Data processing method, device, equipment and medium based on image information fusion

Abstract

The present invention provides a data processing method based on image information fusion, which can be applied to the field of space object detection technology, including: acquiring M frames of long exposure images and N frames of short exposure images; extracting information of dark and weak space objects in point images from the long exposure images, and obtaining the function of the object's motion trajectory and flow rate changing with time; extracting information of dark and weak sources from the short exposure images, the information of the dark and weak sources including a first position and a first flow rate; calculating the second position and second flow rate of the object at the time of short exposure image acquisition based on the function of the motion trajectory and flow rate changing with time; determining the real position and real flow rate of the object based on the position error and flow rate error; and then obtaining observation data of the dark and weak space objects. By fusing the information of dark and weak space objects in images with different exposures, high-precision positioning of dark and weak space objects is achieved. The present invention also provides a data processing device, equipment and medium based on image information fusion.

Description

Technical Field

[0001] The present invention relates to the technical field of space object detection, and in particular to a data processing method, device, equipment and medium based on image information fusion. Background Art

[0002] When using photoelectric observation technology to detect faint space objects, it is usually necessary to use a larger aperture photoelectric telescope system. In this case, two aspects need to be considered. First, since the construction cost of the photoelectric telescope is proportional to the cube of the telescope's aperture, the construction of a large-aperture photoelectric telescope system is likely to increase my country's economic burden; second, under normal circumstances, a large-aperture photoelectric telescope system has a small field of view, and more accurate forecast information is required when tracking and observing faint space objects. In addition, due to the lack of synchronization with the movement of stars, when tracking and observing faint space objects, the star image of the background calibration star in the field of view will be elongated. At present, it is still difficult to obtain high-precision astronomical positioning of faint space objects. Therefore, improving the positioning method of the photoelectric telescope system and then improving the positioning accuracy of faint space objects has a high application value in practical work.

[0003] Traditional observation methods are that the camera basically collects images at a fixed exposure time within a certain period of time. In order to improve the detection success rate of faint targets in tracking mode, the only way is to increase the exposure time. The longer the exposure time of the camera, the longer the star image trajectory of the calibration star used in astronomical positioning, causing the pull line of the background star to be too long, thereby reducing the positioning accuracy of the calibration star, and further affecting the positioning accuracy of faint space objects, making it impossible to achieve astronomical positioning and difficult to obtain high-precision observation data of faint targets. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve at least one of the above-mentioned technical problems arising from the high-precision positioning of dim space objects in the prior art, the embodiments of the present invention provide a data processing method, device, equipment and medium based on image information fusion, which first processes the long and short exposure images separately, and fully utilizes the characteristic that the current equipment can track with high precision for a long time, and finally fuses the position and flow-related information of the space object through function fitting, and realizes high-precision positioning of the dim space object by fusing the dim space object information in images with different exposures.

[0006] (II) Technical solution

[0007] In view of the above technical problems, embodiments of the present invention provide a data processing method, device, equipment and medium based on image information fusion.

[0008] According to a first aspect of the present invention, a data processing method based on image information fusion is provided, comprising: setting M long-exposure image acquisition moments and N short-exposure image acquisition moments in an observation arc segment; acquiring one frame of long-exposure image at each long-exposure image acquisition moment and acquiring one frame of short-exposure image at each short-exposure image acquisition moment, to obtain M frames of long-exposure image and N frames of short-exposure image; performing flat-field, dark-field and local correction preprocessing on the M frames of long-exposure image and the N frames of short-exposure image, to obtain M frames of preprocessed long-exposure image and N frames of preprocessed short-exposure image; extracting information of dark and weak space objects in the form of point images from the M frames of preprocessed long-exposure image, and using a hierarchical clustering method to associate information of the same dark and weak space object to form a dark and weak space object position arc segment, based on The position arc segment of the faint space object is fitted to obtain the function of the motion trajectory of each object changing with time and the function of the flow changing with time; the information of the faint source is extracted from the N frames of preprocessed short exposure images, and the film model of the N frames of preprocessed short exposure images is calculated, wherein the information of the faint source includes the position and flow of the object in the image, and a first position and a first flow are obtained; based on the function of the motion trajectory changing with time and the function of the flow changing with time, the position and flow of the corresponding object in the image at the time of N short exposure image acquisition are calculated to obtain a second position and a second flow; based on the error between the first position and the second position and the error between the first flow and the second flow, the true position and true flow of the object are determined; and based on the film model, the true position and the true flow, the observation data of the faint space object is obtained.

[0009] In some exemplary embodiments, the M long exposure image acquisition moments include an arc start moment and an arc end moment; the M long exposure image acquisition moments are evenly distributed between the arc start moment and the arc end moment; and the exposure duration of the long exposure image is related to the estimated brightness of the target object.

[0010] In some exemplary embodiments, the N short exposure image acquisition moments include an arc segment start moment and an arc segment end moment; the exposure duration of the short exposure image is related to the estimated movement speed of the target object and the pixel scale of the observation device.

[0011] In some exemplary embodiments, in the process of associating information of the same faint space object using a hierarchical clustering method, a preset tolerance is added to the information of the faint space object; in the hierarchical clustering process, at least 4 points are connected together to form a valid position arc.

[0012] In some exemplary embodiments, the fitting function of the function of the motion trajectory varying with time includes a quadratic function; and the fitting function of the function of the flow varying with time includes a cubic spline interpolation function.

[0013] In some exemplary embodiments, based on the error between the first position and the second position and the error between the first flow and the second flow, determining the actual position and the actual flow of the object includes: calculating the error between the first position and the second position to obtain the first error; calculating the error between the first flow and the second flow to obtain the second error; comparing the first error with the preset position error and comparing the second error with the preset flow error to obtain a comparison result; determining the actual position and the actual flow of the object based on the comparison result, wherein if the first error is less than the preset position error and the second error is less than the preset flow error, the first position is defined as the actual position of the object and the first flow is defined as the actual flow of the object; if the first error is greater than the preset position error and / or the second error is greater than the preset flow error, the second position is defined as the actual position of the object and the second flow is defined as the actual flow of the object.

[0014] In some exemplary embodiments, the preset position error does not exceed 10 pixels; and the preset flow error does not exceed 5 times.

[0015] According to a second aspect of the present invention, there is provided a data processing device based on image information fusion, comprising: a setting module, used to set M long-exposure image acquisition moments and N short-exposure image acquisition moments in an observation arc segment; an acquisition module, used to acquire one frame of long-exposure image at each long-exposure image acquisition moment and one frame of short-exposure image at each short-exposure image acquisition moment, to obtain M frames of long-exposure image and N frames of short-exposure image; a preprocessing module, used to perform flat-field, dark-field and local correction preprocessing on the M frames of long-exposure image and the N frames of short-exposure image, to obtain M frames of preprocessed long-exposure image and N frames of preprocessed short-exposure image; a fitting module, used to extract information of dark and weak spatial objects in the form of point images from the M frames of preprocessed long-exposure image, and to associate information of the same dark and weak spatial object using a hierarchical clustering method to form a dark and weak spatial object position arc segment, based on the dark and weak spatial image. The object position arc segment is fitted to obtain the function of the motion trajectory of each object changing with time and the function of the flow changing with time; the first acquisition module is used to extract the information of the dark source from the N frames of pre-processed short exposure images, and calculate the negative film model of the N frames of pre-processed short exposure images, wherein the information of the dark source includes the position and flow of the object in the image, and obtain the first position and the first flow; the second acquisition module is used to calculate the position and flow of the corresponding object in the image at the time of N short exposure image acquisition based on the function of the motion trajectory changing with time and the function of the flow changing with time, and obtain the second position and the second flow; the third acquisition module is used to determine the real position and the real flow of the object based on the error between the first position and the second position and the error between the first flow and the second flow; and the data generation module is used to obtain the observation data of the dark space object based on the negative film model, the real position and the real flow. According to the third aspect of the present invention, an electronic device is provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program when running to implement the above method. According to a fourth aspect of the present invention, a storage medium is provided, characterized in that: computer-readable instructions are stored in the storage medium, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the above method.

[0016] (III) Beneficial effects

[0017] It can be seen from the above technical solutions that the data processing method, device, equipment and medium based on image information fusion provided by the embodiments of the present invention have at least the following beneficial effects:

[0018] (1) It can effectively realize the efficient detection of some faint space objects using small-aperture telescopes, and can effectively extract high-precision data of the observed targets, greatly improving the detection capability and detection accuracy of small-aperture telescopes for faint targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0020] Figure 1 The flowchart of a data processing method based on image information fusion according to an embodiment of the present invention is schematically shown.

[0021] Figure 2 The flowchart of determining the real position and real flow rate of an object based on the error between the first position and the second position and the error between the first flow rate and the second flow rate according to an embodiment of the present invention is schematically shown.

[0022] Figure 3 A schematic diagram of target observation data accuracy evaluation results using a data processing method based on image information fusion according to an embodiment of the present invention is shown schematically.

[0023] Figure 4 The structure block diagram of a data processing device based on image information fusion according to an embodiment of the present invention is schematically shown.

[0024] Figure 5 A block diagram of an electronic device according to a data processing method based on image information fusion according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Figure 1 The flowchart of a data processing method based on image information fusion according to an embodiment of the present invention is schematically shown.

[0027] Depend on Figure 1 It can be seen that a data processing method based on image information fusion according to an embodiment of the present invention includes steps S110-S180.

[0028] In step S110 , M long-exposure image acquisition moments and N short-exposure image acquisition moments are set in one observation arc segment.

[0029] In some exemplary embodiments, the M long exposure image acquisition moments include an arc start moment and an arc end moment; the M long exposure image acquisition moments are evenly distributed between the arc start moment and the arc end moment, and the exposure duration of the long exposure image is related to the estimated brightness of the target object.

[0030] In some exemplary embodiments, the N short-exposure image acquisition moments include the arc segment start moment and the arc segment end moment, and other moments can be set arbitrarily as needed; the exposure time of the short-exposure image is related to the estimated motion speed of the target object and the pixel scale of the observation device, and generally requires that the exposure time of the short-exposure image is not shorter than the time for the target to pass through one pixel and not longer than the time for the target to pass through three pixels. The exposure time of the long-exposure image is longer than the exposure time of the short-exposure image.

[0031] In step S120, one frame of long exposure image is collected at each long exposure image collection moment and one frame of short exposure image is collected at each short exposure image collection moment, to obtain M frames of long exposure image and N frames of short exposure image.

[0032] In step S130 , flat field, dark field and local correction preprocessing is performed on the M frames of long exposure images and the N frames of short exposure images to obtain M frames of preprocessed long exposure images and N frames of preprocessed short exposure images.

[0033] In step S140, information of dark space objects in point images is extracted from the M-frame preprocessed long exposure images, and the information of the same dark space object is associated using a hierarchical clustering method to form dark space object position arcs. Based on the dark space object position arcs, a function of the motion trajectory of each object changing with time and a function of the flow changing with time are fitted.

[0034] When using the hierarchical clustering method to associate the information of the same faint space object, it is necessary to take into account the influence of device jitter and other factors, add a certain tolerance, and at least 4 points need to be connected together to form a valid position arc segment; the fitting function of the function of the motion trajectory changing with time includes a quadratic function.

[0035] In some exemplary embodiments, in the process of fitting the function of each object's motion trajectory changing with time and the function of the flow changing with time, the two functions are fitted separately. It is generally recommended to fit the function of the motion trajectory changing with time using a quadratic function, and it is generally recommended to fit the function of the flow changing with time using a cubic spline interpolation function.

[0036] In step S150, information of dark sources is extracted from N frames of preprocessed short exposure images, and a film model of the N frames of preprocessed short exposure images is calculated, wherein the information of dark sources includes the position and flow of the object in the image, and a first position and a first flow are obtained.

[0037] In step S160, the position and flow rate of the corresponding object in the image at the N short exposure image acquisition moments are calculated based on the function of the motion trajectory changing with time and the function of the flow rate changing with time to obtain a second position and a second flow rate.

[0038] In step S170 , the actual position and actual flow rate of the object are determined based on the error between the first position and the second position and the error between the first flow rate and the second flow rate.

[0039] In some exemplary embodiments, step S170 includes steps S171-S174, see Figure 2 .

[0040] In step S171, the error between the first position and the second position is calculated to obtain a first error.

[0041] In step S172, the error between the first flow rate and the second flow rate is calculated to obtain a second error.

[0042] In step S173, the first error is compared with the preset position error and the second error is compared with the preset flow error to obtain a comparison result. Optionally, the preset position error does not exceed 10 pixels; and the preset flow error does not exceed 5 times (that is, the flow values ​​of adjacent points within 5 times can be considered reasonable).

[0043] In step S174, based on the comparison result, the actual position and actual flow of the object are determined, wherein if the first error is less than the preset position error and the second error is less than the preset flow error, the first position is defined as the actual position of the object and the first flow is defined as the actual flow of the object; if the first error is greater than the preset position error and / or the second error is greater than the preset flow error, the second position is defined as the actual position of the object and the second flow is defined as the actual flow of the object.

[0044] In step S180, based on the film model, the real position and the real flow, the observation data of the faint space object is obtained.

[0045] Figure 3 A schematic diagram of target observation data accuracy evaluation results using a data processing method based on image information fusion according to an embodiment of the present invention is shown schematically.

[0046] like Figure 3 As shown in the figure, a set of mixed images of multiple exposures (the observation time is 0.216 seconds for the long exposure time and 0.01 seconds for the short exposure time) of a target (spherical target with an orbital altitude of about 700 kilometers and a size of 20 cm) taken by a 36 cm telescope are shown in the attached figure. The accuracy evaluation results of the positioning data processed by this method are shown in the attached figure. Figure 2The results show that the positioning accuracy is better than 2 arc seconds and better than 1 pixel scale, which is comparable to the international level. This method greatly improves the detection capability and accuracy of small-aperture telescopes for dim targets.

[0047] In an embodiment of the present invention, a group of images staggered with long and short exposures are collected by setting a shooting rule during the observation of a faint target, and then the position sequence and flow sequence information of the space object in the long exposure image are extracted, and the motion function of the object over time and the change function of the flow over time on the image are fitted, and then the film model is determined based on the short exposure image and all faint sources are extracted, and then the position and flow of the faint target on the short exposure image are jointly determined based on the source in the short exposure image and the long exposure fitting function interpolation, and finally the observation data of the faint target is formed based on the position in the short exposure image and the film model. This method greatly improves the detection capability and detection accuracy of small-aperture telescopes for faint targets.

[0048] Figure 4 The structure block diagram of a data processing device based on image information fusion according to an embodiment of the present invention is schematically shown.

[0049] like Figure 4 As shown, a data processing device 800 based on image information fusion according to an embodiment of the present invention includes a setting module 810, an acquisition module 820, a preprocessing module 830, a fitting module 840, a first acquisition module 850, a second acquisition module 860, a third acquisition module 870 and a data generation module 880.

[0050] The setting module 810 is used to set M long-exposure image acquisition moments and N short-exposure image acquisition moments in one observation arc segment.

[0051] The acquisition module 820 is used to acquire one frame of long exposure image at each long exposure image acquisition moment and one frame of short exposure image at each short exposure image acquisition moment, so as to obtain M frames of long exposure image and N frames of short exposure image.

[0052] The preprocessing module 830 is used to perform flat field, dark field and local correction preprocessing on the M frames of long exposure images and the N frames of short exposure images to obtain M frames of preprocessed long exposure images and N frames of preprocessed short exposure images.

[0053] The fitting module 840 is used to extract the information of the dark space objects in the form of point images from the long exposure images preprocessed by M frames, and use the hierarchical clustering method to associate the information of the same dark space object to form the dark space object position arc segment. Based on the dark space object position arc segment, the function of the motion trajectory of each object changing with time and the function of the flow changing with time are fitted.

[0054] The first acquisition module 850 is used to extract the information of the dark source from the N frames of preprocessed short exposure images, and calculate the film model of the N frames of preprocessed short exposure images, wherein the information of the dark source includes the position and flow of the object in the image, and obtain the first position and the first flow.

[0055] The second acquisition module 860 is used to calculate the position and flow rate of the corresponding object in the image at the N short exposure image acquisition moments based on the function of the motion trajectory changing with time and the function of the flow rate changing with time, and obtain the second position and the second flow rate.

[0056] The third acquisition module 870 is used to determine the actual position and actual flow rate of the object based on the error between the first position and the second position and the error between the first flow rate and the second flow rate.

[0057] The data generation module 880 is used to obtain observation data of faint space objects based on the film model, the real position and the real flow.

[0058] In some specific embodiments, any multiple modules among the setting module 810, the acquisition module 820, the preprocessing module 830, the fitting module 840, the first acquisition module 850, the second acquisition module 860, the third acquisition module 870 and the data generation module 880 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module.

[0059] In some specific embodiments, at least one of the setting module 810, the acquisition module 820, the preprocessing module 830, the fitting module 840, the first acquisition module 850, the second acquisition module 860, the third acquisition module 870 and the data generation module 880 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in any appropriate combination of any of them. Alternatively, at least one of the setting module 810, the acquisition module 820, the preprocessing module 830, the fitting module 840, the first acquisition module 850, the second acquisition module 860, the third acquisition module 870 and the data generation module 880 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be performed.

[0060] Figure 5A block diagram of an electronic device according to a data processing method based on image information fusion according to an embodiment of the present invention is schematically shown.

[0061] like Figure 5 As shown, the electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 to the random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an on-board memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0062] In RAM603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM602 and RAM603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to an embodiment of the present invention by executing the program in ROM602 and / or RAM603. It should be noted that the program can also be stored in one or more memories other than ROM602 and RAM603. Processor 601 can also perform various operations of the method flow according to an embodiment of the present invention by executing the program stored in one or more memories.

[0063] In some specific embodiments, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0064] An embodiment of the present invention shows a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0065] In some specific embodiments, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 602 and / or RAM 603 described above and / or one or more memories other than ROM 602 and RAM 603.

[0066] An embodiment of the present invention shows a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method provided by the embodiment of the present invention.

[0067] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when it is executed by the processor 601. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0068] In some specific embodiments, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0069] In some specific embodiments, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0070] In some specific embodiments, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages, specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, such as Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0071] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0072] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A data processing method based on image information fusion, characterized in that: include: In one observation arc segment, M long-exposure image acquisition moments and N short-exposure image acquisition moments are set; At each long exposure image acquisition moment, one frame of long exposure image is acquired, and at each short exposure image acquisition moment, one frame of short exposure image is acquired, to obtain M frames of long exposure image and N frames of short exposure image; Performing flat field, dark field and local correction preprocessing on the M frames of long exposure images and the N frames of short exposure images to obtain M frames of preprocessed long exposure images and N frames of preprocessed short exposure images; Extracting information of dark space objects in point images from the M-frame preprocessed long exposure images, correlating information of the same dark space object using a hierarchical clustering method to form a dark space object position arc segment, and fitting a function of the motion trajectory of each object changing with time and a function of the flow rate changing with time based on the dark space object position arc segment; Extracting information of a dark source from the N frames of preprocessed short exposure images, and calculating a film model of the N frames of preprocessed short exposure images, wherein the information of the dark source includes a position and flow rate of an object in the image, and obtaining a first position and a first flow rate; Based on the function of the motion trajectory changing with time and the function of the flow changing with time, the position and flow of the corresponding object in the image at the N short exposure image acquisition moments are calculated to obtain a second position and a second flow; Determining a true position and a true flow rate of the object based on an error between the first position and the second position and an error between the first flow rate and the second flow rate; and Based on the film model, the real position and the real flow, the observation data of the faint space object is obtained.

2. The method according to claim 1, characterized in that The M long exposure image acquisition moments include an arc segment start moment and an arc segment end moment; The M long exposure image acquisition moments are evenly distributed between the arc segment start moment and the arc segment end moment; The exposure time of the long exposure image is related to the estimated brightness of the target object.

3. The method according to claim 1, characterized in that: The N short exposure image acquisition moments include an arc segment start moment and an arc segment end moment; The exposure time of the short exposure image is related to the estimated motion speed of the target object and the pixel scale of the observation device.

4. The method according to claim 1, characterized in that: In the process of associating the information of the same faint space object using the hierarchical clustering method, a preset tolerance is added to the information of the faint space object; In the hierarchical clustering process, at least 4 points are connected together to form a valid position arc.

5. The method according to claim 1, characterized in that: The fitting function of the function of the motion trajectory changing with time includes a quadratic function; The fitting function of the function of flow rate changing with time includes a cubic spline interpolation function.

6. The method according to claim 1, characterized in that The determining the real position and the real flow rate of the object based on the error between the first position and the second position and the error between the first flow rate and the second flow rate comprises: Calculating an error between the first position and the second position to obtain a first error; calculating an error between the first flow rate and the second flow rate to obtain a second error; Comparing the first error with a preset position error and comparing the second error with a preset flow error to obtain a comparison result; Based on the comparison results, the real position and real flow of the object are determined, If the first error is smaller than the preset position error and the second error is smaller than the preset flow error, the first position is defined as the actual position of the object and the first flow is defined as the actual flow of the object; If the first error is greater than the preset position error and / or the second error is greater than the preset flow error, the second position is defined as the actual position of the object and the second flow is defined as the actual flow of the object.

7. The method according to claim 6, characterized in that The preset position error does not exceed 10 pixels; and the preset flow error does not exceed 5 times.

8. A data processing device based on image information fusion, characterized in that: The device comprises: A setting module, used to set M long-exposure image acquisition moments and N short-exposure image acquisition moments in an observation arc segment; An acquisition module is used to acquire one frame of long exposure image at each long exposure image acquisition moment and to acquire one frame of short exposure image at each short exposure image acquisition moment, so as to obtain M frames of long exposure image and N frames of short exposure image; A preprocessing module, used for performing flat field, dark field and local correction preprocessing on the M frames of long exposure images and the N frames of short exposure images to obtain M frames of preprocessed long exposure images and N frames of preprocessed short exposure images; A fitting module is used to extract information of dark space objects in point images from the M frames of preprocessed long exposure images, associate information of the same dark space object using a hierarchical clustering method to form a dark space object position arc segment, and obtain a function of the motion trajectory of each object changing with time and a function of the flow rate changing with time based on the dark space object position arc segment; A first acquisition module is used to extract information of a dark source from the N frames of pre-processed short-exposure images, and calculate a negative film model of the N frames of pre-processed short-exposure images, wherein the information of the dark source includes a position and flow rate of an object in the image, and obtain a first position and a first flow rate; A second acquisition module is used to calculate the position and flow rate of the corresponding object in the image at the N short exposure image acquisition moments based on the function of the motion trajectory changing with time and the function of the flow rate changing with time, so as to obtain a second position and a second flow rate; a third acquisition module, configured to determine a real position and a real flow rate of the object based on an error between the first position and the second position and an error between the first flow rate and the second flow rate; and A data generation module is used to obtain observation data of faint space objects based on the film model, the real position and the real flow.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the method according to any one of claims 1 to 7.

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