point to the growth region; obtaining a third color difference value between the color of the pixel point in the neighborhood of the growing area and the designated color, inducing the pixel point in the neighborhood to the growing area to expand the growing area in response to the third color difference value being smaller than a second threshold value, and continuing to compare the color difference between the color of the pixel point in the neighborhood of the expanded growing area and the designated color until the color difference value between the color of the pixel point in the neighborhood of the expanded growing area and the designated color is larger than or equal to the second threshold value; dividing the enlarged growth area from the first rainfall pattern, and determining the growth area obtained after division as a second rainfall pattern.
In some embodiments of the present application, the rainfall information includes at least an average rainfall; the third obtaining module 903 is specifically configured to: summing the rainfall in different rainfall areas according to the second rainfall map and the actual area corresponding to the unit pixel points to obtain a first value; and dividing the first numerical value by the actual area of the first area to obtain the average rainfall of the first area.
In some embodiments of the present application, the first obtaining module 901 is specifically configured to: acquiring a third rainfall pattern of the second area, wherein the area range of the second area is larger than or equal to the area range of the first area; extracting an ROI region in the second region based on the ROI of interest extraction algorithm; a rainfall map of the ROI area is determined as a first rainfall map of the first area.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
According to the rainfall information acquisition device, through acquiring the first rainfall image of the first area, carrying out relevant treatment on the first rainfall image by combining an area growth algorithm, more accurate rainfall information of the first area can be obtained, manpower and material resources and time cost can be saved, the problem that part of area rainfall information which is difficult to monitor by a remote sensing station is blank is solved to a certain extent, and follow-up flood forecasting and other works are facilitated.
In order to achieve the above embodiments, the present application further proposes an electronic device including: a processor, and a memory for storing instructions executable by the processor. Wherein the instructions are executed by a processor to enable the processor to perform the aforementioned rainfall information acquisition method.
In order to implement the above-described embodiments, the present application also proposes a non-transitory computer-readable storage medium, which when executed by a processor of an electronic device, enables the electronic device to perform the aforementioned rainfall information acquisition method.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless explicitly defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (10)
1. The rainfall information acquisition method is characterized by comprising the following steps of:
acquiring a first rainfall pattern of a first area;
dividing the first rainfall map by using a region growing algorithm according to the colors of all pixel points in the first rainfall map to obtain a second rainfall map; wherein different colors in the second rainfall pattern represent different rainfall;
and obtaining rainfall information of the first area according to the second rainfall graph and the actual area corresponding to the unit pixel point.
2. The method according to claim 1, wherein the dividing the first rainfall map by a region growing algorithm according to the color of each pixel point in the first rainfall map to obtain a second rainfall map includes:
according to the colors of all the pixel points in the first rainfall graph, determining a first pixel point in the first area as a seed point, wherein the first pixel point is a pixel point with a first color difference value smaller than a first threshold value with a designated color; wherein different ones of the specified colors represent different rainfall;
obtaining a second color difference value between the color of the pixel point in the neighborhood range of the seed point and the designated color through a color difference formula;
responsive to the second color difference value being less than a second threshold, generalizing pixels within the seed point neighborhood range to a growth region;
obtaining a third color difference value between the color of the pixel point in the neighborhood of the growing area and the designated color, responding to the third color difference value being smaller than the second threshold value, inducing the pixel point in the neighborhood to the growing area so as to enlarge the growing area, and continuing to compare the color difference between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color until the color difference value between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color is larger than or equal to the second threshold value;
dividing the enlarged growth area from the first rainfall pattern, and determining the growth area obtained after division as the second rainfall pattern.
3. The method of claim 1, wherein the rainfall information includes at least an average rainfall; the obtaining rainfall information of the first area according to the second rainfall map and the actual area corresponding to the unit pixel point includes:
summing the rainfall in different rainfall areas according to the second rainfall map and the actual area corresponding to the unit pixel points to obtain a first value;
and dividing the first numerical value by the actual area of the first area to obtain the average rainfall of the first area.
4. The method of claim 1, wherein the obtaining a first rainfall pattern for the first area comprises:
acquiring a third rainfall pattern of a second area, wherein the area range of the second area is larger than or equal to the area range of the first area;
extracting an ROI region in the second region based on an ROI of interest extraction algorithm;
and determining a rainfall pattern of the ROI area as a first rainfall pattern of the first area.
5. A rainfall information acquisition device, characterized by comprising:
the first acquisition module is used for acquiring a first rainfall pattern of the first area;
the second acquisition module is used for dividing the first rainfall graph through a region growing algorithm according to the colors of all pixel points in the first rainfall graph to obtain a second rainfall graph; wherein different colors in the second rainfall pattern represent different rainfall;
and the third acquisition module is used for acquiring the rainfall information of the first area according to the second rainfall graph and the actual area corresponding to the unit pixel point.
6. The apparatus of claim 5, wherein the second acquisition module is specifically configured to:
according to the colors of all the pixel points in the first rainfall graph, determining a first pixel point in the first area as a seed point, wherein the first pixel point is a pixel point with a first color difference value smaller than a first threshold value with a designated color; wherein different ones of the specified colors represent different rainfall;
obtaining a second color difference value between the color of the pixel point in the neighborhood range of the seed point and the designated color through a color difference formula;
responsive to the second color difference value being less than a second threshold, generalizing pixels within the seed point neighborhood range to a growth region;
obtaining a third color difference value between the color of the pixel point in the neighborhood of the growing area and the designated color, responding to the third color difference value being smaller than the second threshold value, inducing the pixel point in the neighborhood to the growing area so as to enlarge the growing area, and continuing to compare the color difference between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color until the color difference value between the color of the pixel point in the neighborhood of the growing area after enlarging and the designated color is larger than or equal to the second threshold value;
dividing the enlarged growth area from the first rainfall pattern, and determining the growth area obtained after division as the second rainfall pattern.
7. The apparatus of claim 5, wherein the rainfall information comprises at least an average rainfall; the third obtaining module is specifically configured to:
summing the rainfall in different rainfall areas according to the second rainfall map and the actual area corresponding to the unit pixel points to obtain a first value;
and dividing the first numerical value by the actual area of the first area to obtain the average rainfall of the first area.
8. The apparatus of claim 5, wherein the first acquisition module is specifically configured to:
acquiring a third rainfall pattern of a second area, wherein the area range of the second area is larger than or equal to the area range of the first area;
extracting an ROI region in the second region based on an ROI of interest extraction algorithm;
and determining a rainfall pattern of the ROI area as a first rainfall pattern of the first area.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-4 when the program is executed by the processor.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-4.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109143413A (en) * | 2018-09-11 | 2019-01-04 | 深圳市银河系科技有限公司 | A kind of rainfall measuring method and device based on image recognition |
| CN110750516A (en) * | 2019-09-29 | 2020-02-04 | 浪潮软件集团有限公司 | Radar map-based rainfall analysis model construction method, construction system and analysis method |
| US10613252B1 (en) * | 2015-10-02 | 2020-04-07 | Board Of Trustees Of The University Of Alabama, For And On Behalf Of The University Of Alabama In Huntsville | Weather forecasting systems and methods |
| CN113269805A (en) * | 2021-06-11 | 2021-08-17 | 北京大学 | Remote sensing rainfall inversion training sample self-adaptive selection method guided by rainfall event |
| CN113343976A (en) * | 2021-05-13 | 2021-09-03 | 武汉大学 | Anti-highlight interference engineering measurement mark extraction method based on color-edge fusion feature growth |
-
2023
- 2023-04-10 CN CN202310375714.XA patent/CN116468737A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10613252B1 (en) * | 2015-10-02 | 2020-04-07 | Board Of Trustees Of The University Of Alabama, For And On Behalf Of The University Of Alabama In Huntsville | Weather forecasting systems and methods |
| CN109143413A (en) * | 2018-09-11 | 2019-01-04 | 深圳市银河系科技有限公司 | A kind of rainfall measuring method and device based on image recognition |
| CN110750516A (en) * | 2019-09-29 | 2020-02-04 | 浪潮软件集团有限公司 | Radar map-based rainfall analysis model construction method, construction system and analysis method |
| CN113343976A (en) * | 2021-05-13 | 2021-09-03 | 武汉大学 | Anti-highlight interference engineering measurement mark extraction method based on color-edge fusion feature growth |
| CN113269805A (en) * | 2021-06-11 | 2021-08-17 | 北京大学 | Remote sensing rainfall inversion training sample self-adaptive selection method guided by rainfall event |
Non-Patent Citations (3)
| Title |
|---|
| QIHANG LI ET AL.: "An image recognition method for the deformation area of open-pit rock slopes under variable rainfall", 《MEASUREMENT》, 2 December 2021 (2021-12-02), pages 1 - 17 * |
| 李璟汶 等: "岩质排土场边坡形变区域的自动识别与评估", 《江西冶金》, vol. 42, no. 4, 31 August 2022 (2022-08-31), pages 68 - 76 * |
| 谢习华 等: "基于 SLIC和改进区域生长的非结构化道路识别", 《计算机工程与应用》, vol. 58, no. 14, 31 December 2022 (2022-12-31), pages 210 - 218 * |
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