Block adjustment method and device suitable for multi-source remote sensing image

Abstract

The invention provides a block adjustment method and device for a multi-source remote sensing image, and solves the problem that the splicing precision and efficiency of the multi-source remote sensing image in a large area are low. All panchromatic images and a multispectral image corresponding to each panchromatic image are distinguished from the image data set, and connection points of the panchromatic images are extracted; carrying out connection point matching among all panchromatic images; performing connection point matching between the panchromatic image and the corresponding multispectral image; performing control point matching on all panchromatic images and a satellite remote sensing orthographic reference image; obtaining object space coordinates of each matching point; based on the object space coordinates of the connection points and the RPC parameters of the images corresponding to the connection points, resection is carried out, and error points and error images are removed; joint adjustment is carried out on the connection points and the control points, and transformation parameters and object space coordinates of the connection points of each image are calculated; and according to the object space plane coordinates after the connection points are corrected, obtaining the elevation based on the DEM, comparing the obtained elevation with the original elevation, and if the obtained elevation value does not change, correcting the original RPC parameter file.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-source remote sensing image processing, and in particular to a block adjustment method and device suitable for multi-source remote sensing images. Background Art

[0002] In processing multi-source remote sensing images over large areas, traditional stitching techniques typically involve matching tie points between multiple spectral images and matching overlapping areas between multispectral and panchromatic images. This results in excessive tie point matching. This excessive matching increases the data processing workload and affects processing results, leading to low stitching accuracy and efficiency. Summary of the Invention

[0003] In view of this, an embodiment of the present invention provides a regional block adjustment method and device applicable to multi-source remote sensing images, which solves the problems of low precision and efficiency in stitching multi-source remote sensing images of large areas.

[0004] In a first aspect, the present invention provides a block adjustment method applicable to multi-source remote sensing images, comprising: Step 01: Identify all panchromatic images from a multi-source remote sensing image dataset and extract tie points from the panchromatic images; Step 02: performing tie point matching between all the panchromatic images; Step 03: Identify the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image dataset, and perform tie point matching between the panchromatic image and the corresponding multispectral image; Step 04: Match control points of all the panchromatic images with the satellite remote sensing orthophoto reference images; Step 05: Obtain the object coordinates of each matching point based on the connection points, control points and DEM data; Step 06: Based on the object coordinates of the tie points and the RPC parameters of their corresponding images, perform a resection to eliminate error points and error images. Step 07: tie point and control point are carried out joint adjustment, wherein, tie point only revise object space plane coordinate, and control point does not revise object space coordinate, and iteration ends, and according to the transformation parameter of every scene image, eliminates error tie point and error control point; Step 08: Obtain the elevation based on the DEM according to the corrected object plane coordinates of the connection points, compare the obtained elevation with the original elevation, and determine whether the obtained elevation value has changed to determine whether the elevation needs to be corrected. If the obtained elevation value has not changed, there is no need to correct the elevation, and then correct the original RPC parameter file.

[0005] In one embodiment, the step of comparing the obtained elevation with the original elevation to determine whether the obtained elevation value has changed further includes: if the obtained elevation value has changed, correcting the elevation value of the matching point and repeating steps 07-08 until the elevation value has not changed.

[0006] In one embodiment, the performing of rear intersection based on the object coordinates of the connection points and the RPC parameters of their corresponding images and eliminating error points and error images includes: performing rear intersection based on the object coordinates of the connection points and the RPC parameters of their corresponding images, eliminating error connection points according to an image-side error threshold coefficient, and then counting the connection point errors on each image to eliminate error images greater than the coefficient threshold.

[0007] In one embodiment, it further includes: obtaining affine transformation parameters of each image based on the connection points and the control points; and the correcting the original RPC parameter file includes: correcting the RPC parameters of the multi-source remote sensing image based on the affine transformation parameters.

[0008] In one embodiment, the method includes: jointly adjusting the tie points and the control points to obtain the affine transformation parameters of each image and the object space coordinates of each tie point.

[0009] In a second aspect, the present invention provides a block adjustment device suitable for multi-source remote sensing images, comprising: The discrimination and extraction module is used to discriminate all panchromatic images from the multi-source remote sensing image data set and extract connection points from the panchromatic images; discriminate the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image data set; A matching module is used to match tie points between all the panchromatic images; match tie points between the panchromatic images and the corresponding multispectral images; and match control points between all the panchromatic images and the satellite remote sensing orthophoto reference images; A data processing module is configured to obtain the object coordinates of each matching point based on the tie points, control points, and DEM data; perform a rear intersection based on the object coordinates of the tie points and the RPC parameters of their corresponding images to eliminate error points and error images; perform a joint adjustment on the tie points and the control points, wherein the tie points only correct the object coordinates, while the control points do not correct the object coordinates. After the iteration is completed, the error tie points and error control points are eliminated based on the transformation parameters of each image; and obtain elevations based on the DEM according to the object coordinates of the tie points after correction. The judgment module is used to compare the obtained elevation with the original elevation to determine whether the obtained elevation value has changed, so as to determine whether the elevation needs to be corrected; Fitting correction module, used to correct the original RPC parameter file.

[0010] In a third aspect, the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any one of the above methods.

[0011] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when executed by a processor.

[0012] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which implements the steps of any of the above methods when executed by a processor.

[0013] The embodiment of the present invention provides a regional block adjustment method and device suitable for multi-source remote sensing images, which distinguishes all panchromatic images from a multi-source remote sensing image dataset and extracts tie points from the panchromatic images; performs tie point matching between all the panchromatic images; distinguishes the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image dataset, and performs tie point matching between the panchromatic image and the corresponding multispectral image; performs control point matching on all the panchromatic images and a satellite remote sensing orthophoto reference image; obtains the object coordinates of each matching point based on the tie points, control points and DEM data; and obtains the object coordinates of each matching point based on the tie points. The object coordinates and the RPC parameters of their corresponding images are intersected to eliminate error points and error images; the connection points and control points are jointly adjusted, wherein the connection points only correct the object plane coordinates, and the control points do not correct the object coordinates. The iteration ends and, according to the transformation parameters of each scene image, the error connection points and error control points are eliminated; based on the object plane coordinates after the connection points are corrected, the elevation is obtained based on the DEM, the obtained elevation is compared with the original elevation, and it is judged whether the obtained elevation value has changed to judge whether it is necessary to correct the elevation. If the obtained elevation value has not changed, there is no need to correct the elevation, then the original RPC parameter file is corrected. The present invention is applicable to the splicing of optical remote sensing areas of large areas, and the splicing effect and precision are improved by the above-mentioned technical means, thereby improving splicing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 FIG2 is a flow chart of a block adjustment method for multi-source remote sensing images provided by an embodiment of the present invention.

[0015] Figure 2 FIG2 is a schematic structural diagram of a block adjustment device for multi-source remote sensing images provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0017] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0018] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0019] In one embodiment of the present invention, a block adjustment method for multi-source remote sensing images is provided. Multi-source remote sensing images refer to a collection of multiple remote sensing image data acquired through different sensors, different platforms, or different technical means. The core of this method is "multi-source", that is, the diversity of data sources. It aims to provide more comprehensive and accurate surface information by integrating image data with different characteristics. Figure 1 As shown in FIG, the matching method of the multi-source remote sensing image includes: Step 01: Identify all panchromatic images from a multi-source remote sensing image dataset and extract tie points from the panchromatic images.

[0020] Panchromatic images (PAN) are high-resolution black-and-white images captured by a single sensor channel (wideband). Their key characteristic is that they cover a wide electromagnetic range (typically from visible light to near-infrared) while generating only a single grayscale band. This provides high spatial resolution but lacks spectral information, resulting in high clarity.

[0021] Specifically, panchromatic images usually have higher spatial resolution, can capture finer edge and texture features of objects, and are more suitable for extracting stable connection points.

[0022] Step 02: Perform tie point matching between all the panchromatic images.

[0023] Optionally, techniques such as geometric positioning and feature matching are used to match the connection points of different panchromatic images.

[0024] Step 03: Identify the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image dataset, and perform tie point matching between the panchromatic image and the corresponding multispectral image.

[0025] Specifically, a satellite has a panchromatic payload and a multispectral payload, and the images taken by the two payloads on the satellite have a corresponding relationship. This step only matches the corresponding multispectral images instead of matching all overlapping areas.

[0026] Furthermore, the panchromatic image has a high resolution, while the multispectral image has a low resolution. By aligning the multispectral image to the panchromatic image, as long as the panchromatic images are registered with each other, the multispectral images are indirectly registered, which reduces the complexity of registration and adjustment and results in higher accuracy.

[0027] Step 04: Match the control points of all the panchromatic images with the satellite remote sensing orthophoto reference images.

[0028] Among them, satellite remote sensing orthophoto reference images are Digital Orthophoto Map (DOM) reference images. These are high-precision remote sensing images that have undergone geometric correction (orthorectification). They have a unified map coordinate system (such as UTM / WGS84) and eliminate geometric distortion caused by terrain undulation and sensor attitude. In multi-source remote sensing image processing, DOM reference images are often used as geometric benchmarks or control benchmarks to assist in the geometric correction, stitching, and accuracy verification of other images.

[0029] Since the resolution of multispectral images is relatively low, if tie point matching is also performed between multispectral images, it will inevitably lead to increased errors in the regional block adjustment results. Therefore, the present invention only matches the tie points of the multispectral and corresponding panchromatic scenes, directly eliminating the subsequent multispectral and panchromatic registration steps, thereby increasing efficiency and improving accuracy.

[0030] Furthermore, after step 04, the method further includes: obtaining the matching connection point error, determining whether the error is greater than an error threshold, and if so, deleting the corresponding matching point. Specifically, the reprojection error between the matching connection points is obtained through front intersection and back intersection.

[0031] Step 05: Obtain the object coordinates of each matching point based on the tie points, control points, and DEM data. Optionally, the object coordinates are three-dimensional coordinates. The tie points and control points are jointly adjusted to obtain the affine transformation parameters for each image and the object plane coordinates X and Y of each matching point. The prior art also includes matching tie points between multiple spectra and matching overlapping regions between multiple spectra and panchromatic images. However, the present invention eliminates these matching steps, thereby reducing the amount of data and improving matching efficiency.

[0032] Step 06: Based on the object coordinates of the tie points and the RPC parameters of their corresponding images, perform a resection to eliminate error points and error images. Step 07: Jointly adjust the tie points and control points. The tie points only correct the object plane coordinates, while the control points do not correct the object plane coordinates. The iteration ends and the error tie points and error control points are eliminated according to the transformation parameters of each image.

[0033] Specifically, based on the object-space coordinates of the tie points and the RPC parameters of their corresponding images, a rear intersection is performed, and the error tie points are eliminated according to the image-space error threshold coefficient. Then, the tie point errors on each image are counted, and the error images with errors greater than the coefficient threshold are eliminated.

[0034] Step 08: Obtain the elevation based on the DEM according to the corrected object plane coordinates of the connection points, compare the obtained elevation with the original elevation, and determine whether the obtained elevation value has changed to determine whether the elevation needs to be corrected. If the obtained elevation value has not changed, there is no need to correct the elevation, and then correct the original RPC parameter file.

[0035] After one iteration, the elevation of each matching point is obtained using the object plane coordinates X and Y based on the digital elevation model. The obtained elevation of the matching point is compared with the elevation of the original point to determine whether the elevation value has changed. If the elevation value has not changed, the iteration is terminated and the RPC parameters of the multi-source remote sensing image are refitted and corrected. If the elevation value has changed, the elevation value of the matching point is corrected and steps 07 to 08 are repeated until the elevation value has not changed.

[0036] Specifically, the method provided by the present invention further includes obtaining affine transformation parameters for each image scene based on the tie points and the control points; and jointly adjusting the tie points and control points to obtain the affine transformation parameters for each image scene and the object plane coordinates of each matching point. Furthermore, refitting and correcting the RPC parameters of the multi-source remote sensing imagery includes correcting the RPC parameters of the multi-source remote sensing imagery based on the affine transformation parameters. RPC parameters (Rational Polynomial Coefficients) are a sensor-independent, universal geometric model commonly used in remote sensing image geometric positioning. They are used to establish a mathematical relationship between image pixel coordinates (row and column numbers) and geographic coordinates (latitude, longitude, and elevation). Their core feature is that they approximate complex sensor imaging geometry through rational functions, replacing traditional, rigorous physical models (such as collinearity equations).

[0037] The method provided in this embodiment eliminates the need for multispectral matching and adjustment and subsequent panchromatic and multispectral registration steps, thereby improving efficiency and accuracy.

[0038] In one embodiment of the present invention, a block adjustment device 100 suitable for multi-source remote sensing images is provided. Figure 2 As shown, the block adjustment device 100 for multi-source remote sensing images includes a discrimination and extraction module 10, a matching module 20, a data processing module 30, a judgment module 40, and a fitting and correction module 50. The functions of each module are as follows.

[0039] The discrimination and extraction module 10 is used to discriminate all panchromatic images from the multi-source remote sensing image data set and extract connection points from the panchromatic images; discriminate the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image data set; The matching module 20 is used to perform tie point matching between all the panchromatic images; perform tie point matching between the panchromatic images and the corresponding multispectral images; and perform control point matching between all the panchromatic images and the satellite remote sensing orthophoto reference images. The data processing module 30 is configured to obtain the object coordinates of each matching point based on the tie points, control points, and DEM data; perform a resection based on the object coordinates of the tie points and the RPC parameters of their corresponding images to eliminate erroneous points and erroneous images; perform a joint adjustment on the tie points and the control points, wherein the tie points only correct the object coordinates, while the control points do not correct the object coordinates. Upon completion of the iteration, erroneous tie points and erroneous control points are eliminated based on the transformation parameters of each image; and obtain elevations based on the DEM using the corrected object coordinates of the tie points. The judgment module 40 is used to compare the acquired elevation with the original elevation to determine whether the acquired elevation value has changed to determine whether the elevation needs to be corrected; The fitting and correction module 50 is used to refit and correct the RPC parameters of the multi-source remote sensing images.

[0040] Furthermore, when the judgment module 40 determines that the elevation value has not changed, the fitting correction module 50 refits and corrects the RPC parameters of the multi-source remote sensing image. When the judgment module 40 determines that the elevation value has changed, the fitting correction module 50 corrects the elevation value of the matching point, and then the data processing module 30, the judgment module 40 and the fitting correction module 50 repeatedly perform a joint adjustment of the connection points and the control points, wherein the connection points only correct the object plane coordinates, and the control points do not correct the object coordinates. The iteration ends, and according to the transformation parameters of each scene image, the error connection points and error control points are eliminated, and the elevation is obtained based on the object plane coordinates after the connection points are corrected based on the DEM. The obtained elevation is compared with the original elevation to determine whether the obtained elevation value has changed, so as to determine whether the elevation needs to be corrected, until the elevation value does not change.

[0041] Furthermore, the data processing module 30 is also used to perform rear intersection based on the object space coordinates of the connection points and the RPC parameters of their corresponding images, eliminate erroneous connection points according to the image space error threshold coefficient, and then count the connection point errors on each image to eliminate erroneous images greater than the coefficient threshold.

[0042] Furthermore, the data processing module 30 is further configured to obtain affine transformation parameters of each image based on the connection points and the control points; and the fitting correction module 50 is further configured to correct the RPC parameters of the multi-source remote sensing image based on the affine transformation parameters.

[0043] Furthermore, the data processing module 30 is also used to perform joint adjustment on the tie points and the control points to obtain the affine transformation parameters of each image and the object plane coordinates of each matching point.

[0044] The block adjustment device 100 for multi-source remote sensing images provided in this embodiment is suitable for stitching images of large areas to improve the stitching effect.

[0045] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0046] In some implementations of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.

[0047] In some implementations of this embodiment, a computer program product is provided, including a computer program / instruction, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.

[0048] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components to execute the methods in the above embodiments.

[0049] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof. The computer-readable storage medium may include, but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (such as hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0050] The computer-readable storage medium may also store at least one computer-executable program / instruction, such as a computer-readable instruction. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0051] In addition, the computer device may also include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.).

[0052] The processor can communicate with external devices via an I / O bus via a wired or wireless network.

[0053] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0054] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a portion of code, and the above-mentioned module, program segment or a portion of code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes 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 and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0055] It should be noted that, in this disclosure, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element limited by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0056] Although the embodiments disclosed in this disclosure are as described above, the above contents are merely embodiments adopted to facilitate understanding of the disclosure and are not intended to limit the disclosure. Any person skilled in the art of the disclosure may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope of the disclosure. However, the scope of patent protection of the disclosure shall still be based on the scope defined by the attached claims.

Claims

1. A block adjustment method suitable for multi-source remote sensing images, characterized in that: include: Step 01: Identify all panchromatic images from a multi-source remote sensing image dataset and extract tie points from the panchromatic images; Step 02: performing tie point matching between all the panchromatic images; Step 03: Identify the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image dataset, and perform tie point matching between the panchromatic image and the corresponding multispectral image; Step 04: Match control points of all the panchromatic images with the satellite remote sensing orthophoto reference images; Step 05: Obtain the object coordinates of each matching point based on the connection points, control points and DEM data; Step 06: Based on the object coordinates of the tie points and the RPC parameters of their corresponding images, perform a resection to eliminate error points and error images. Step 07: tie point and control point are carried out joint adjustment, wherein, tie point only revise object space plane coordinate, and control point does not revise object space coordinate, and iteration ends, and according to the transformation parameter of every scene image, eliminates error tie point and error control point; Step 08: Obtain the elevation based on the DEM according to the corrected object plane coordinates of the connection points, compare the obtained elevation with the original elevation, and determine whether the obtained elevation value has changed. If the obtained elevation value has not changed, there is no need to correct the elevation value, and correct the original RPC parameter file.

2. the block adjustment method applicable to multi-source remote sensing images according to claim 1, is characterized in that, The step of comparing the acquired elevation with the original elevation to determine whether the acquired elevation value has changed further includes: if the acquired elevation value has changed, correcting the elevation value and repeating steps 07 to 08 until the elevation value does not change.

3. the block adjustment method that is applicable to multi-source remote sensing image according to claim 1, is characterized in that, Based on the object coordinates of the connection points and the RPC parameters of their corresponding images, resection is performed to eliminate error points and error images, including: Based on the object-space coordinates of the tie points and the RPC parameters of their corresponding images, a rear intersection is performed, and the error tie points are eliminated according to the image-space error threshold coefficient. Then, the tie point errors on each image are counted, and the error images with errors greater than the coefficient threshold are eliminated.

4. the block adjustment method that is applicable to multi-source remote sensing image according to claim 1, is characterized in that, Also includes: Obtaining affine transformation parameters of each image based on the connection points and the control points; The correcting the original RPC parameter file includes correcting the RPC parameters of the multi-source remote sensing image based on the affine transformation parameters.

5. the block adjustment method that is applicable to multi-source remote sensing image according to claim 4, is characterized in that, include: The tie points and control points are jointly adjusted to obtain the affine transformation parameters of each image and the object plane coordinates of each tie point.

6. A block adjustment device suitable for multi-source remote sensing images, characterized in that: include: The discrimination and extraction module is used to discriminate all panchromatic images from the multi-source remote sensing image data set and extract connection points from the panchromatic images; discriminate the multispectral image of the scene corresponding to each panchromatic image from the multi-source remote sensing image data set; A matching module is used to match tie points between all the panchromatic images; match tie points between the panchromatic images and the corresponding multispectral images; and match control points between all the panchromatic images and the satellite remote sensing orthophoto reference images; A data processing module is configured to obtain the object coordinates of each matching point based on the tie points, control points, and DEM data; perform a rear intersection based on the object coordinates of the tie points and the RPC parameters of their corresponding images to eliminate error points and error images; perform a joint adjustment on the tie points and the control points, wherein the tie points only correct the object coordinates, while the control points do not correct the object coordinates. After the iteration is completed, the error tie points and error control points are eliminated based on the transformation parameters of each image; and obtain elevations based on the DEM according to the object coordinates of the tie points after correction. The judgment module is used to compare the obtained elevation with the original elevation to determine whether the obtained elevation value has changed, so as to determine whether the elevation needs to be corrected; Fitting correction module, used to correct the original RPC parameter file.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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