Auxiliary focusing method, device, equipment, medium and program product of space camera

Abstract

The application relates to the field of auxiliary focusing technology, in particular to an auxiliary focusing method, device, equipment, medium and program product of a space camera, wherein the method comprises the following steps: acquiring multiple frames of continuous remote sensing images and corresponding camera pixel parameter information of the space camera in different scenes under different focal lengths; calculating a definition score value, and extracting remote sensing images meeting a certain definition from the multiple frames of continuous remote sensing images; and then adjusting an initial image distance by using the corresponding camera pixel parameter information to obtain a final image distance and determine a final focal length. Therefore, the problems that in the related art, the adjustment rules set on the ground may not cover all possible shooting scenes and conditions, resulting in untimely focal length adjustment or unsatisfactory adjustment effect, and that the process of first shooting pictures and then analyzing and adjusting is not only cumbersome, needs to consume more time and resources, and is also subject to certain subjective factors, and the accuracy is easily affected, are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of auxiliary focusing, and in particular relates to an auxiliary focusing method, device, equipment, medium and program product of a space camera. BACKGROUND

[0002] Space cameras are widely used. According to the actual use of the camera on the satellite and the characteristics of the detected object, the space camera can be applied to the fields of forestry monitoring, agricultural investigation, meteorology, ocean observation, disaster prevention, topographic observation, military imaging reconnaissance and the like. In the application process of the space camera, due to the influence of factors such as satellite attitude, orbit and weather, the space camera may capture pictures with unclear quality when shooting, and it is necessary to adjust parameters to capture high-quality remote sensing images. At the same time, due to the complexity of the space camera environment, a high-performance camera load is needed to ensure the quality of the remote sensing image.

[0003] In the related art, the focal length of the space camera can be adjusted according to the adjustment rules set by the ground when the space camera is shooting, and then the corresponding remote sensing image is obtained. Alternatively, the space camera can be used to first capture pictures to the ground equipment, and then the ground personnel analyzes the pictures and sends adjustment instructions to the space camera, and then adjusts the focal length of the space camera.

[0004] However, in the related art, the adjustment rules set by the ground may not cover all possible shooting scenes and conditions, resulting in untimely focal length adjustment or unsatisfactory adjustment effect. The process of first shooting pictures and then analyzing and adjusting is not only cumbersome, but also requires more time and resources, and there is a certain subjective factor, and its accuracy is easily affected, which needs to be improved. SUMMARY

[0005] The present application provides an auxiliary focusing method, device, equipment, medium and program product of a space camera to solve the problems in the related art that the adjustment rules set by the ground may not cover all possible shooting scenes and conditions, resulting in untimely focal length adjustment or unsatisfactory adjustment effect, and the process of first shooting pictures and then analyzing and adjusting is not only cumbersome, but also requires more time and resources, and there is a certain subjective factor, and its accuracy is easily affected.

[0006] The first aspect embodiment of the present application provides an auxiliary focusing method of a space camera, including the following steps: acquiring a plurality of continuous remote sensing images of the space camera in different scenes and under different focal lengths, and obtaining camera pixel parameter information corresponding to the plurality of continuous remote sensing images based on the plurality of continuous remote sensing images; calculating a definition score value of the plurality of continuous remote sensing images, and extracting a remote sensing image satisfying a preset definition from the plurality of continuous remote sensing images based on the definition score value; adjusting an initial image distance of the space camera by using the camera pixel parameter information corresponding to the remote sensing image satisfying the preset definition to obtain a final image distance of the space camera, and obtaining a final focal length of the space camera based on the final image distance and the different focal lengths.

[0007] Optionally, in an embodiment of the present application, the calculation of the definition score value of the plurality of continuous remote sensing images includes: inputting the plurality of continuous remote sensing images into a pre-trained matching model to obtain the definition score value of the plurality of continuous remote sensing images.

[0008] Optionally, in an embodiment of the present application, the calculation of the definition score value of the plurality of continuous remote sensing images includes: acquiring a feature value of at least one image feature in the plurality of continuous remote sensing images; and combining a feature weight of the at least one image feature and the feature value to calculate a first definition score value of the plurality of continuous remote sensing images.

[0009] Optionally, in an embodiment of the present application, the calculation formula of the first definition score value can be, but is not limited to:

[0010]

[0011] wherein S t is the definition score value of the tth remote sensing image, i and j are the ith straight line feature and the jth circular feature in the tth image, l is a straight line feature, c is a circular feature, m is the number of straight line features, n is the number of circular features, L i is the weight value of different straight line features, C j is the weight value of different circular features.

[0012] Optionally, in an embodiment of the present application, the calculation of the definition score value of the plurality of continuous remote sensing images includes: acquiring a region image of different regions in each continuous remote sensing image based on the plurality of continuous remote sensing images; and calculating a second definition score value of the plurality of continuous remote sensing images based on a region weight of the different regions and the region image.

[0013] Optionally, in an embodiment of the present application, the calculation formula of the second definition score value can be, but is not limited to:

[0014]

[0015] wherein, x is the number of regions of the tth frame remote sensing image, w k is the weight value of each region.

[0016] Optionally, in an embodiment of the present application, the calculation of the definition score value of the plurality of continuous remote sensing images comprises: obtaining a target feature of at least one target in the plurality of continuous remote sensing images; and calculating a third definition score value of the plurality of continuous remote sensing images based on a target weight of the target feature and the target feature; wherein, the calculation formula of the third definition score value can be but is not limited to:

[0017]

[0018] wherein, w k is the weight value of the kth region in the tth frame remote sensing image, A is the type of the target in the tth frame remote sensing image, B is the weight value of the target in the tth frame remote sensing image, and D is the confidence of the target in the tth frame remote sensing image.

[0019] The second aspect embodiment of the present application provides an auxiliary focusing device of a space camera, comprising: an acquisition module, configured to acquire a plurality of continuous remote sensing images captured by a space camera in different scenes at different focal lengths, and obtain camera pixel parameter information corresponding to the plurality of continuous remote sensing images based on the plurality of continuous remote sensing images; a calculation module, configured to calculate a definition score value of the plurality of continuous remote sensing images, and extract a remote sensing image satisfying a preset definition from the plurality of continuous remote sensing images based on the definition score value; and a generation module, configured to adjust an initial image distance of the space camera by using camera pixel parameter information corresponding to the remote sensing image satisfying the preset definition, to obtain a final image distance of the space camera, and obtain a final focal length of the space camera based on the final image distance and the different focal lengths.

[0020] Optionally, in an embodiment of the present application, the calculation module comprises: an input unit, configured to input the plurality of continuous remote sensing images into a pre-trained matching model, to obtain the definition score value of the plurality of continuous remote sensing images.

[0021] Optionally, in an embodiment of the present application, the calculation module comprises: a first acquisition unit, configured to acquire a feature value of at least one image feature in the plurality of continuous remote sensing images; and a first calculation unit, configured to calculate a first definition score value of the plurality of continuous remote sensing images in combination with a feature weight of the at least one image feature and the feature value.

[0022] Optionally, in an embodiment of the present application, the calculation formula of the first definition score value can be but is not limited to:

[0023]

[0024] wherein S t is the definition of the clarity score value of the t-th frame remote sensing image, i and j are the i-th straight line feature and the j-th circular feature in the t-th frame image respectively, l is the straight line feature, c is the circular feature, m is the number of straight line features, n is the number of circular features, L i is the weight value of different straight line features, C j is the weight value of different circular features.

[0025] Optionally, in an embodiment of the present application, the calculation module comprises: a second acquisition unit, configured to acquire a region image of different regions in each continuous remote sensing image based on the plurality of continuous remote sensing images; and a second calculation unit, configured to calculate a second clarity score value of the plurality of continuous remote sensing images based on region weights of the different regions and the region images.

[0026] Optionally, in an embodiment of the present application, the calculation formula of the second clarity score value can be but is not limited to:

[0027]

[0028] wherein x is the number of regions of the t-th frame remote sensing image, w k is the weight value of each region.

[0029] Optionally, in an embodiment of the present application, the calculation module comprises: a third acquisition unit, configured to acquire target features of at least one target in the plurality of continuous remote sensing images; and a third calculation unit, configured to calculate a third clarity score value of the plurality of continuous remote sensing images based on target weights of the target features and the target features; wherein the calculation formula of the third clarity score value can be but is not limited to:

[0030]

[0031] wherein w k is the weight value of the k-th region in the t-th frame remote sensing image, A is the type of the target in the t-th frame remote sensing image, B is the weight value of the target in the t-th frame remote sensing image, and D is the confidence of the target in the t-th frame remote sensing image.

[0032] The third aspect embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor executes the program to implement the auxiliary focusing method of the spatial camera as described in the above embodiments.

[0033] The fourth aspect of the present application provides a computer readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned auxiliary focusing method of a space camera.

[0034] The fifth aspect of the present application provides a computer program product comprising a computer program, which, when executed by a processor, implements the above-mentioned auxiliary focusing method of a space camera.

[0035] The embodiments of the present application can obtain remote sensing images meeting a certain definition according to multiple frames of continuous remote sensing images, corresponding camera pixel parameter information and definition score values of the space camera under different focal lengths in different scenes, and then adjust the initial image distance of the space camera using the camera pixel parameter information corresponding to the remote sensing images meeting a certain definition to obtain the final image distance, thereby determining the final focal length of the space camera, which can adapt to the shooting requirements under different scenes and focal lengths, ensure that the space camera can shoot high-quality remote sensing images under different conditions, improve the automation level of remote sensing image processing, and reduce manual intervention and errors. Thus, the problems that the adjustment rules set on the ground in the related art can not cover all possible shooting scenes and conditions, resulting in untimely focal length adjustment or unsatisfactory adjustment effect, and that the process of first shooting pictures and then analyzing and adjusting is not only cumbersome, requires more time and resources, and has certain subjective factors, and its accuracy is easily affected, are solved.

[0036] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0037] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings, wherein:

[0038] Figure 1 A block diagram of a camera system for auxiliary focusing of a space camera according to an embodiment of the present application;

[0039] Figure 2 A flowchart of an auxiliary focusing method of a space camera according to an embodiment of the present application;

[0040] Figure 3 A flowchart of an auxiliary focusing method of a space camera according to an embodiment of the present application;

[0041] Figure 4 A flowchart of an auxiliary focusing method of a space camera according to another embodiment of the present application;

[0042] Figure 5This is a flowchart of an auxiliary focusing method for a space camera according to yet another embodiment of this application;

[0043] Figure 6 This is a block diagram of an auxiliary focusing device for a space camera according to an embodiment of this application;

[0044] Figure 7 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0045] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0046] The following description, with reference to the accompanying drawings, describes an auxiliary focusing method, apparatus, device, medium, and program product for a space camera according to embodiments of this application. Addressing the issue that ground-based adjustment rules mentioned in the background art may not cover all possible shooting scenarios and conditions, leading to untimely or unsatisfactory focus adjustments, and that the process of capturing images first and then analyzing and adjusting them is not only cumbersome and time-consuming but also subject to subjective factors, making its accuracy susceptible to errors, this application provides an auxiliary focusing method for a space camera. In this method, multiple consecutive remote sensing images captured by the space camera at different focal lengths in different scenarios, along with corresponding camera pixel parameter information and sharpness scores, are used to obtain a remote sensing image that meets a certain level of sharpness. Then, the initial image distance of the space camera is adjusted using the camera pixel parameter information corresponding to the remote sensing image that meets the required sharpness, resulting in the final image distance and thus determining the final focal length of the space camera. This method can adapt to shooting needs under different scenarios and focal lengths, ensuring that the space camera can capture high-quality remote sensing images under various conditions, improving the automation level of remote sensing image processing, and reducing manual intervention and errors. This solves the problems in related technologies, such as the ground setting adjustment rules not being able to cover all possible shooting scenarios and conditions, resulting in untimely or unsatisfactory focus adjustment, and the process of taking pictures first and then analyzing and adjusting them being not only cumbersome and requiring more time and resources, but also subject to certain subjective factors, which can easily affect the accuracy.

[0047] Before introducing the space camera assisted focusing method proposed in the embodiments of this application, we will first explain a camera system for space camera assisted focusing involved in the embodiments of this application.

[0048] Specifically, Figure 1This is a block diagram of a camera system for space camera-assisted focusing according to an embodiment of this application.

[0049] like Figure 1 As shown, the camera system 10 for space camera assisted focusing includes: a satellite management system 101, a camera payload 102, and an intelligent processing unit 103.

[0050] The satellite management system 101 can receive detection information from the intelligent processing unit 103 and adjust and control the various subsystems of the satellite platform according to the detection information. For example, it can control the attitude of the satellite according to the detection information so that the satellite's camera faces a suitable angle. At the same time, it can control the switching on and off of the camera equipment in the camera payload 102 subsystem, as well as adjust the parameter settings of the camera equipment.

[0051] For example, the satellite management system 101 of this application embodiment can record the status parameters corresponding to multiple consecutive remote sensing images captured by the camera payload 102, including camera pixel parameters, etc., which are not specifically limited in this application; it can also send the camera pixel parameter information corresponding to clear remote sensing images with a sharpness score greater than a certain sharpness value to the camera payload 102, etc., which can be set by those skilled in the art according to the actual situation, and are not specifically limited in this application.

[0052] The camera payload 102 may include, but is not limited to, various optical payloads of the satellite, such as infrared cameras, high-resolution cameras, etc. This application does not impose specific limitations.

[0053] Furthermore, in this embodiment of the application, when the camera payload 102 is powered on to capture multiple frames of continuous remote sensing images, it can continuously zoom to capture multiple frames of continuous remote sensing images with continuously changing image distances; in addition, the camera payload 102 in this embodiment of the application receives camera pixel parameters sent by the satellite management system 101 to adjust the initial image distance, and zooms according to the camera pixel parameters to acquire multiple frames of continuous remote sensing images.

[0054] The intelligent processing unit 103, as an intelligent autonomous machine, carries complex image processing algorithms. It receives multiple frames of continuous remote sensing images sent by the camera payload 102 through the data interface, processes the multiple frames of continuous remote sensing images in real time, obtains the detection information of the target or region of interest, and sends the detection information to the satellite management system 101.

[0055] For example, in this application embodiment, the intelligent processing unit 103 can acquire multiple frames of continuous remote sensing images captured by the camera payload 102, process the multiple frames of continuous remote sensing images, and analyze and determine whether the sharpness score of the multiple frames of continuous remote sensing images within the continuous frame time period is greater than a preset sharpness value.

[0056] Additionally, it should be noted that the camera system 10 for space camera-assisted focusing may also include a satellite platform and a power supply subsystem, etc., which are not specifically limited in this application. The satellite platform in this embodiment may further include a telemetry and control subsystem, a power supply subsystem, and attitude control, etc., which are not specifically limited in this application.

[0057] Furthermore, in this embodiment, the satellite management system 101, camera payload 102, and intelligent processing unit 103 can be connected via system lines, such as a CAN (Controller Area Network) bus connection. The specific configuration can be made by those skilled in the art according to the actual situation, and this application does not impose any specific limitations.

[0058] Specifically, Figure 2 This is a flowchart of an auxiliary focusing method for a space camera provided according to an embodiment of this application.

[0059] like Figure 2 As shown, the space camera's assisted focusing method includes the following steps:

[0060] In step S201, multiple consecutive remote sensing images captured by a space camera at different focal lengths in different scenarios are acquired, and camera pixel parameter information corresponding to the multiple consecutive remote sensing images is obtained based on the multiple consecutive remote sensing images.

[0061] It is understood that the different scenarios in the embodiments of this application may include, but are not limited to, scenarios with different terrains such as mountains, oceans, and plains. The specific scenarios can be set by those skilled in the art according to the actual situation, and this application does not impose any specific limitations.

[0062] As one possible implementation, embodiments of this application can acquire multiple consecutive remote sensing images captured by a space camera at different focal lengths in different scenarios, and can also acquire camera pixel parameter information corresponding to multiple consecutive remote sensing images.

[0063] For example, in some embodiments, the embodiments of this application may be carried out in accordance with... Figure 3 The process shown obtains camera pixel parameter information, and its main contents are:

[0064] Step S301: Turn on the camera, take pictures, and continuously adjust the image distance.

[0065] This can be understood as combining Figure 1 In this embodiment of the application, when the space camera is powered on to capture remote sensing images, zoom is achieved by continuously adjusting the image distance, thereby obtaining remote sensing images with continuously changing image distances.

[0066] Step S302: The satellite management system records the camera status parameters when the camera captures the corresponding image frame.

[0067] This can be understood as combining Figure 1 In this embodiment of the application, when using a space camera to capture multiple consecutive remote sensing images, the satellite management system can be used to record the camera pixel parameter information corresponding to the multiple consecutive remote sensing images.

[0068] Additionally, it should be noted that in the embodiments of this application, each frame of remote sensing image captured by the space camera will have corresponding auxiliary data. The relevant parameters recorded during the capture can be recorded in the auxiliary data. The specific settings can be made by those skilled in the art according to the actual situation, and this application does not impose any specific limitations.

[0069] Optionally, in one embodiment of this application, calculating the sharpness score of multiple consecutive remote sensing images includes: obtaining the feature value of at least one image feature in the multiple consecutive remote sensing images; and calculating a first sharpness score of the multiple consecutive remote sensing images by combining the feature weight and feature value of the at least one image feature. The formula for calculating the first sharpness score may be, but is not limited to, the following:

[0070]

[0071] Among them, S t Let be the sharpness score of the t-th frame of the remote sensing image, i and j be the i-th straight line feature and the j-th circular feature in the t-th frame image, respectively, l be the straight line feature, c be the circular feature, m be the number of straight line features, n be the number of circular features, and L be the sharpness score of the t-th frame of the remote sensing image. i C represents the weight values ​​for different straight line characteristics. j These are the weight values ​​for different circular features.

[0072] It is understood that, in the embodiments of this application, image features may include, but are not limited to, circular features, straight line features, etc., and can be specifically set by those skilled in the art according to the actual situation. This application does not impose specific limitations.

[0073] In some embodiments of this application, the calculation of sharpness scores for multiple consecutive remote sensing images may include:

[0074] In this embodiment, feature values ​​of each frame of remote sensing image are extracted, such as straight line feature l or circular feature c, and the number of features of each frame of remote sensing image is calculated, such as the number of straight line features m and the number of circular features n. Different weights, such as L and C, are assigned to different image features. This application does not impose specific limitations, thereby obtaining a first sharpness score value for multiple consecutive frames of remote sensing images. The formula for calculating the first sharpness score value may be, but is not limited to, the following:

[0075]

[0076] Among them, S tLet be the sharpness score of the t-th frame of the remote sensing image, i and j be the i-th straight line feature and the j-th circular feature in the t-th frame image, respectively, l be the straight line feature, c be the circular feature, m be the number of straight line features, n be the number of circular features, and L be the sharpness score of the t-th frame of the remote sensing image. i C represents the weight values ​​for different straight line characteristics. j These are the weight values ​​for different circular features.

[0077] Optionally, in one embodiment of this application, calculating the sharpness score of multiple consecutive remote sensing images includes: acquiring region images of different regions in each consecutive remote sensing image based on the multiple consecutive remote sensing images; and calculating a second sharpness score of the multiple consecutive remote sensing images based on the region weights of different regions and the region images. The formula for calculating the second sharpness score may be, but is not limited to, the following:

[0078]

[0079] Where x is the number of regions in the t-th frame of the remote sensing image, w k Weight values ​​for each region.

[0080] In some embodiments of this application, the calculation of sharpness scores for multiple consecutive remote sensing images may include:

[0081] In this embodiment, different region weights are assigned to different regions of each frame of remote sensing image, dividing each frame of remote sensing image into region images of different regions, such as x regions, with each region having a region weight of w. k This allows us to obtain a second sharpness score for multiple consecutive frames of remote sensing images. The formula for calculating the second sharpness score can be, but is not limited to, the following:

[0082]

[0083] Where x is the number of regions in the t-th frame of the remote sensing image, w k Weight values ​​for each region.

[0084] Optionally, in one embodiment of this application, calculating the sharpness score of multiple consecutive remote sensing images includes: acquiring target features of at least one target in the multiple consecutive remote sensing images; and calculating a third sharpness score of the multiple consecutive remote sensing images based on the target weights and target features of the target features. The formula for calculating the third sharpness score may be, but is not limited to, the following:

[0085]

[0086] Among them, w kLet A be the weight value of the k-th region in the t-th frame of the remote sensing image, B be the target type in the t-th frame of the remote sensing image, and D be the confidence level of the target in the t-th frame of the remote sensing image.

[0087] It is understood that the target features in the embodiments of this application may include, but are not limited to, the type, quantity, weight and confidence level of the target, etc., and this application does not impose specific limitations.

[0088] In some embodiments of this application, the calculation of sharpness scores for multiple consecutive remote sensing images may include:

[0089] In this embodiment, target features of multiple consecutive remote sensing images can be extracted using deep learning methods, and targets in each consecutive remote sensing image can be detected. By calculating the type, quantity, weight, and confidence level of the targets, a third sharpness score of the multiple consecutive remote sensing images is obtained. The formula for calculating the third sharpness score can be, but is not limited to, the following:

[0090]

[0091] Among them, w k Let A be the weight value of the k-th region in the t-th frame of the remote sensing image, B be the target type in the t-th frame of the remote sensing image, and D be the confidence level of the target in the t-th frame of the remote sensing image.

[0092] In step S202, the sharpness score of multiple consecutive remote sensing images is calculated, and remote sensing images that meet the preset sharpness are extracted from the multiple consecutive remote sensing images based on the sharpness score.

[0093] In practical implementation, embodiments of this application can extract remote sensing images that meet a certain level of sharpness based on the sharpness scores of multiple consecutive remote sensing images. This "certain level of sharpness" can be set by those skilled in the art according to actual circumstances, and this application does not impose specific limitations.

[0094] For example, in some embodiments, the embodiments of this application may be carried out in accordance with... Figure 3 The process shown extracts remote sensing images that meet a certain resolution. The main contents are as follows:

[0095] Step S303: The intelligent processing unit acquires continuous image frame data.

[0096] Step S304: Process and analyze the consecutive frame images to obtain the optimal frame number.

[0097] It can be understood that the embodiments of this application can use an intelligent processing unit to process and analyze multiple consecutive frames of remote sensing images, and determine whether the sharpness score of each frame of remote sensing image meets certain sharpness conditions based on the sharpness score value, thereby obtaining a remote sensing image that meets certain sharpness, and taking the corresponding frame number as the best frame number.

[0098] In other words, the method by which the intelligent processing unit in this application determines the best frame number is as follows: by detecting multiple consecutive remote sensing images, and based on the calculated sharpness score of the multiple consecutive remote sensing images, the remote sensing image with the highest relative score is selected as the best frame, thereby obtaining the best frame number.

[0099] Optionally, in one embodiment of this application, calculating the sharpness score of multiple consecutive remote sensing images includes: inputting the multiple consecutive remote sensing images into a pre-trained matching model to obtain the sharpness score of the multiple consecutive remote sensing images.

[0100] It is understood that, in the embodiments of this application, the matching model may include, but is not limited to, models of different terrain patterns such as mountains, oceans, and plains. The specific model can be set by those skilled in the art according to the actual situation, and this application does not impose specific limitations. Furthermore, in the embodiments of this application, the method for training the matching model may be to first collect image datasets of different terrains, classify and label the image datasets respectively, and then use the labeled image datasets to train the matching model respectively. The specific model can be set by those skilled in the art according to the actual situation, and this application does not impose specific limitations.

[0101] Additionally, it should be noted that in the embodiments of this application, the matching model can be a matching model for a specific target, such as a companion star or companion target for a satellite. In this case, the distance between the space camera and the target is only tens to hundreds of meters. Compared with the shooting distance of hundreds of kilometers when shooting ground targets, it is also necessary to adjust the image distance of the space camera to shoot the specific target. The specific settings can be made by those skilled in the art according to the actual situation, and this application does not impose any specific restrictions.

[0102] As one possible approach, embodiments of this application can obtain the sharpness score of multiple consecutive remote sensing images through a pre-trained matching model.

[0103] For example, in some embodiments, the embodiments of this application may be carried out in accordance with... Figure 4 The process shown extracts remote sensing images that meet a certain resolution. The main contents are as follows:

[0104] Step S401: Prepare the matching mode (e.g., terrain modes such as mountains, ocean, plains, etc.).

[0105] It can be understood that the embodiments of this application can be combined withFigure 1 It uses an intelligent processing unit to acquire different scenes captured by a space camera, and then matches them with different matching models.

[0106] Step S402: The camera continuously zooms and captures consecutive frame images.

[0107] It can be understood that the embodiments of this application are combined with Figure 1 By continuously zooming the space camera, multiple frames of continuous remote sensing images can be captured.

[0108] Step S403: The satellite management system records the parameters of consecutive frame images.

[0109] It can be understood that the embodiments of this application are combined with Figure 1 The satellite management system is used to record camera pixel parameter information corresponding to multiple consecutive frames of remote sensing images.

[0110] Step S404: The intelligent processing unit acquires continuous image frames.

[0111] Step S405: Use the matching model to determine the optimal frame number for processing.

[0112] It can be understood that the embodiments of this application utilize an intelligent processing unit to acquire multiple frames of continuous remote sensing images, and compare and match them with the captured multiple frames of continuous remote sensing images through a pre-trained matching model, process the multiple frames of continuous remote sensing images, and then obtain remote sensing images that meet a certain level of clarity, and take the corresponding frame number as the best frame number.

[0113] In step S203, the initial image distance of the space camera is adjusted using the camera pixel parameter information corresponding to the remote sensing image that meets the preset resolution, so as to obtain the final image distance of the space camera, and the final focal length of the space camera is obtained based on the final image distance and different focal lengths.

[0114] As one possible implementation, embodiments of this application can adjust the initial image distance of the space camera based on the camera pixel parameter information of a remote sensing image that meets a certain resolution, thereby obtaining the final image distance, and determining the final focal length of the space camera based on the final image distance.

[0115] For example, such as Figure 3 As shown, the content of adjusting the focal length in the embodiments of this application can be:

[0116] Step S305: Send the best frame number information to the space camera.

[0117] Step S306: Adjust the camera to the image distance corresponding to the optimal frame number.

[0118] It can be understood that, in this application embodiment, the best frame number information obtained by the satellite management system and the camera pixel parameter information corresponding to the best frame number can be sent to the space camera. The space camera receives the camera pixel parameter information sent by the satellite management system, adjusts the initial image distance of the space camera, and obtains the final image distance of the space camera, thereby determining the final focal length of the space camera, and using the final focal length to reacquire multiple frames of continuous remote sensing images.

[0119] The auxiliary focusing method for a space camera proposed in this application will be described below with reference to several embodiments.

[0120] Example 1:

[0121] A schematic diagram illustrating the working principle of an auxiliary focusing method for a space camera provided in this application embodiment is shown below. Figure 3 As shown, the main content will not be elaborated upon here.

[0122] Example 2:

[0123] A schematic diagram illustrating the working principle of another auxiliary focusing method for a space camera provided in this application embodiment is shown below. Figure 4 As shown, the main content will not be elaborated upon here.

[0124] Example 3:

[0125] A schematic diagram illustrating the working principle of another space camera assisted focusing method provided in this application embodiment is shown below. Figure 5 As shown, the main content is as follows:

[0126] Step S501: Start shooting and continuously adjust the image distance.

[0127] This application can be understood as meaning that the embodiments of this application can acquire multiple consecutive remote sensing images captured by a space camera at different focal lengths in different scenarios.

[0128] Step S502: Record the camera state parameters corresponding to the time the camera captures the image.

[0129] This application can be understood as meaning that, during the capture of images by a space camera, the camera pixel parameter information corresponding to multiple consecutive frames of remote sensing images can be recorded.

[0130] Step S503: Acquire and process continuous image frame data.

[0131] It can be understood that the embodiments of this application can calculate the sharpness score of multiple consecutive remote sensing images, and the calculation process is as shown above, which will not be repeated here.

[0132] Step S504: Determine the optimal frame number.

[0133] Step S505: Does the resolution meet the requirements?

[0134] This application embodiment can be understood as follows: based on the sharpness scores of multiple consecutive remote sensing images, the remote sensing image with the highest relative score is selected as the best frame, thereby obtaining the best frame number and a remote sensing image that meets a certain level of sharpness. If the sharpness does not meet the requirements, step S506 is executed; if it does, step S508 is executed.

[0135] Step S506: The camera continuously adjusts the image distance within the range near the predetermined pixel.

[0136] Step S507: Record information such as the image distance value when the camera captures consecutive frame images.

[0137] This can be understood as follows: when the sharpness score of a remote sensing image does not meet a certain sharpness condition, multiple consecutive frames of remote sensing images can be acquired again, and the image distance of the space camera can be adjusted until there is a remote sensing image in the multiple consecutive frames that meets a certain sharpness condition.

[0138] Step S508: Send the best frame number information to the camera payload.

[0139] Step S509: When the camera is adjusted to the optimal frame number, take a picture at the corresponding image distance.

[0140] It can be understood that the embodiments of this application can use the camera pixel parameter information of remote sensing images that meet a certain resolution to adjust the initial image distance of the space camera and obtain the final image distance of the space camera, thereby determining the final focal length of the space camera, and using the final focal length to reacquire multiple consecutive remote sensing images.

[0141] The space camera assisted focusing method proposed in this application can obtain a remote sensing image with a certain level of sharpness by using multiple consecutive remote sensing images captured by the space camera at different focal lengths in different scenarios, the corresponding camera pixel parameter information, and the sharpness score value. Then, the initial image distance of the space camera is adjusted using the camera pixel parameter information corresponding to the remote sensing image with a certain level of sharpness to obtain the final image distance, thereby determining the final focal length of the space camera. This method can adapt to shooting needs under different scenarios and focal lengths, ensuring that the space camera can capture high-quality remote sensing images under different conditions, improving the automation level of remote sensing image processing, and reducing manual intervention and errors. Therefore, it solves the problems in related technologies where ground-based adjustment rules may not cover all possible shooting scenarios and conditions, leading to untimely or unsatisfactory focus adjustment. Furthermore, the process of capturing images first and then analyzing and adjusting them is not only cumbersome and time-consuming, but also subject to subjective factors, making its accuracy susceptible to errors.

[0142] Next, referring to the accompanying drawings, an auxiliary focusing device for a space camera according to an embodiment of this application is described.

[0143] Figure 6 This is a block diagram of an auxiliary focusing device for a space camera provided according to an embodiment of this application.

[0144] like Figure 6 As shown, the auxiliary focusing device 60 of the space camera includes: an acquisition module 601, a calculation module 602, and a generation module 603.

[0145] The acquisition module 601 is used to acquire multiple consecutive remote sensing images captured by a space camera at different focal lengths in different scenarios, and to obtain camera pixel parameter information corresponding to the multiple consecutive remote sensing images based on the multiple consecutive remote sensing images.

[0146] The calculation module 602 is used to calculate the sharpness score of multiple consecutive remote sensing images, and extract remote sensing images that meet the preset sharpness from the multiple consecutive remote sensing images based on the sharpness score.

[0147] The generation module 603 is used to adjust the initial image distance of the space camera using the camera pixel parameter information corresponding to the remote sensing image that meets the preset resolution, so as to obtain the final image distance of the space camera, and obtain the final focal length of the space camera based on the final image distance and different focal lengths.

[0148] Optionally, in one embodiment of this application, the calculation module 302 includes an input unit.

[0149] The input unit is used to input multiple consecutive frames of remote sensing images into a pre-trained matching model to obtain the sharpness score of the multiple consecutive frames of remote sensing images.

[0150] Optionally, in one embodiment of this application, the calculation module 602 includes: a first acquisition unit and a first calculation unit.

[0151] The first acquisition unit is used to acquire the feature value of at least one image feature in multiple consecutive remote sensing images.

[0152] The first calculation unit is used to calculate the first sharpness score of multiple consecutive remote sensing images by combining the feature weights and feature values ​​of at least one image feature.

[0153] Optionally, in one embodiment of this application, the formula for calculating the first sharpness score may be, but is not limited to, the following:

[0154]

[0155] Among them, S tLet be the sharpness score of the t-th frame of the remote sensing image, i and j be the i-th straight line feature and the j-th circular feature in the t-th frame image, respectively, l be the straight line feature, c be the circular feature, m be the number of straight line features, n be the number of circular features, and L be the sharpness score of the t-th frame of the remote sensing image. i C represents the weight values ​​for different straight line characteristics. j These are the weight values ​​for different circular features.

[0156] Optionally, in one embodiment of this application, the calculation module 602 includes: a second acquisition unit and a second calculation unit.

[0157] The second acquisition unit is used to acquire regional images of different regions in each frame of continuous remote sensing images based on multiple frames of continuous remote sensing images.

[0158] The second calculation unit is used to calculate the second sharpness score of multiple consecutive remote sensing images based on the regional weights and regional images of different regions.

[0159] Optionally, in one embodiment of this application, the formula for calculating the second sharpness score may be, but is not limited to, the following:

[0160]

[0161] Where x is the number of regions in the t-th frame of the remote sensing image, w k Weight values ​​for each region.

[0162] Optionally, in one embodiment of this application, the calculation module 602 includes: a third acquisition unit and a third calculation unit.

[0163] The third acquisition unit is used to acquire the target features of at least one target in multiple consecutive remote sensing images.

[0164] The third calculation unit is used to calculate the third sharpness score of multiple consecutive remote sensing images based on the target weight and target features.

[0165] The formula for calculating the third-degree clarity score can be, but is not limited to, the following:

[0166]

[0167] Among them, w k Let A be the weight value of the k-th region in the t-th frame of the remote sensing image, B be the target type in the t-th frame of the remote sensing image, and D be the confidence level of the target in the t-th frame of the remote sensing image.

[0168] It should be noted that the explanation of the aforementioned embodiment of the auxiliary focusing method for a space camera also applies to the auxiliary focusing device for the space camera in this embodiment, and will not be repeated here.

[0169] The auxiliary focusing device for a space camera proposed in this application can obtain a remote sensing image with a certain level of sharpness based on multiple consecutive remote sensing images captured by the space camera at different focal lengths in different scenarios, the corresponding camera pixel parameter information, and the sharpness score. Then, the initial image distance of the space camera is adjusted using the camera pixel parameter information corresponding to the remote sensing image with the required sharpness to obtain the final image distance, thereby determining the final focal length of the space camera. This adapts to the shooting needs of different scenarios and focal lengths, ensuring that the space camera can capture high-quality remote sensing images under different conditions, improving the automation level of remote sensing image processing, and reducing manual intervention and errors. Therefore, it solves the problems in related technologies where ground-based adjustment rules may not cover all possible shooting scenarios and conditions, leading to untimely or unsatisfactory focal length adjustments. Furthermore, the process of capturing images first and then analyzing and adjusting them is not only cumbersome and time-consuming but also subject to subjective factors, making its accuracy susceptible to errors.

[0170] Figure 7 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. The electronic device may include:

[0171] The memory 701, the processor 702, and the computer program stored on the memory 701 and executable on the processor 702.

[0172] When the processor 702 executes the program, it implements the space camera auxiliary focusing method provided in the above embodiments.

[0173] Furthermore, electronic devices also include:

[0174] Communication interface 703 is used for communication between memory 701 and processor 702.

[0175] The memory 701 is used to store computer programs that can run on the processor 702.

[0176] The memory 701 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0177] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0178] Optionally, in a specific implementation, if the memory 701, processor 702, and communication interface 703 are integrated on a single chip, then the memory 701, processor 702, and communication interface 703 can communicate with each other through an internal interface.

[0179] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0180] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described space camera assisted focusing method.

[0181] This application also provides a computer program product, including a computer program that, when executed, implements the above-described space camera assisted focusing method.

[0182] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0183] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0184] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0185] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0186] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0187] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0188] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0189] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method of assisted focusing of a space camera, characterized in that, The method comprises the following steps: obtaining a plurality of continuous remote sensing images captured by a spatial camera in different scenes at different focal lengths, and obtaining camera pixel parameter information corresponding to the plurality of continuous remote sensing images based on the plurality of continuous remote sensing images; calculating a definition score value of the plurality of continuous remote sensing images, and extracting a remote sensing image satisfying a preset definition from the plurality of continuous remote sensing images based on the definition score value; adjusting an initial image distance of the spatial camera using camera pixel parameter information corresponding to the remote sensing image satisfying the preset definition to obtain a final image distance of the spatial camera, and obtaining a final focal length of the spatial camera based on the final image distance and the different focal lengths; wherein the calculation of the definition score value of the plurality of continuous remote sensing images comprises: obtaining a region image of different regions in each continuous remote sensing image based on the plurality of continuous remote sensing images; calculating a second definition score value of the plurality of continuous remote sensing images based on region weights of the different regions and the region images; the calculation formula of the second definition score value is: ， in, For the first Frame sharpness score of remote sensing image and The first The first frame of the image The first straight line feature and the first A circular feature, It has the characteristics of a straight line. It has a circular feature. For linear characteristic quantity, The number of circular features. These are the weight values ​​for different line characteristics. These are the weight values ​​for different circular features. For the first Number of regions in a frame of remote sensing image Weight values ​​for each region.

2. The method of claim 1, wherein, the calculation of the definition score value of the plurality of continuous remote sensing images comprises: inputting the plurality of continuous remote sensing images into a pre-trained matching model to obtain the definition score value of the plurality of continuous remote sensing images.

3. The method of claim 1, wherein, the calculation of the definition score value of the plurality of continuous remote sensing images comprises: obtaining a target feature of at least one target in the plurality of continuous remote sensing images; calculating a third definition score value of the plurality of continuous remote sensing images based on target weights of the target features and the target features; wherein the calculation formula of the third definition score value is: ， wherein, is the frame remote sensing image, weight value of the frame remote sensing image, category of the target in the frame remote sensing image, weight value of the target in the frame remote sensing image, confidence of the target in the frame remote sensing image.

4. An electronic device, comprising: comprise: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the method for assisting focusing of the spatial camera according to any one of claims 1-3.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the method for assisting focusing of the spatial camera according to any one of claims 1-3.

6. A computer program product, characterised in that, The program is executed by the processor to implement the method for assisting focusing of the spatial camera according to any one of claims 1-3.

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