CN113313099B

CN113313099B - Real-time acquisition method, system and storage medium based on remote sensing image map

Info

Publication number: CN113313099B
Application number: CN202110876682.2A
Authority: CN
Inventors: 温仕结; 蓝金桃
Original assignee: Guangdong Xingrui Technology Co ltd
Current assignee: Chengde Jintu Geographic Information Engineering Co.,Ltd.
Priority date: 2021-07-31
Filing date: 2021-07-31
Publication date: 2021-10-29
Anticipated expiration: 2041-07-31
Also published as: CN113313099A

Abstract

The invention provides a method, a system and a storage medium for acquiring a remote sensing image map in real time, wherein the method comprises the following steps: the remote sensor collects continuous frame remote sensing image maps in a preset area in real time and sends the maps to the data processing center in sequence; dividing the current frame remote sensing image map into a plurality of map areas according to a preset dividing mode by a data processing center; comparing each map area in the current frame remote sensing image map with the map areas at the same positions in the historical frame remote sensing image map one by one; screening out a map area with inconsistent comparison from the current frame remote sensing image map, taking the map area as an updated map area and sending the updated map area to a user terminal; and filtering out the non-updated map area from the historical frame remote sensing image map by the user terminal based on the updated map area, and then combining the non-updated map area with the received updated map area to restore the non-updated map area to the current frame remote sensing image map and display the current frame remote sensing image map. The method and the device can achieve the effect that the user terminal obtains the remote sensing image map in real time.

Description

Real-time acquisition method, system and storage medium based on remote sensing image map

Technical Field

The invention relates to the technical field of data processing, in particular to a method, a system and a storage medium for acquiring a remote sensing image map in real time.

Background

At present, some maps APP of a user terminal support viewing of remote sensing image maps, in the remote sensing image maps, map surface content elements are mainly composed of images, and a drawing object is expressed or explained by a certain map symbol in an auxiliary mode.

However, a frame of remote sensing image map is usually very large, a larger remote sensing image map is not favorable for fast network transmission, and further map APPs on user terminals are difficult to obtain a real-time remote sensing image map, because the information amount of a single frame of remote sensing image map is relatively large, if a data center transmits the remote sensing image map acquired by a remote sensor in real time, too many network resources are occupied, and further network transmission delay is caused, and the map APP of the user terminal is jammed, and many times, in order to avoid occupying too many network resources, the data center synchronizes the latest remote sensing image map to the map APPs of each user terminal according to a predetermined period, so that a user can see the remote sensing image map acquired before the remote sensing image map is possibly a certain period of time through the map APPs, and the real-time effect cannot be satisfied.

Disclosure of Invention

In order to solve at least one technical problem, the invention provides a method, a system and a storage medium for obtaining a remote sensing image map in real time, which can realize the effect of obtaining the remote sensing image map in real time by a map APP of a user terminal.

The invention provides a real-time acquisition method based on a remote sensing image map, which comprises the following steps:

the remote sensor collects continuous frame remote sensing image maps in a preset area in real time and sends the maps to the data processing center in sequence;

dividing the data processing center into a plurality of map areas according to a preset dividing mode based on the current frame remote sensing image map, wherein the preset dividing mode is predetermined by the data processing center and each user terminal;

comparing each map area in the current frame remote sensing image map with the map areas at the same positions in the historical frame remote sensing image map one by one;

screening out a map area with inconsistent comparison from the current frame remote sensing image map, taking the map area as an updated map area and sending the updated map area to a user terminal;

filtering out an un-updated map area from the historical frame remote sensing image map by the user terminal based on the updated map area, and then combining the un-updated map area with the received updated map area to restore the un-updated map area to the current frame remote sensing image map and display the current frame remote sensing image map;

continuously receiving a preset number of remote sensing image maps of a preset area by the data processing center;

determining the area range of change in the preset area by the data processing center according to the preset number of remote sensing image maps;

updating the segmentation mode based on the changed region range;

and synchronizing the updated segmentation mode to the user terminal, and enabling the data processing center to carry out remote sensing image map segmentation processing according to the updated segmentation mode.

In the scheme, each map area in the current frame remote sensing image map is compared with the map areas at the same position in the historical frame remote sensing image map one by one, and the method specifically comprises the following steps:

dividing the historical frame remote sensing image map into a plurality of map areas by the data processing center according to a preset dividing mode, respectively calculating the abstract value of the image data of each map area to obtain a corresponding first abstract value, and locally storing the first abstract value;

the data processing center respectively performs abstract calculation on a plurality of map areas obtained after the current frame remote sensing image map is segmented to obtain corresponding second abstract values;

comparing the second abstract value corresponding to each map area in the current frame remote sensing image map with the first abstract value corresponding to the map area at the same position in the historical frame remote sensing image map one by the data processing center;

if the second abstract value corresponding to a certain map area in the current frame remote sensing image map is consistent with the first abstract value corresponding to the map area at the same position in the historical frame remote sensing image map, judging that the map area in the current frame remote sensing image map is not updated relative to the map area at the same position in the historical frame remote sensing image map; and otherwise, judging that a certain map area in the current frame remote sensing image map is updated relative to a map area at the same position in the historical frame remote sensing image map.

In this scheme, after the current frame remote sensing image map is restored and displayed, the method further includes:

the data processing center and the user terminal synchronously cache related information of a preset number of historical remote sensing image maps, and the related information of each historical remote sensing image map comprises a plurality of map areas divided according to an updated dividing mode;

dividing a newly received frame of remote sensing image map into a plurality of map areas according to an updated dividing mode by the data processing center;

comparing a plurality of map areas of a newly received frame of remote sensing image map with a preset number of historical remote sensing image maps one by the data processing center;

when the map is compared with a certain historical remote sensing image map, the number of a plurality of map areas of a newly received frame of remote sensing image map is calculated to be consistent with the number of the map areas of the historical remote sensing image map;

traversing a preset number of historical remote sensing image maps, and selecting the consistent map with the maximum number as a target historical remote sensing image map;

comparing each map area in a newly received frame of remote sensing image map with map areas at the same position in a target historical frame of remote sensing image map one by one;

screening out a map area with inconsistent comparison from a newly received frame of remote sensing image map to serve as an updated map area of a new frame, and then sending the updated map area of the new frame and the frame number of the target historical frame of remote sensing image map to a user terminal;

and the user terminal determines a target historical frame remote sensing image map from a preset number of historical remote sensing image maps cached locally based on the frame number of the target historical frame remote sensing image map, filters an un-updated map area of a new frame from the target historical frame remote sensing image map based on an updated map area of the new frame, and combines the un-updated map area of the new frame with the updated map area of the received new frame to restore the newly received one-frame remote sensing image map and display the newly received one-frame remote sensing image map.

In this scheme, the data processing center divides the current frame remote sensing image map into a plurality of map regions according to a predetermined division mode, and specifically includes:

the data processing center is preset with a plurality of segmentation modes, and establishes a first association table of the plurality of segmentation modes and different network signal levels;

the data processing center evaluates the network signals of each accessed user terminal and determines the network signal level of each user terminal based on the network signals of each user terminal;

matching a corresponding segmentation mode from the first association table according to the determined network signal level;

synchronizing the matched segmentation modes to corresponding user terminals;

and the data processing center divides the current frame remote sensing image map into a plurality of map areas according to a synchronous division mode.

the data processing center is preset with a plurality of segmentation modes, and establishes a second association table of the plurality of segmentation modes and each administrative region;

the data processing center acquires a corresponding administrative region label based on the current frame remote sensing image map;

matching a corresponding segmentation mode in a second association table according to the acquired administrative region label;

synchronizing the administrative region labels and the matched segmentation modes to all accessed user terminals, and performing local association storage;

dividing a remote sensing image map of a certain administrative region into a plurality of map regions by the data processing center according to a synchronous dividing mode;

when a certain user terminal needs to check the remote sensing image map of a certain administrative area in real time, a segmentation mode associated with the administrative area is selected for processing.

The second aspect of the present invention further provides a real-time obtaining system based on a remote sensing image map, including at least one memory and at least one processor, where the memory stores a real-time obtaining method program based on a remote sensing image map, and when the real-time obtaining method program based on a remote sensing image map is executed by the at least one processor, the following steps are implemented:

updating the segmentation mode based on the changed region range;

In the scheme, after the current frame remote sensing image map is restored and displayed, when the program of the real-time acquisition method based on the remote sensing image map is executed by at least one processor, the following steps are also realized:

The third aspect of the present invention further provides a computer-readable storage medium, in which a remote sensing image map-based real-time obtaining method program is stored, and when the remote sensing image map-based real-time obtaining method program is executed by at least one processor, the steps of the remote sensing image map-based real-time obtaining method according to the first aspect are implemented.

The invention provides a method, a system and a storage medium for acquiring a remote sensing image map in real time, which can effectively solve the problem that a user terminal is difficult to acquire the remote sensing image map in real time, ensure real-time updating, reduce the probability of time delay and improve the transmission efficiency by reducing the data volume of transmission.

Additional aspects and advantages of the invention 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 invention.

Drawings

FIG. 1 is a flow chart of a method for real-time acquisition of a remote sensing image map according to the present invention;

FIG. 2 is a schematic diagram illustrating the update partitioning of the present invention;

fig. 3 shows a block diagram of a real-time acquisition system based on a remote sensing image map.

Detailed Description

In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.

Fig. 1 shows a flow chart of a real-time acquisition method based on a remote sensing image map according to the invention.

As shown in fig. 1, a first aspect of the present invention provides a method for obtaining a remote sensing image map in real time, where the method includes:

s102, collecting continuous frame remote sensing image maps in a preset area in real time by a remote sensor, and sequentially sending the maps to a data processing center;

s104, the data processing center divides the remote sensing image map into a plurality of map areas according to a preset division mode based on the current frame remote sensing image map, wherein the preset division mode is agreed by the data processing center and each user terminal in advance;

s106, comparing each map area in the current frame remote sensing image map with the map areas at the same positions in the historical frame remote sensing image map one by one;

s108, screening out a map area with inconsistent comparison from the current frame remote sensing image map, taking the map area as an updated map area and sending the updated map area to a user terminal;

and S110, filtering out an un-updated map area from the historical frame remote sensing image map by the user terminal based on the updated map area, and combining the un-updated map area with the received updated map area to restore the un-updated map area into the current frame remote sensing image map and display the current frame remote sensing image map.

It should be noted that, a map APP is installed on the user terminal, and in practical application, the data processing center synchronizes the remote sensing image maps of the continuous frames collected by the remote sensor in the preset area in real time to the map APP of the user terminal, so that the user can check the condition in the preset area in real time through the map APP. The remote sensors may be mounted on satellites or drones so that they detect the ground from high altitudes. The preset segmentation mode is appointed by the data processing center and the user terminal in advance, so that after the data processing center segments the remote sensing image map according to the preset segmentation mode, the user terminal can combine the segmented map regions together, and in the transmission process of the remote sensing image map, the data processing center only transmits a part of image data (namely, updates the map region), so that the data volume of network transmission is reduced, and the delay phenomenon is avoided.

It should be noted that the remote sensor collects the continuous frame remote sensing image maps according to the time sequence, and for the continuous frame remote sensing image maps, the current frame remote sensing image map is opposite to the historical frame remote sensing image map, the current frame remote sensing image map is the remote sensing image map which needs to be transmitted and processed currently, and the historical frame remote sensing image map is the remote sensing image map which is transmitted and processed before relative to the current frame remote sensing image map.

According to an embodiment of the present invention, the historical frame remote sensing image map is a previous frame remote sensing image map of the current frame remote sensing image map, but is not limited thereto.

According to the specific embodiment of the present invention, the data processing center is divided into a plurality of map areas according to a predetermined division manner based on the current frame remote sensing image map, and specifically includes:

the data processing center divides the current frame remote sensing image map into a plurality of map areas with the same size according to a criss-cross dividing mode, and attaches corresponding dividing labels to each map area.

It is to be understood that, in general, the remote sensing image map is rectangular, and each map region after being segmented may be square or rectangular, but is not limited thereto.

According to the specific embodiment of the present invention, the filtering, by the user terminal, an un-updated map area from the history frame remote sensing image map based on the updated map area specifically includes:

and filtering out the missing segmentation labels from the complete segmentation labels by the user terminal based on the received segmentation labels of the updated map area, and determining the non-updated map area from the historical frame remote sensing image map based on the missing segmentation labels.

According to the embodiment of the invention, each map area in the current frame remote sensing image map is compared with the map areas at the same position in the historical frame remote sensing image map one by one, and the method specifically comprises the following steps:

It should be noted that if the image data of the two map areas are directly compared, the calculation amount is large, which is not favorable for solving the problem of transmission delay. The invention respectively carries out abstract calculation on the image data of a plurality of divided map areas, and replaces the compared data with abstract values from the traditional image data, thereby greatly reducing the compared data volume and further improving the processing and transmission efficiency of the data.

According to the embodiment of the invention, after the current frame remote sensing image map is restored and displayed, the method further comprises the following steps:

It should be noted that, usually, the current frame remote sensing image map and the previous frame remote sensing image map can be selected to be compared, however, if the current frame remote sensing image map has a large change relative to the previous frame remote sensing image map, the amount of data to be transmitted is large, which is not favorable for solving the problem of transmission delay. The invention can enable the data processing center and the user terminal to synchronously cache the preset number of historical remote sensing image maps, and select one frame of historical remote sensing image map with less change relative to a newly received frame of remote sensing image map as the target historical remote sensing image map, thereby reducing the transmitted data volume and effectively solving the problem of transmission delay.

According to the specific embodiment of the invention, the data processing center and the user terminal synchronously cache the preset number of historical remote sensing image maps, which specifically comprises the following steps:

the data processing center and the user terminal always keep caching a preset number of historical remote sensing image maps; when the data processing center sends out one frame of remote sensing image map, the remote sensing image map is updated and cached in a preset number of historical remote sensing image maps at the side end, and the historical remote sensing image map with the earliest sending time sequence at the side end is removed; and updating and caching the divided map area corresponding to one remote sensing image map in a preset number of historical remote sensing image maps at the side end when the user terminal receives the divided map area corresponding to one remote sensing image map, and removing the historical remote sensing image map with the earliest receiving time sequence at the side end.

It should be noted that, in order to further improve the comparison efficiency of the map area, the present invention may compare the abstract values of the map area, and the comparison method is described above and will not be described herein.

According to the embodiment of the invention, the data processing center divides the current frame remote sensing image map into a plurality of map areas according to a preset dividing mode, and the method specifically comprises the following steps:

synchronizing the matched segmentation modes to corresponding user terminals;

According to the specific embodiment of the present invention, the association relationship between the multiple segmentation methods and different network signal levels can be characterized as follows:

the multiple division modes are classified according to the division density, the network signals are classified according to the signal intensity, the dense division mode corresponds to the network signal level with low signal intensity, and the sparse division mode corresponds to the network signal level with high signal intensity.

It can be understood that different user terminals are in different network coverage areas, corresponding network signals are different, and for a user terminal with a poor network signal, the data volume transmitted to the user terminal needs to be reduced as little as possible, so that the remote sensing image map can be divided into more map areas by adopting an intensive dividing mode, and when the map areas are compared with the historical remote sensing image map, more non-updated map areas can be eliminated, so that the data volume of the updated map areas needing to be transmitted is reduced. On the contrary, for the user terminal with better network signal, a sparse division mode can be adopted to reduce the calculation amount of division and combination of the data processing center and the user terminal as much as possible, thereby avoiding excessive occupation of CPU resources.

According to the specific embodiment of the present invention, the data processing center divides the current frame remote sensing image map into a plurality of map areas according to a predetermined dividing manner, and specifically includes:

the data processing center is preset with a plurality of segmentation modes, and establishes a relation table of the plurality of segmentation modes, different network signal levels and CPU performance;

the data processing center evaluates the network signals and CPU performance of each accessed user terminal;

matching a corresponding segmentation mode in the relation table aiming at the network signal and the CPU performance of each user terminal;

and synchronizing the matched segmentation modes to the corresponding user terminals.

It should be noted that the data processing center may agree on different segmentation modes for each user terminal, and may agree on two segmentation modes based on the CPU performance of the user terminal and the network signal, for example, if the network signal of a certain user terminal is not good, but the CPU performance is good, the matching segmentation mode should be able to segment the remote sensing image map into more map areas to reduce the amount of data transmitted, and increase the number of operations for comparison and combination at the local side based on the advantage of strong CPU computing power of the user terminal. Another example is: the network signal of the user terminal is good, but the CPU performance is not good, the matching segmentation mode can segment the remote sensing image map into fewer map areas so as to reduce the operation times of comparison or combination of the two sides at the local side, and the transmitted data volume is increased based on the advantage of good network signal.

It can be understood that the data processing center can summarize remote sensing image maps acquired by remote sensors of various terrains (or administrative regions), and corresponding segmentation modes are formulated for the remote sensing image maps of different terrains. For example, in some situations, the number of moving objects is large, and the moving objects are dense (for example, vehicles in a city district), and compared with an area without moving objects (for example, houses in the city district), the area of a single area is small, so that a more dense dividing manner can be adopted, and each divided map area is relatively small, so that more non-updated map areas can be screened out conveniently. In some situations, the number of moving objects is small, the moving objects are sparse (such as vehicles in suburban areas), and compared with areas without moving objects (such as cultivated lands, roads and the like in suburban areas), areas in a single area are large, so that a more sparse dividing mode can be adopted, the divided map areas are relatively large, the number of the divided map areas is reduced while the non-updated map areas are screened out, the number of subsequent comparison and combination times is further reduced, and excessive CPU resources are avoided being occupied.

updating the segmentation mode based on the changed region range;

In practical application, the segmentation mode can be adaptively updated based on the development change of the moving object according to the time trajectory. Generally, the moving objects may be people, building facilities, and the like, and the moving areas of the moving objects in a short time are concentrated, and if the division manner is not reasonable in the early stage, for example, too many map areas are divided, the complexity of later comparison and combination may be increased, and too many CPU resources will be occupied. If the map area is too small in division, the number of the map areas which are not updated can be reduced, most of the map areas have to be transmitted due to updating, and therefore the data volume of transmission is increased, and the real-time performance and low delay performance of remote sensing image map transmission are not guaranteed. Preferably, the value of the preset number ranges from 20 to 50, but is not limited thereto.

According to the embodiment of the invention, the conditions for triggering the update of the partition mode comprise the following two conditions:

firstly, triggering is carried out according to a preset time period, namely, the data processing center continuously receives a preset number of remote sensing image maps in a preset area according to the preset time period, and updating and segmenting processes are carried out.

And secondly, triggering according to the updating and displaying state of the remote sensing image map of the user terminal, namely when the updating and displaying delay of the remote sensing image map occurs in the user terminal, sending an updating request to the data processing center by the user terminal, and updating the segmentation mode flow by the data processing center based on the updating request.

According to the embodiment of the present invention, updating the segmentation mode based on the changed region range specifically includes:

presetting the shape of a remote sensing image map as a rectangle, segmenting according to a crisscross segmentation mode, and presetting the minimum longitudinal segmentation size and the minimum transverse segmentation size of the remote sensing image map;

respectively calculating the longitudinal distance between the upper boundary of each changed area range and the upper edge of the rectangle along the longitudinal direction of the remote sensing image map, and selecting the minimum longitudinal distance as a first longitudinal distance; respectively calculating the longitudinal distance between the lower boundary of each changed area range and the lower side of the rectangle, and selecting the minimum longitudinal distance as a second longitudinal distance; respectively calculating the longitudinal distance between two adjacent changed area ranges, and selecting the minimum longitudinal distance as a third longitudinal distance;

respectively judging whether the first longitudinal distance, the second longitudinal distance and the third longitudinal distance are larger than the minimum longitudinal dividing size, if so, comparing the first longitudinal distance, the second longitudinal distance and the third longitudinal distance, selecting the minimum longitudinal distance as a first target longitudinal distance, and then selecting the maximum size of the rectangular side edge capable of being longitudinally equally divided in the interval range of the first target longitudinal distance and the minimum longitudinal dividing size as the final longitudinal dividing size;

if one or two of the longitudinal intervals are larger than the minimum longitudinal division size, selecting the largest longitudinal interval from the longitudinal intervals larger than the minimum longitudinal division size as a second target longitudinal interval, and then selecting the largest dimension capable of longitudinally equally dividing the side edge of the rectangle within the interval range of the second target longitudinal interval and the minimum longitudinal division size as a final longitudinal division size;

if the minimum longitudinal split size is less than or equal to the minimum longitudinal split size, selecting the minimum longitudinal split size as a final longitudinal cutting size;

respectively calculating the transverse distance between the left boundary of each changed area range and the left side of the rectangle along the transverse direction of the remote sensing image map, and selecting the minimum transverse distance as a first transverse distance; respectively calculating the transverse distance between the right boundary of each changed area range and the right side edge of the rectangle, and selecting the minimum transverse distance as a second transverse distance; respectively calculating the transverse distance between two adjacent changed area ranges, and selecting the minimum transverse distance as a third transverse distance;

respectively judging whether the first transverse distance, the second transverse distance and the third transverse distance are larger than the minimum transverse dividing size, if so, comparing the first transverse distance, the second transverse distance and the third transverse distance, selecting the minimum transverse distance as a first target transverse distance, and then selecting the maximum size capable of transversely equally dividing the upper side and the lower side of the rectangle in the interval range of the first target transverse distance and the minimum transverse dividing size as the final transverse dividing size;

if one or two of the transverse distances are larger than the minimum transverse dividing size, selecting the largest transverse distance from the transverse distances larger than the minimum transverse dividing size as a second target transverse distance, and then selecting the largest size capable of transversely equally dividing the upper side and the lower side of the rectangle within the interval range of the second target transverse distance and the minimum transverse dividing size as a final transverse dividing size;

if the minimum transverse dividing sizes are less than or equal to the minimum transverse dividing size, selecting the minimum transverse dividing size as a final transverse cutting size;

and updating the segmentation mode according to the obtained final longitudinal segmentation size and the transverse segmentation size.

It is understood that the minimum vertical division size is the minimum division size for equally dividing the sides of the rectangle along the vertical direction, and the minimum horizontal division size is the minimum division size for equally dividing the upper and lower sides of the rectangle along the horizontal direction.

It should be noted that, when the segmentation mode is set, the horizontal and vertical segmentation sizes cannot be too small, and if the horizontal and vertical segmentation sizes are too small, the number of segmented map areas is increased, so that the complexity of map area comparison and combination is increased; the size of the map is not too large, and if the size of the map is too large, the area of the non-updated map is not easy to be divided, so that the phenomenon of transmission delay is not avoided.

As shown in fig. 2, a plurality of irregular figures, that is, a region range in which the moving object changes exist in the remote sensing image map. The first longitudinal spacing, the second longitudinal spacing, and the third longitudinal spacing, as well as the first lateral spacing, the second lateral spacing, and the third lateral spacing, may be made according to varying area ranges. For ease of illustration, only three regions of variation are labeled in fig. 2, as well as a first longitudinal spacing, a second longitudinal spacing, and a third longitudinal spacing.

As shown in fig. 3, the second aspect of the present invention further provides a system 3 for acquiring a remote sensing image map in real time, which includes at least one memory 31 and at least one processor 32, where the memory stores a program of a method for acquiring a remote sensing image map in real time, and when the program of the method is executed by the at least one processor, the method includes the following steps:

and filtering out an un-updated map area from the historical frame remote sensing image map by the user terminal based on the updated map area, and then combining the un-updated map area with the received updated map area to restore the un-updated map area into the current frame remote sensing image map and display the current frame remote sensing image map.

According to the embodiment of the invention, after the current frame remote sensing image map is restored and displayed, when the program of the real-time acquisition method based on the remote sensing image map is executed by at least one processor, the following steps are also realized:

The third aspect of the present invention further provides a computer-readable storage medium, in which a remote sensing image map-based real-time obtaining method program is stored, and when the remote sensing image map-based real-time obtaining method program is executed by at least one processor, the steps of the remote sensing image map-based real-time obtaining method are implemented.

The intelligent detection of the public facilities is realized by combining the big data information resources and the neural network machine learning method, the unmanned aerial vehicle replaces manual detection, the detection difficulty is reduced, the detection cost is saved, the detection efficiency is improved, meanwhile, due to the fact that no excessive human factors participate, the phenomena of missing detection or false detection can be avoided, and the detection accuracy is further improved.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. A real-time acquisition method based on a remote sensing image map is characterized by comprising the following steps:

updating the segmentation mode based on the changed region range, wherein the specific updating segmentation mode is as follows: presetting the shape of a remote sensing image map as a rectangle, segmenting according to a crisscross segmentation mode, and presetting the minimum longitudinal segmentation size and the minimum transverse segmentation size of the remote sensing image map;

updating the segmentation mode according to the obtained final longitudinal segmentation size and the transverse segmentation size;

2. The method for acquiring the remote sensing image map in real time according to claim 1, wherein each map area in the current frame remote sensing image map is compared with the map areas at the same positions in the historical frame remote sensing image map one by one, and specifically comprises the following steps:

3. The method for acquiring the remote sensing image map in real time according to claim 2, wherein after the current remote sensing image map is restored and displayed, the method further comprises:

4. The method for acquiring the remote sensing image map in real time according to claim 1, wherein the data processing center divides the current frame remote sensing image map into a plurality of map areas according to a predetermined dividing manner, and specifically comprises:

synchronizing the matched segmentation modes to corresponding user terminals;

5. The method for acquiring the remote sensing image map in real time according to claim 1, wherein the data processing center divides the current frame remote sensing image map into a plurality of map areas according to a predetermined dividing manner, and specifically comprises:

6. A real-time acquisition system based on a remote sensing image map is characterized by comprising at least one memory and at least one processor, wherein a real-time acquisition method program based on the remote sensing image map is stored in the memory, and when being executed by the at least one processor, the real-time acquisition method program based on the remote sensing image map realizes the following steps:

7. The system according to claim 6, wherein each map area in the current frame remote sensing image map is compared with map areas at the same position in the historical frame remote sensing image map one by one, and the system specifically comprises:

8. The system according to claim 7, wherein after the remote sensing image map is restored to the current frame remote sensing image map and displayed, the program of the method for obtaining the remote sensing image map in real time further implements the following steps when executed by the at least one processor:

9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a remote sensing image map-based real-time acquisition method program, and when the remote sensing image map-based real-time acquisition method program is executed by at least one processor, the steps of the remote sensing image map-based real-time acquisition method according to any one of claims 1 to 5 are implemented.