Optical satellite image processing method, device, equipment and medium

Abstract

The present disclosure provides a method for processing optical satellite images, including: using a strict imaging model to calculate virtual control points of the optical satellite images; calculating regularization parameters of the optical satellite images according to the image point coordinates, longitude, latitude and elevation of the virtual control points; calculating regularized coordinates of the virtual control points according to the image point coordinates, longitude, latitude, elevation and regularization parameters of the optical satellite images; constructing a rationalized coefficient error equation by order using the regularized coordinates of the virtual control points and the rationalized coefficients of a rational function model, performing iterative calculations based on the error equation of the rationalized coefficients to update the rationalized coefficients; and establishing a relationship between the image point coordinates of the optical satellite images and the geodetic coordinates of ground points using the rational function model after the rationalized coefficients are updated. The present disclosure also provides an optical satellite image processing device, an electronic device and a storage medium.

Description

Technical Field

[0001] The present disclosure relates to the field of remote sensing image processing, and in particular to a method, device, equipment and medium for processing optical satellite images. Background Art

[0002] The rational function model (RPc model) is a model that uses rational polynomials to establish the relationship between image point coordinates and ground point geodetic coordinates. It is widely used in the field of optical satellite image processing. Due to the large number of parameters in the rational function model, the existing optical satellite image methods based on the rational function model are prone to over-parameterization, which reduces the fitting accuracy of the rational function model and thus affects the accuracy of optical satellite image processing. Summary of the invention

[0003] Based on this, the present disclosure provides, on one hand, a method for processing optical satellite images, including: calculating virtual control points of the optical satellite images using a strict imaging model; calculating regularization parameters of the optical satellite images according to the coordinates, longitude, latitude and elevation of the virtual control points; calculating regularized coordinates of the virtual control points according to the coordinates, longitude, latitude, elevation and regularization parameters of the optical satellite images; constructing rationalized coefficient error equations in stages using the regularized coordinates of the virtual control points and the rationalized coefficients of a rational function model, performing iterative calculations based on the error equations of the rationalized coefficients in stages to update the rationalized coefficients; and establishing a relationship between the image point coordinates of the optical satellite image and the geodetic coordinates of ground points using the rational function model after the rationalized coefficients are updated.

[0004] Optionally, the use of a strict imaging model to calculate the virtual control points of the optical satellite image includes: gridding the optical satellite image in the image row and column directions and in the elevation directions to obtain a plurality of coordinate points; for each coordinate point, constructing the strict imaging model according to the image point coordinates of the coordinate point, the elevation corresponding to the image point, the center position of the GPS antenna corresponding to the coordinate point, and satellite attitude information; intersecting the strict imaging model with the earth model to obtain the coordinates corresponding to the coordinate point on the ground; and combining the image point coordinates of the coordinate point and the corresponding coordinates on the ground to form a virtual control point corresponding to the coordinate point.

[0005] Optionally, the step of constructing a rationalized coefficient error equation in stages using the regularized coordinates of the virtual control point and the rationalized coefficient of the rational function model, and performing iterative calculation based on the rationalized coefficient error equation in stages to update the rationalized coefficient includes: constructing a first-order rationalized coefficient error equation according to the current initial value of the rationalized coefficient of the rational function model and the regularized coordinates of the virtual control point; solving the first-order rationalized coefficient error equation to update the current rationalized coefficient to obtain a first rationalized coefficient; constructing a second-order rationalized coefficient error equation according to the first rationalized coefficient and the regularized coordinates of the virtual control point. The invention relates to a method for obtaining a rational coefficient error equation; solving the second-order rational coefficient error equation to update the first rational coefficient and obtain a second rational coefficient; constructing a third-order rational coefficient error equation according to the second rational parameter and the regularized coordinates of the virtual control point; solving the third-order rational coefficient error equation to update the second rational coefficient and obtain a third rational coefficient; iteratively calculating the third rational coefficient until the fitting residual and mean error of the rational function model calculated according to the updated rational coefficient meet the preset conditions, and taking the rational coefficient at this time as the final rational coefficient.

[0006] Optionally, the process until the fitting residual and mean error of the rational function model calculated according to the updated rationalized coefficients meet preset conditions includes: judging whether the number of iterations reaches the maximum number of iterations, if so, stopping the iterative calculation; or judging whether the change in the maximum fitting residual and mean error between two adjacent iterations is less than a preset threshold, if so, stopping the iterative calculation; or judging whether the maximum fitting residual and mean error are less than a target threshold, if so, stopping the iterative calculation.

[0007] Optionally, the rationalized coefficient error equation is solved using a spectral correction iteration method.

[0008] Optionally, the processing method also includes: calculating a first virtual control point of the optical satellite image as a check point based on half the grid size and the same elevation used in the step of calculating the virtual control points of the optical satellite image using a strict imaging model; calculating the coordinate value of the check point on the optical satellite image using the regularization parameter and the updated rationalization coefficient; calculating the mean square error between the image coordinate values ​​of all the virtual control points and the coordinate value of the check point on the optical satellite image; and judging the fitting accuracy of the rational function model based on the mean square error.

[0009] Optionally, the virtual control points are calculated hierarchically in the elevation direction.

[0010] On the other hand, the present disclosure provides an optical satellite image processing device, including: a first calculation module, used to calculate the virtual control point of the optical satellite image using a strict imaging model; a second calculation module, used to calculate the regularization parameter of the optical satellite image according to the coordinates, longitude, latitude and elevation of the virtual control point; a third calculation module, used to calculate the regularized coordinates of the virtual control point according to the coordinates, longitude, latitude, elevation and the regularization parameter of the optical satellite image; an iterative calculation module, used to construct a rationalized coefficient error equation by order using the regularized coordinates of the virtual control point and the initial value of the rationalized coefficient of the rational function model, and perform iterative calculation based on the error equation of the rationalized coefficient to update the rationalized coefficient; a processing module, used to establish the relationship between the image point coordinates of the optical satellite image and the geodetic coordinates of the ground point by using the rational function model after the rationalized coefficient is updated.

[0011] On the other hand, the present disclosure further provides an electronic device, including: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method.

[0012] Another aspect of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the above-mentioned method. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0014] Figure 1 The flowchart of the optical satellite image processing method provided by the embodiment of the present disclosure is schematically shown.

[0015] Figure 2 The structural block diagram of the optical satellite image processing device provided by an embodiment of the present disclosure is schematically shown.

[0016] Figure 3 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure 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 disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present disclosure.

[0018] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0019] In the present disclosure, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or can communicate with each other; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0020] In the description of the present disclosure, it is necessary to understand that the terms "longitudinal", "length", "circumferential", "front", "rear", "left", "right", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the subsystem or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0021] Throughout the drawings, the same elements are represented by the same or similar reference numerals. Conventional structures or configurations will be omitted when they may cause confusion in the understanding of the present disclosure. The shapes, sizes, and positional relationships of the components in the drawings do not reflect the actual size, proportion, and actual positional relationship. In addition, in the claims, any reference symbol between brackets shall not be construed as a limitation to the claims.

[0022] Similarly, in order to simplify the present disclosure and help understand one or more of the various disclosed aspects, in the above description of the exemplary embodiments of the present disclosure, the various features of the present disclosure are sometimes grouped together into a single embodiment, figure, or description thereof. The description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0023] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the feature. In the description of the present disclosure, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0024] Figure 1 The flowchart of the optical satellite image processing method provided by the embodiment of the present disclosure is schematically shown.

[0025] like Figure 1 As shown, the optical satellite image processing method may include, for example, operations S101 to S105.

[0026] In operation S101 , virtual control points of optical satellite images are calculated using a rigorous imaging model.

[0027] In the disclosed embodiment, a strict imaging model may be used to hierarchically calculate virtual control points in the image domain at a fixed grid size and at a fixed elevation interval in the elevation direction.

[0028] Specifically, first, the input optical satellite image is gridded to obtain multiple coordinate points, which can be divided according to a fixed grid size. Next, for each coordinate point, a strict imaging model is constructed based on the image point coordinates of the coordinate point, the elevation corresponding to the image point, the center position of the GPS antenna corresponding to the coordinate point, and the satellite attitude information. Among them, Lagrange interpolation and polynomial fitting can be used to obtain the center position of the GPS antenna and the satellite attitude information corresponding to the coordinate point, respectively, and leap seconds and other information can be used to calculate the various time systems corresponding to the point, and use this as input to calculate parameters such as precession, nutation, and polar shift, and use the maximum and minimum values ​​of the ground elevation corresponding to the image to obtain several elevation values. Next, the strict imaging model is intersected with the earth model to obtain the coordinates corresponding to the coordinate point on the ground, and the image point coordinates of the coordinate point and the corresponding coordinates on the ground constitute the virtual control point corresponding to the coordinate point.

[0029] In operation S102 , regularization parameters of the optical satellite image are calculated according to the coordinates, longitude, latitude, and elevation of the virtual control point.

[0030] In the embodiment of the present disclosure, the regularization parameter of the optical satellite image can be calculated using formula (1), and formula (1) can be:

[0031]

[0032]

[0033]

[0034]

[0035]

[0036] LineScale=max(|Line max -LineOff|,|Line min -LineOff|)

[0037] SampleScale = max(|Sample max -SampleOff|,|Sample min -SampleOff|)

[0038] LatitudeScale = max(|Latitude max -LatitudeOff|,|Latitude min -LatitudeOff|)

[0039] LongtitudeScale=max(|Longtitude max -LongtitudeOff|,|Longtitude min -LongtitudeOff|)

[0040] HeightScale=max(|Height max -HeightOff|,|Height min -HeightOff|).

[0041] Where Line, Sample, Latitude, Longtitude, and Height are the row, column, latitude, longitude, and elevation of each virtual control point. LineOff, SampleOff, LatitudeOff, LongtitudeOff, HeightOff, LineScale, SampleScale, LatitudeScale, LongtitudeScale, and HeightScale are the regularization parameters corresponding to the row, column, latitude, longitude, and elevation, respectively. n is the number of virtual control points, and the subscripts max and min represent the maximum and minimum values ​​of this type of data.

[0042] In operation S103 , the regularized coordinates of the virtual control point are calculated according to the coordinates, longitude, latitude, elevation, and regularization parameters of the optical satellite image of the virtual control point.

[0043] In the embodiment of the present disclosure, the regularized coordinates of the virtual control point can be calculated using formula (2). Formula (2) can be:

[0044]

[0045]

[0046]

[0047]

[0048]

[0049] Among them, l n ,s n , U n , V n , W n are the regularized coordinates of the virtual control points.

[0050] In operation S104, a rationalized coefficient error equation is constructed by ordering the regularized coordinates of the virtual control points and the rationalized coefficients of the rational function model, and an iterative calculation is performed based on the order-based rationalized coefficient error equation to update the rationalized coefficients.

[0051] In the embodiment of the present disclosure, before constructing the rationalized coefficient error equation in stages, the rational function is deformed using the regularized coordinates calculated above, and the deformed rational function is as shown in formula (3):

[0052] f l =Num L (U, V, W)-l n ·Den L (U, V, W)

[0053] f s =Num S (U, V, W)-s n ·Den S (U, V, W)

[0054] Among them, Num L (U, V, W), Num S (U, V, W), Den L (U, V, W), Den S (U, V, W) is the calculation result of the numerator and denominator obtained by using the current value of the rationalization coefficient (RPC coefficient) and the normalized coordinate value.

[0055] Next, the first-order rationalization coefficient error equation is constructed according to the initial value of the current rationalization coefficient of the rational function model and the regularized coordinates of the virtual control point.

[0056] Specifically, the first-order RPC coefficient error equation can be constructed using formula (4), which can be:

[0057]

[0058]

[0059] Among them, a i , b i , c i , d i They correspond to the row numerator, row denominator, column numerator, and column denominator coefficients in the RPC coefficient respectively; Then it is its corresponding partial derivative.

[0060] Next, the first-order rationalization coefficient error equation is solved to update the current rationalization coefficient and obtain the first rationalization coefficient.

[0061] Next, a second-order rationalized coefficient error equation is constructed according to the first rationalized coefficient and the regularized coordinates of the virtual control point.

[0062] Specifically, the second-order RPC coefficient error equation can be constructed using formula (5), which can be:

[0063]

[0064]

[0065] Next, a second-order rationalization coefficient error equation is solved to update the first rationalization coefficient to obtain a second rationalization coefficient.

[0066] Next, a third-order rationalized coefficient error equation is constructed according to the second rationalized parameter and the regularized coordinates of the virtual control point.

[0067] Specifically, the third-order RPC coefficient error equation can be constructed using formula (6), which can be:

[0068]

[0069]

[0070] Next, the third-order rationalization coefficient error equation is solved to update the second rationalization coefficient to obtain the third rationalization coefficient.

[0071] Next, the third rationalized coefficient updated above is used for iterative calculation until the fitting residual and mean error of the rational function model calculated according to the updated rationalized coefficient meet the preset conditions, and the rationalized coefficient at this time is used as the final rationalized coefficient.

[0072] The formula for iterative calculation can be formula (7):

[0073]

[0074]

[0075] Among them, the spectral correction iteration method can be used to solve the rationalized coefficient error equation to update the RPC coefficient.

[0076] In the disclosed embodiment, the RPC fitting residual and mean error are calculated using the updated RPC coefficients. If one of the termination conditions is met, the iteration is exited to obtain the result or report an exception, otherwise the iterative calculation is repeated. The judgment condition may include: judging whether the number of iterations reaches the maximum number of iterations, if so, stopping the iterative calculation. Or, judging whether the change in the maximum fitting residual and mean error between two adjacent iterations is less than a preset threshold, if so, stopping the iterative calculation. Or, judging whether the maximum fitting residual and mean error are less than a target threshold, if so, stopping the iterative calculation.

[0077] In operation S105, the relationship between the image point coordinates of the optical satellite image and the geodetic coordinates of the ground point is established using the rational function model with updated rationalized coefficients.

[0078] In another embodiment of the present disclosure, the method for processing optical satellite images may further include, for example, determining the fitting accuracy of a rational function model.

[0079] Specifically, based on half of the grid size and the same elevation used in the step of calculating the virtual control points of the optical satellite image using the strict imaging model, a first virtual control point of the optical satellite image is calculated as a check point. The coordinate value of the check point on the optical satellite image is calculated using the regularization parameter and the updated rationalization coefficient. The mean error between the image coordinate values ​​of all virtual control points and the coordinate value of the check point on the optical satellite image is calculated. The fitting accuracy of the rational function model is determined according to the mean error.

[0080] According to the method for processing optical satellite images provided by the embodiments of the present disclosure, since the regularization parameters of the optical satellite images and the regularization coordinates of the virtual control points are calculated based on the virtual control points, the rationalization coefficients of the rational function model are decomposed, iteratively settled and updated according to the regularization parameters and the regularization coordinates, so as to obtain the rationalization coefficients with better structure, so as to improve the fitting accuracy of the rational function model, thereby improving the processing accuracy of the optical satellite images.

[0081] Figure 2 The structural block diagram of the optical satellite image processing device provided by an embodiment of the present disclosure is schematically shown.

[0082] like Figure 2As shown, the optical satellite image processing device 200 may include, for example, a first calculation module 210 , a second calculation module 220 , a third calculation module 230 , an iterative calculation module 240 and a processing module 250 .

[0083] The first calculation module 210 is used to calculate virtual control points of optical satellite images using a strict imaging model.

[0084] The second calculation module 220 is used to calculate the regularization parameters of the optical satellite image according to the coordinates, longitude, latitude and elevation of the virtual control point.

[0085] The third calculation module 230 is used to calculate the regularized coordinates of the virtual control point according to the coordinates, longitude, latitude, elevation and regularization parameters of the optical satellite image of the virtual control point.

[0086] The iterative calculation module 240 is used to construct a rationalized coefficient error equation by order using the regularized coordinates of the virtual control points and the rationalized coefficients of the rational function model, and perform iterative calculation based on the rationalized coefficient error equation to update the rationalized coefficients.

[0087] The processing module 250 is used to establish the relationship between the image point coordinates of the optical satellite image and the geodetic coordinates of the ground point by using the rational function model with updated rationalized coefficients.

[0088] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in 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, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0089] For example, any of the first computing module 210, the second computing module 220, the third computing module 230, the iterative computing module 240, and the processing module 250 can be combined in one module / unit / subunit for implementation, or any of the modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functions of one or more of these modules / units / subunits can be combined with at least part of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to an embodiment of the present disclosure, at least one of the first computing module 210, the second computing module 220, the third computing module 230, the iterative computing module 240, and the processing module 250 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 by any one of the three implementation methods of software, hardware, and firmware, or by a suitable combination of any of them. Alternatively, at least one of the first calculation module 210, the second calculation module 220, the third calculation module 230, the iterative calculation module 240 and the processing module 250 may be at least partially implemented as a computer program module, which may perform corresponding functions when executed.

[0090] It should be noted that the signal processing device part in the embodiment of the present disclosure corresponds to the signal processing method part in the embodiment of the present disclosure, and their specific implementation details are also the same, which will not be repeated here.

[0091] Figure 3 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0092] like Figure 3As shown, the electronic device 300 according to an embodiment of the present disclosure includes a processor 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage part 303 to a random access memory (RAM) 303. The processor 301 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 301 may also include an onboard memory for caching purposes. The processor 301 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 disclosure.

[0093] In RAM 303, various programs and data required for the operation of electronic device 300 are stored. Processor 301, ROM 302 and RAM 303 are connected to each other through bus 304. Processor 301 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 302 and / or RAM 303. It should be noted that the program can also be stored in one or more memories other than ROM 302 and RAM 303. Processor 301 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0094] According to an embodiment of the present disclosure, the electronic device 300 may further include an input / output (I / O) interface 305, which is also connected to the bus 304. The electronic device 300 may further include one or more of the following components connected to the I / O interface 305: an input portion 306 including a keyboard, a mouse, etc.; an output portion 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 308 including a hard disk, etc.; and a communication portion 309 including a network interface card such as a LAN card, a modem, etc. The communication portion 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage portion 308 as needed.

[0095] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the processor 301, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0096] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; 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 disclosure is implemented.

[0097] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it 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 disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0098] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 302 and / or the RAM 303 described above and / or one or more memories other than the ROM 302 and the RAM 303 .

[0099] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that 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 flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

Claims

1. A method for processing optical satellite images, comprising: calculating virtual control points of the optical satellite image using a rigorous imaging model; Calculating regularization parameters of the optical satellite image according to the image point coordinates, longitude, latitude and elevation of the virtual control point; Calculating the regularized coordinates of the virtual control point according to the coordinates, longitude, latitude, elevation of the virtual control point and the regularization parameters of the optical satellite image; Using the regularized coordinates of the virtual control point and the initial values ​​of the rationalized coefficients of the rational function model, a rationalized coefficient error equation is constructed in stages, and an iterative calculation is performed based on the staged rationalized coefficient error equation to update the rationalized coefficient; Using the rational function model with updated rationalized coefficients, the relationship between the image point coordinates of the optical satellite image and the geodetic coordinates of the ground point is established; The step of constructing a rationalized coefficient error equation by using the regularized coordinates of the virtual control point and the rationalized coefficient of the rational function model in order, and performing iterative calculation based on the rationalized coefficient error equation in order to update the rationalized coefficient includes: Constructing a first-order rationalization coefficient error equation according to the initial value of the current rationalization coefficient of the rational function model and the regularized coordinates of the virtual control point; Solving the first-order rationalization coefficient error equation to update the current rationalization coefficient and obtain a first rationalization coefficient; Constructing a second-order rationalized coefficient error equation according to the first rationalized coefficient and the regularized coordinates of the virtual control point; Solving the second-order rationalization coefficient error equation to update the first rationalization coefficient to obtain a second rationalization coefficient; Constructing a third-order rationalized coefficient error equation according to the second rationalized parameter and the regularized coordinates of the virtual control point; Solving the third-order rationalization coefficient error equation to update the second rationalization coefficient to obtain a third rationalization coefficient; Iterative calculation is performed with the third rationalized coefficient until the fitting residual and mean error of the rational function model calculated according to the updated rationalized coefficient meet preset conditions, and the rationalized coefficient at this time is used as the final rationalized coefficient.

2. The optical satellite image processing method according to claim 1, wherein: The method of calculating the virtual control points of the optical satellite image using a strict imaging model includes: Gridding the optical satellite image in the image row and column direction and the elevation direction to obtain a plurality of coordinate points; For each coordinate point, the strict imaging model is constructed according to the image point coordinates of the coordinate point, the elevation corresponding to the image point, the center position of the GPS antenna corresponding to the coordinate point, the satellite attitude, precession, nutation, polar motion and leap second; Intersecting the strict imaging model with the earth model to obtain the coordinates corresponding to the coordinate points on the ground; The image point coordinates of the coordinate point and the corresponding coordinates on the ground constitute a virtual control point corresponding to the coordinate point.

3. The optical satellite image processing method according to claim 1, wherein: The step of calculating the fitting residual and mean error of the rational function model calculated according to the updated rationalized coefficients until they meet the preset conditions includes: Determine whether the number of iterations reaches the maximum number of iterations. If so, stop the iterative calculation; or; Determine whether the changes in the maximum fitting residual and mean error between two adjacent iterations are less than a preset threshold, if so, stop the iterative calculation; or; Determine whether the maximum fitting residual and the mean error are less than the target threshold. If so, stop the iterative calculation.

4. The optical satellite image processing method according to claim 1, wherein: The rationalized coefficient error equation is solved using a spectral correction iterative method.

5. The optical satellite image processing method according to claim 1, further comprising: Calculating a first virtual control point of the optical satellite image as a check point based on half the grid size and the same elevation used in the step of calculating the virtual control point of the optical satellite image using the strict imaging model; Calculating the coordinate value of the check point on the optical satellite image using the regularization parameter and the updated rationalization coefficient; Calculating mean square errors between the image coordinate values ​​of all the virtual control points and the coordinate values ​​of the check points on the optical satellite image; The fitting accuracy of the rational function model is determined according to the mean square error.

6. The optical satellite image processing method according to claim 1 or 5, wherein: The virtual control points are calculated hierarchically in the elevation direction.

7. An optical satellite image processing device, comprising: A first calculation module, used for calculating virtual control points of the optical satellite image using a strict imaging model; a second calculation module, for calculating the regularization parameters of the optical satellite image according to the coordinates, longitude, latitude and elevation of the virtual control point; a third calculation module, configured to calculate the regularized coordinates of the virtual control point according to the coordinates, longitude, latitude, elevation of the virtual control point and the regularization parameters of the optical satellite image; An iterative calculation module, used to construct a rationalized coefficient error equation by order using the regularized coordinates of the virtual control point and the initial values ​​of the rationalized coefficients of the rational function model, and to perform iterative calculation based on the order-based rationalized coefficient error equation to update the rationalized coefficients; Wherein, a first-order rationalized coefficient error equation is constructed according to the initial value of the current rationalized coefficient of the rational function model and the regularized coordinates of the virtual control point; Solving the first-order rationalization coefficient error equation to update the current rationalization coefficient and obtain a first rationalization coefficient; Constructing a second-order rationalized coefficient error equation according to the first rationalized coefficient and the regularized coordinates of the virtual control point; Solving the second-order rationalization coefficient error equation to update the first rationalization coefficient to obtain a second rationalization coefficient; Constructing a third-order rationalized coefficient error equation according to the second rationalized parameter and the regularized coordinates of the virtual control point; Solving the third-order rationalization coefficient error equation to update the second rationalization coefficient to obtain a third rationalization coefficient; Iterative calculation is performed using the third rationalization coefficient until the fitting residual and mean error of the rational function model calculated according to the updated rationalization coefficient meet the preset conditions, and the rationalization coefficient at this time is used as the final rationalization coefficient; The processing module is used to establish the relationship between the image point coordinates of the optical satellite image and the geodetic coordinates of the ground point by using the rational function model after updating the rationalized coefficients.

8. An electronic device comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method according to any one of claims 1 to 6.

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