CN115311363B - High-resolution satellite image assistance-based footprint camera orientation method and system - Google Patents
High-resolution satellite image assistance-based footprint camera orientation method and system Download PDFInfo
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Abstract
The invention discloses a high-resolution satellite image-based footprint camera orientation method and system, wherein the method comprises the following steps: extracting orientation points from the footprint camera image; determining the ground point coordinates of the orientation points under the assistance of the high-score satellite images; and solving the orientation parameters of the footprint camera by utilizing the orientation points on the footprint camera image and the ground point coordinates of the orientation points. The multispectral image and the footprint camera image are used for spectral matching, and the radiation difference between the images is reduced; simulating the images of the footprint camera by using the imaging geometric model, and eliminating geometric deformation among the images; then, realizing high-precision matching of the footprint camera image and the multispectral image by using a high-precision geometric matching method, and finally establishing a corresponding relation between the panchromatic image and the footprint camera image; and then, acquiring ground point coordinates of the orientation points by using an optimization model and a digital surface model of the high-resolution satellite panchromatic image, using the ground point coordinates as control points, and then realizing high-precision orientation of the footprint camera by using the control points.
Description
Technical Field
The invention belongs to the technical field of satellite image processing, and particularly relates to a high-resolution satellite image-assistance-based footprint camera orientation method and system during ground observation by combining a linear array camera and an area array camera.
Background
The laser footprint camera is used for recording footprint points of laser spots during imaging and is adopted by a high-resolution seven-grade satellite. In order to acquire three-dimensional image data, the high-resolution seven-numbered satellite is simultaneously provided with two high-resolution push-broom cameras which respectively form an included angle of 21 degrees and an included angle of-5 degrees with the downward viewing direction. The carried rear-view camera can simultaneously obtain a panchromatic image with high resolution and a multispectral image with lower resolution. In order to obtain high-precision elevation information, the high-resolution seven-model satellite is also provided with two lasers, and a laser emergent light path is recorded by using a footprint camera. The realization of the high-precision corresponding relation between the footprint camera image and the high-resolution satellite image is a key factor for determining the ground position of the laser point. However, due to different spectral responses, different image resolutions and different imaging angles between the footprint camera and the high-resolution camera, high-precision registration between the footprint camera and the high-resolution camera is difficult, and it is difficult to accurately recover the spatial orientation of the footprint camera and determine the emergent direction of the laser spot.
Therefore, aiming at the problems of large radiation difference, obvious geometric deformation and the like between a high-resolution satellite image and a footprint camera image, which lead to low precision and poor reliability of a classical registration method, a technical means for solving the high-precision orientation problem of a small-image-size footprint camera image is urgently needed in the field. Therefore, the invention provides a high-precision and high-robustness footprint camera orientation method based on high-resolution satellite image assistance.
Disclosure of Invention
The invention provides a high-resolution satellite image-assisted footprint camera orientation method and system for solving the problem of high-precision orientation of a footprint camera, which are used for realizing high-precision orientation of the footprint camera under the assistance of the high-resolution camera, namely realizing high-precision geometric correspondence between the footprint camera and the high-resolution camera and providing a pointing reference for laser height measurement assisted three-dimensional satellite image positioning. Specifically, the technical scheme of the invention utilizes the auxiliary function of the high-resolution satellite image to obtain the accurate ground coordinates corresponding to the positioning points on the footprint camera image, thereby realizing the high-precision positioning and registration of the footprint camera and obtaining more accurate orientation parameters. According to the technical scheme, the radiation difference between the images is eliminated by utilizing the spectral matching of the multispectral image and the footprint camera image, the geometric deformation between the images is eliminated by utilizing the simulation image, the high-precision geometric matching is utilized to realize the high-precision matching between the footprint camera image and the multispectral image, and the corresponding relation between the panchromatic image and the footprint camera image is established by utilizing the matching relation between the panchromatic image and the multispectral image, so that in the final orientation link, the accurate ground point coordinate is obtained by utilizing the imaging geometric model of the high-precision panchromatic image, the accurate matching between the orientation point and the ground point coordinate on the footprint camera image is realized, the orientation correction of the footprint camera in the final link is further improved, and the more accurate attitude matrix of the footprint camera is obtained.
In one aspect, the invention provides a footprint camera orientation method based on high-resolution satellite image assistance, which comprises the following steps:
extracting orientation points from the footprint camera image;
determining the ground point coordinates of the orientation points under the assistance of the high-score satellite images;
solving the orientation parameters of the footprint camera by using the orientation points on the footprint camera image and the ground point coordinates of the orientation points;
the acquisition process of the ground point coordinates of the orientation points comprises the following steps:
superposing multispectral image wave bands corresponding to the footprint camera image spectrum in the high-resolution satellite image to generate a reference image;
calculating the image point coordinates of each image point in the footprint camera image on the reference image by using the imaging geometric model of the multispectral image and taking the ground point coordinates of each image point in the footprint camera image as a medium, and then performing gray level interpolation on the image points to synthesize a simulation image of the footprint camera image;
and then, calculating the coordinates of the image points of the orientation points corresponding to the multispectral image by taking the matching points of the orientation points on the simulation image as media, determining the coordinates of the image points of the orientation points corresponding to the panchromatic image by utilizing the registration relationship between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the coordinates of the ground points of the positioning points by utilizing the imaging geometric model of the panchromatic image.
The reference image generated by the technical scheme of the invention is generated by performing spectrum matching on the footprint camera image and the multispectral image, namely the generated reference image reduces the radiation difference between the images; further generating a simulation image by using the imaging geometric model of the footprint camera image and the imaging geometric model of the multispectral image according to the reference image, wherein the process takes the ground point coordinates of each image point in the footprint camera image as a conversion medium, and the generated simulation image can eliminate geometric deformation among the images; furthermore, the technical scheme of the invention is continuously based on the simulation image, the matching points of the set orientation points in the footprint camera image on the simulation image are searched, and then the simulation image is used as a medium to construct the matching relation between the footprint camera image and the multispectral image; and then, establishing a mapping relation between the footprint camera image and the panchromatic image by taking the multispectral image as a medium, further obtaining ground point coordinates of the orientation points calculated by depending on the imaging geometric model of the high-precision panchromatic image, further forming control points, and realizing the high-precision positioning and registration of the footprint camera by utilizing the orientation points and the ground point coordinates thereof.
Further optionally, the orientation parameters of the footprint camera are an attitude matrix of the footprint camera obtained by optimizing orientation points on the footprint camera image and ground point coordinates of the orientation points based on the constructed observation equation and an error equation thereof;
wherein the observation equation is expressed as:
wherein u is the homogeneous coordinate of the image plane, corresponding to the homogeneous coordinate of the image point on the footprint camera image; m is a scale factor, I is a unit matrix, s is a camera position at the imaging moment, K is a camera matrix, and p represents a homogeneous coordinate of a ground point object space and a homogeneous coordinate corresponding to the ground point;
is a transformation matrix from the geocentric inertial coordinate system to the body coordinate system,
is a transformation matrix from the earth-centered earth-fixed system to the earth-centered inertial system,
a deviation matrix of the orientation parameters to be estimated;
the error equation is expressed as:
wherein v is a residual error, corresponding to a residual error between the homogeneous coordinates of the orientation points on the footprint camera image and the homogeneous coordinates of the orientation points obtained by using the observation equation; x is an unknown number corresponding to the deviation matrix
Correction numbers of middle three Euler angles, wherein A is a coefficient matrix, and L is a constant part; p is a weight matrix which represents the measurement precision of the directional point image space;
performing iterative calculation by using the observation equation and the error equation to update the deviation matrix of the orientation parameter to be estimated, and then performing the iterative calculation according to a formula
The pose matrix R of the footprint camera is updated.
According to the technical scheme, iterative calculation is formed by using an observation equation and an error equation, and an attitude matrix is continuously corrected until the accuracy requirement is met, the error is lower than a preset range, the error tends to be converged and the like, namely a preset iteration termination condition is met. The iteration termination condition is set depending on the precision requirement, which is not specifically limited by the present invention.
Further optionally, the process of solving the orientation parameters of the footprint camera using the orientation points on the footprint camera image and the ground point coordinates of the orientation points further comprises:
deleting the orientation points with residual errors exceeding a preset threshold value by adopting a weight selection iterative method;
and then the orientation parameters of the footprint camera are solved by using the deleted orientation points and the ground point coordinates thereof.
According to the technical scheme, the orientation points with large residual errors are eliminated by using a weight selection iteration method, namely elevation fluctuation points are eliminated, and the orientation and registration accuracy can be further ensured.
Further optionally, the registration relationship of the multispectral image and the panchromatic image is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the coordinates of the image points on the full-color image,
is the coordinate of the image point on the multispectral image.
It should be understood that if the panchromatic image and the multispectral image are directly registered, the registration relationship between the footprint camera image and the panchromatic image can be directly obtained by using the registration model; if the panchromatic image and the multispectral image are not well registered, the corresponding relation of the image points between the panchromatic image and the multispectral image can be determined according to the formula, and then the registration relation between the footprint camera image and the panchromatic image is obtained.
Further optionally, the extraction rule of the directional point is: the points with the largest average gradient and no edges in the image interval.
Further optionally, the synthetic process of the simulation image is as follows;
a) Calculating ground point coordinates corresponding to each image point on the footprint camera image by using an external digital elevation model based on an imaging geometric model of the footprint camera image;
b) Calculating the coordinates of the image points corresponding to the ground point on the reference image based on the coordinates of the ground point in the step A and by using the imaging geometric model of the multispectral image;
c) And B, aiming at the image point coordinates in the step B, performing gray level interpolation on the reference image to obtain the gray level of the corresponding image point on the simulation image, namely performing pixel-by-pixel gray level interpolation to generate the simulation image.
Further optionally, taking a matching point of the orientation point on the simulated image as a medium, the process of calculating the coordinates of the image point of the orientation point on the multispectral image is as follows:
searching on the simulated image, and determining a matching point corresponding to each directional point on the simulated image according to the maximum selection basis of the correlation coefficient; or searching on the simulated image, roughly screening matching points corresponding to each directional point by using correlation coefficients meeting preset coefficient thresholds, and then carrying out fine matching according to a least square method or a phase correlation algorithm to obtain matching points corresponding to each directional point on the simulated image;
then, calculating the ground point coordinates corresponding to the matching points by using the imaging geometric model and the external digital elevation model of the footprint camera image;
based on the ground point coordinates corresponding to the matching points, calculating the image point coordinates of the ground point coordinates corresponding to the multispectral image by using the imaging geometric model of the multispectral image, namely the image point coordinates corresponding to the multispectral image as the orientation points;
and then constructing homonymous point pairs between the footprint camera image and the multispectral image by using the orientation points on the footprint camera image and the image point coordinates corresponding to the multispectral image.
It should be understood that the purpose of finding the matching point based on the correlation coefficient is to find the image point most similar/close to the orientation point on the simulated image as the matching point, therefore, the correlation coefficient refers to the correlation coefficient between the orientation point and the image point on the simulated image, and the invention does not restrict the type of the correlation coefficient. The predetermined coefficient threshold is an empirical value, such as set to 0.9.
In a second aspect, the present invention provides a system based on the method for orienting a footprint camera, comprising: the system comprises an orientation point extraction module, a ground point coordinate calculation module of an orientation point and an orientation module;
the orientation point extraction module is used for extracting orientation points from the footprint camera image;
the ground point coordinate calculation module of the orientation point is used for determining the ground point coordinate of the orientation point under the assistance of the high-score satellite image;
the orientation module is used for solving the orientation parameters of the footprint camera by utilizing the orientation points on the footprint camera image and the ground point coordinates of the orientation points;
the process of acquiring the ground point coordinates of the directional point by the ground point coordinate calculation module of the directional point is as follows:
superposing multispectral image wave bands corresponding to the footprint camera image spectrum in the high-resolution satellite image to generate a reference image;
taking the ground point coordinates of each image point in the footprint camera image as a medium, calculating the image point coordinates of the ground point coordinates on the reference image by using the imaging geometric model of the multispectral image, and further carrying out gray interpolation on the image points to synthesize a simulation image of the footprint camera image;
and then, taking the matching point of the orientation point on the simulated image as a medium, calculating the coordinate of the image point of the orientation point on the multispectral image, determining the coordinate of the image point of the orientation point on the panchromatic image by utilizing the registration relation between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the ground point coordinate of the positioning point by utilizing the imaging geometric model of the panchromatic image.
In a third aspect, the present invention provides an electronic terminal, which includes:
one or more processors;
and memory storing one or more computer programs;
wherein the processor invokes the computer program to implement:
a high-resolution satellite image-based footprint camera orientation method.
In a fourth aspect, the present invention provides a readable storage medium storing a computer program for invocation by a processor to implement:
a high-resolution satellite image-based footprint camera orientation method.
Advantageous effects
1. The technical scheme provided by the invention can effectively solve the problem of high-precision registration between the footprint camera and the high resolution camera, and effectively overcome the technical obstacle that the classical registration method cannot meet the requirement due to the problems of large radiation difference, remarkable geometric deformation and the like between the high resolution satellite image and the footprint camera image. The orientation method of the footprint camera provided by the invention has the advantages that the multispectral image is introduced to carry out image simulation and spectrum matching on the footprint camera image, so that the matching precision and reliability between the high-resolution satellite image and the footprint camera image are improved; the method comprises the steps of establishing a direct mapping relation between a multispectral image and a panchromatic image by utilizing the error consistency of the panchromatic image and the multispectral image, and further finally establishing a corresponding relation between the panchromatic image and an image of a footprint camera, so that a high-precision panchromatic image geometric model can be utilized to carry out high-precision orientation on the footprint camera, multiple groups of accurately-positioned orientation points and ground point coordinates thereof are obtained, control points are formed, and the orientation precision of the footprint camera is finally improved.
2. In a further preferred scheme of the invention, after the precise relation between the orientation point on the footprint camera image and the ground coordinate point thereof is obtained, the orientation point with the residual error exceeding the preset threshold value is deleted by a weight selection iterative method, so that the orientation precision of the final result can be further ensured.
Drawings
Fig. 1 is a schematic diagram of a footprint camera image provided by an embodiment of the present invention.
Fig. 2 is a schematic diagram of a full-color image of a high-resolution satellite according to the present invention.
Fig. 3 is a schematic diagram of a simulation image of the multispectral reference image provided by the present invention.
Fig. 4 is a technical route diagram provided by the present invention.
Detailed Description
The invention provides a high-resolution satellite image-based footprint camera orientation method, which realizes optimization of a footprint camera geometric model by using a high-precision high-resolution camera geometric model and improves the positioning precision of the footprint camera. In the following examples, a high-resolution seven-numbered satellite is taken as an example, and in other possible embodiments, the invention is also applicable to other laser footprint cameras with different platforms without departing from the concept of the invention, that is, the high-resolution satellite capable of acquiring multispectral images and panchromatic images or the high-resolution satellite carrying the rear-view camera of the invention. The present invention will be further described with reference to the following examples.
Example 1:
the method for orienting a high-resolution satellite image-assisted footprint camera provided by the embodiment mainly comprises three steps, namely: extracting the orientation point of the footprint camera, determining the object-side coordinate of the orientation point, and estimating the orientation parameter of the footprint camera. It can also be expressed as: extracting orientation points from the footprint camera image; determining the ground point coordinates of the orientation points under the assistance of the high-score satellite images; and solving the orientation parameters of the footprint camera by using the orientation points on the footprint camera image and the ground point coordinates of the orientation points.
In this embodiment, the following steps are performed to achieve the orientation of the footprint camera, and in other possible embodiments, the order of some steps may be modified according to the above-mentioned concepts without departing from the concept of the present invention. As shown in fig. 4, the method for orienting a footprint camera of the present embodiment includes:
step 1: and carrying out spectrum matching on the footprint camera image and the multispectral image to synthesize a reference image, namely superposing multispectral image wave bands corresponding to the footprint camera image spectrum to generate the reference image.
The high-resolution seven-satellite in the embodiment adopts a double-line array system to acquire three-dimensional data, and meanwhile, an active laser radar is carried to point to the geocentric to acquire elevation information, wherein the included angle between a forward-looking camera and a downward-looking direction is 21 degrees, and the acquired image ground sampling distance is 0.79 m; the included angle between the rear-view camera and the downward-view direction is 5 degrees, and a panchromatic image with high resolution and a multispectral image with lower resolution can be obtained simultaneously. Wherein, the following table 1 shows the bopp ranges of the cameras:
TABLE 1
From the above table, the corresponding spectrum range of the full color band of the front-view camera and the rear-view camera of the high-altitude seven-grade satellite is 0.45 to 0.9μmCovering the range from blue to near infrared spectrum; while the footprint cameraObtaining the land property energy from green to red only from 0.50 to 0.72μmResulting in significant spectral differences between the panchromatic image and the footprint camera image. The spectral feature difference between the footprint camera image and the panchromatic image is large, which will severely restrict the matching accuracy of the orientation points, as shown in fig. 1, which is a schematic diagram of the footprint camera image. Fig. 2 is a schematic diagram of a full-color image. Due to the green wave band (0.52 to 0.59) of the multispectral cameraμm) And red wavelength band (0.63 to 0.69)μm) The spectral range of the reference image data is close to that of the footprint camera, so that the reference image data is synthesized by adding the green wave band and the red wave band of the multispectral camera, and the spectral matching of the reference data and the footprint camera is realized. Therefore, the spectrum matching in this step can be expressed by the following formula:
in the formula, DN S Representing reference image data, DN G Representing green band data, DN, in a multi-spectral image R Representing red band data in the multi-spectral image.
It will be appreciated that the reference image synthesized using the above formula is spectrally matched to the footprint camera image; and because the multi-spectral image wave bands are registered with high precision, the synthesized reference image and the multi-spectral image also keep the high-precision registration relationship. At this time, the geometric model of the multispectral image may be directly applied to the synthesized reference image, that is, the imaging geometric model of the synthesized reference image is consistent with the imaging geometric model of the multispectral image.
Step 2: synthesizing a simulation image, namely calculating the ground point coordinates of each image point in the footprint camera image, calculating the coordinates of the ground point coordinates corresponding to the reference image by using the imaging geometric model of the spectrum image, and synthesizing the simulation image by gray level interpolation, as shown in fig. 3.
In this embodiment, the imaging geometric model of the footprint camera image may be a rational polynomial model or a rigorous imaging geometric model, and ground point coordinates (lat, lon, h) corresponding to the image point (i, j) on the footprint camera image are calculated by using an optical tracking method under the support of an external digital elevation model. And then, calculating the coordinates (is, js) of the image points corresponding to the reference image by using a multispectral image geometric model (rational polynomial model or rigorous imaging geometric model). Finally, a truncated Sinc function interpolation method is used to perform gray interpolation on image points (is, js) on the synthesized reference image to obtain the gray of the simulated image points, that is, the gray interpolation of one image element by one image element is performed to generate the simulated image, as shown in fig. 3.
It should be understood that the imaging geometric model and the external digital elevation model are used for calculating the ground point coordinates corresponding to the image points, namely the calculation process from the image points to the ground coordinate points; and calculating the image point coordinates corresponding to the ground point coordinates by using the imaging geometric model, that is, the calculation process from the ground point to the image point coordinates is all realizable in the prior art, so the invention does not make specific statement to this. In addition, the truncated Sinc function interpolation method is also an existing algorithm, so the calculation process is not specifically stated.
And 3, step 3: extracting a plurality of interest points from the footprint camera image, and searching the simulation image for matching points of the interest points. In this embodiment, it is preferable to determine the ground point coordinates of the interest points and then screen the interest points, where the screened interest points are the final orientation points used for orientation correction.
In the embodiment, interest points are extracted at certain intervals on the footprint camera image, and the interest points are preferably points with the maximum average gradient and are not edges in the image interval range. Then, based on the interest point, a matching point is searched on the simulated image, in this embodiment, preferably, a correlation coefficient method is used to perform pixel-level matching, and on this basis, a least square or phase correlation algorithm is used to match a high-precision matching point. Wherein the interest point can be understood as a directional point.
It should be understood that the invention does not restrict the type of the correlation coefficient and the coefficient threshold value when performing pixel-level matching, and it performs adaptive adjustment and setting according to the precision requirement; and the algorithm type of the correlation coefficient is not restricted, and according to the technical idea of the invention, the coefficient capable of representing the correlation can meet the requirement of the technical scheme of the invention. When the correlation coefficient method is used for pixel level matching, a preset coefficient threshold value needs to be set, and the method is set according to the precision requirement, namely the preset coefficient threshold value is an empirical value.
And 4, step 4: and calculating the coordinates of ground points corresponding to the matching points on the simulation image by using an imaging geometric model of the footprint camera image and an external digital elevation model, and calculating the coordinates of image points corresponding to the multispectral image on the basis of the coordinates of the ground points by using an imaging geometric model of the multispectral image, thereby obtaining homonymous point pairs between the footprint camera image and the multispectral image.
And 5: and obtaining homonymous point pairs between the footprint camera image and the panchromatic image by utilizing homonymous point pairs between the footprint camera image and the multispectral image based on the registration relationship between the multispectral image and the panchromatic image.
When the panchromatic image and the multispectral image are directly registered, the registration model is directly utilized to obtain the homonymy point pairs of the footprint camera image and the panchromatic image. If the registration is good, the following mapping relationship between the image and the ground point is established by the high-resolution seven sensor correction product, so that the same-name point pair of the footprint camera image and the panchromatic image can be obtained, specifically:
wherein the content of the first and second substances,
the coordinates of the image points on the full-color image,
is the coordinate of the image point on the multispectral image.
It will be appreciated that the pairs of homologous points obtained in accordance with the above steps are in fact the orientation points on the footprint camera image and their corresponding image point coordinates on the full colour image.
And 6: and calculating the ground point coordinates of the orientation points by using the imaging geometric model of the panchromatic image.
When the control points exist on the panchromatic image, the control points are preferably utilized to perform orientation or block adjustment, a compensation model of the panchromatic image is solved, and imaging geometric model optimization of the panchromatic image is realized. It should be understood that the present optimization step is based on prior art implementations, and therefore, implementation procedures are not specifically set forth; and in other possible embodiments, the optimization is not rigidly specified.
Furthermore, in this embodiment, the optimized imaging geometric Model of the panchromatic image, the coordinates of the image points on the panchromatic image, and the global DEM (Digital Elevation Model) are used to calculate the coordinates (lat, lon, h) of the ground points corresponding to the orientation points.
It should be understood that the full-color camera generally has higher spatial resolution, and therefore, the object coordinates of the orientation point are determined by using the optimized high-resolution full-color camera in the embodiment, so that the orientation precision of the footprint camera image can be further ensured.
And 7: and carrying out high-precision orientation on the footprint camera by using the ground point coordinates of the orientation points and the image point coordinates on the footprint camera image.
The orientation parameters of the footprint camera are based on the constructed observation equation and the error equation thereof, and the attitude matrix of the footprint camera is obtained by utilizing the orientation points on the image of the footprint camera and the ground point coordinates of the orientation points to optimize;
wherein the observation equation is expressed as:
wherein u is the homogeneous coordinate of the image plane, corresponding to the homogeneous coordinate of the image point on the footprint camera image; m is a scale factor, I is a unit matrix, s is a camera position at the imaging moment, K is a camera matrix, and p represents a homogeneous coordinate of a ground point object space and a homogeneous coordinate corresponding to the ground point;
is a transformation matrix of the earth's center inertial coordinate system to the body coordinate system,
is a conversion matrix from the earth-centered earth-fixed system to the earth-centered inertial system,
a deviation matrix of the orientation parameters to be estimated;
the error equation is expressed as:
wherein v is a residual error, corresponding to a residual error between the homogeneous coordinates of the orientation points on the footprint camera image and the homogeneous coordinates of the orientation points obtained by using the observation equation; x is an unknown number corresponding to the deviation matrix
Correction numbers of middle three Euler angles, wherein A is a coefficient matrix, and L is a constant part; and P is a weight matrix and represents the image space measurement precision of the directional point. Note that the error equation
For the conventional expression of the industry, commas represent intervals, the former being a numerical model, i.e.
Representing an error numerical model; the latter is a statistical model, i.e. a weight matrix P. Further, the expressions and calculations of the matrices a, L are conventional in the art, and therefore they are not specifically stated.
It should be understood that the construction of the bias matrix is well known in the art and its three euler angles are pitch, roll and yaw, respectively, as follows:
wherein the content of the first and second substances,
corresponding to pitch, roll and yaw angles, respectively.
Performing iterative least square calculation by using the observation equation and the error equation to update the deviation matrix of the orientation parameter to be estimated, and further according to a formula
The pose matrix R of the footprint camera is updated. For example, based on the ground point coordinates of the positioning points, the homogeneous coordinates of the image points on the footprint camera image are calculated by using an observation equation; then, residual errors are calculated based on original image point coordinates of the positioning points and the calculated homogeneous coordinates of the image points on the images of the footprint cameras to obtain X, and then a deviation matrix is updated
Obtaining the deviation matrix of the directional parameter to be estimated by the above cycle iteration and least square method
And further according to the formula
The pose matrix R of the footprint camera is updated.
In addition, in this embodiment, it is also preferable to delete the orientation point with the residual error exceeding 3 times of the median error by using a weight selection iterative method in advance. The prediction threshold is an empirical value and is set according to the precision requirement.
In conclusion, the precision orientation of the footprint camera is realized according to the above process, and the problem of high precision orientation of the footprint camera image is solved. It should be noted that in some embodiments, for example, the step of setting the orientation point may be used as the first step; in some embodiments, the order of the step 1-step 2 of constructing the simulation image and the positioning of the orientation points may be unconstrained.
Example 2:
the embodiment provides a system based on the footprint camera orientation method, which comprises the following steps: the system comprises an orientation point extraction module, a ground point coordinate calculation module of an orientation point and an orientation module;
the orientation point extraction module is used for extracting orientation points from the footprint camera image;
the ground point coordinate calculation module of the orientation point is used for determining the ground point coordinate of the orientation point under the assistance of the high-score satellite image;
the orientation module is used for solving the orientation parameters of the footprint camera by utilizing the orientation points on the footprint camera image and the ground point coordinates of the orientation points;
in some implementations, the ground point coordinate calculation module for the directional points includes: the system comprises a reference image generation module, a simulation image synthesis module and a homonymy point determination module.
Specifically, the reference image generation module is configured to superimpose multispectral image bands corresponding to the footprint camera image spectrum in a high-resolution satellite image to generate a reference image; the simulation image synthesis module is used for calculating the image point coordinates of each image point in the footprint camera image on the reference image by using the imaging geometric model of the multispectral image and taking the ground point coordinates of each image point in the footprint camera image as a medium, and then carrying out gray level interpolation on the image points to synthesize the simulation image of the footprint camera image; the homonymous point determining module is used for calculating the coordinates of the orientation points corresponding to the image points on the multispectral image by taking the matching points of the orientation points on the simulated image as a medium, determining the coordinates of the orientation points corresponding to the image points on the panchromatic image by utilizing the registration relation between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the coordinates of the ground points of the positioning points by utilizing the imaging geometric model of the panchromatic image.
In some implementations, referring to embodiment 1, the ground point coordinate calculation module for the directional points includes: the device comprises a reference image generation module, a simulation image synthesis module, a matching point search module, a first homonymy point pair extraction module, a second homonymy point pair extraction module and a calculation module.
Specifically, the reference image generation module is configured to superimpose multispectral image bands corresponding to the footprint camera image spectrum in a high-resolution satellite image to generate a reference image; the simulated image synthesis module is used for calculating the image point coordinates of each image point in the footprint camera image on the reference image by using the imaging geometric model of the multispectral image and taking the ground point coordinates of each image point in the footprint camera image as a medium, and then carrying out gray level interpolation on the image points to synthesize the simulated image of the footprint camera image; and the matching point searching module is used for extracting a plurality of interest points from the footprint camera image and searching the simulation image for the matching points of the interest points. The first dotted pair extraction module is used for calculating the ground point coordinates corresponding to the matching points on the simulation image by using the imaging geometric model and the elevation data of the footprint camera image, calculating the image point coordinates corresponding to the multispectral image by using the imaging geometric model of the multispectral image based on the ground point coordinates, and further obtaining the dotted pairs between the footprint camera image and the multispectral image. The second homonymous point pair extraction module is used for obtaining homonymous point pairs between the footprint camera image and the panchromatic image by utilizing homonymous point pairs between the footprint camera image and the multispectral image based on the registration relation between the multispectral image and the panchromatic image. And the calculation module is used for calculating the ground point coordinates of the orientation points by using the imaging geometric model of the panchromatic image.
In some implementations, the reference image generation module and the simulation image synthesis module may not be regarded as sub-modules of the ground point coordinate calculation module of the orientation point.
For the implementation process of each module, please refer to the content of the above method, which is not described herein again. It should be understood that the above described division of functional blocks is merely a division of logical functions and that in actual implementation there may be additional divisions, for example, where multiple elements or components may be combined or integrated into another system or where some features may be omitted, or not implemented. Meanwhile, the integrated unit can be realized in a hardware form, and can also be realized in a software functional unit form.
Example 3:
the present embodiments provide an electronic terminal comprising one or more processors and a memory storing one or more computer programs, wherein the processors invoke the computer programs to perform: a high-resolution satellite image-based footprint camera orientation method.
In some implementations, the processor invokes the computer program to perform in particular:
orientation points are extracted on the footprint camera image.
And determining the ground point coordinates of the orientation points with the aid of the high-score satellite images.
And solving the orientation parameters of the footprint camera by using the orientation points on the footprint camera image and the ground point coordinates of the orientation points.
When the processor calls a computer program to realize the acquisition process of the ground point coordinates of the directional point, the processor executes the following steps:
the ground point coordinates of each image point in the footprint camera image obtained based on the imaging geometric model of the footprint camera image are used as a medium, the imaging geometric model of the multispectral image is used for calculating the image point coordinates of the ground point coordinates corresponding to the reference image, and then gray level interpolation is carried out on the image points to synthesize a simulation image of the footprint camera image; and then, taking the matching point of the orientation point on the simulated image as a medium, calculating the coordinate of the image point of the orientation point on the multispectral image, determining the coordinate of the image point of the orientation point on the panchromatic image by utilizing the registration relation between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the ground point coordinate of the positioning point by utilizing the imaging geometric model of the panchromatic image.
In other implementations, the processor invokes the computer program to perform in particular:
step 1: and carrying out spectrum matching on the footprint camera image and the multispectral image to synthesize a reference image, namely superposing multispectral image wave bands corresponding to the footprint camera image spectrum to generate the reference image.
Step 2: and synthesizing a simulation image, namely calculating the ground point coordinates of each image point in the footprint camera image, calculating the coordinates of the ground point coordinates on the reference image according to the imaging geometric model of the spectrum image, and synthesizing the simulation image through gray level interpolation.
And 3, step 3: extracting a plurality of interest points from the footprint camera image, and searching the simulation image for matching points of the interest points.
And 4, step 4: and calculating the coordinates of ground points corresponding to the matching points on the simulation image by using an imaging geometric model of the footprint camera image and an external digital elevation model, and calculating the coordinates of image points corresponding to the multispectral image on the basis of the coordinates of the ground points by using an imaging geometric model of the multispectral image, thereby obtaining homonymous point pairs between the footprint camera image and the multispectral image.
And 5: and obtaining homonymous point pairs between the footprint camera image and the panchromatic image by utilizing homonymous point pairs between the footprint camera image and the multispectral image based on the registration relationship between the multispectral image and the panchromatic image.
And 6: and calculating the ground point coordinates of the orientation points by using the imaging geometric model of the panchromatic image.
And 7: and carrying out high-precision orientation on the footprint camera by using the ground point coordinates of the orientation points and the image point coordinates on the footprint camera image.
It should be understood that the implementation procedures of some steps and whether some steps are executed or not and the execution sequence of some steps can refer to the implementation procedures of the foregoing embodiments.
The memory may comprise high speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.
If the memory and the processor are implemented independently, the memory, the processor and the communication interface may be connected to each other via a bus and perform communication with each other. The bus may be an industry standard architecture bus, a peripheral device interconnect bus, an extended industry standard architecture bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc.
Optionally, in a specific implementation, if the memory and the processor are integrated on a chip, the memory and the processor may complete communication with each other through an internal interface.
It should be understood that in the embodiments of the present invention, the Processor may be a Central Processing Unit (CPU), and the Processor may also be other general purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field-Programmable Gate arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The memory may include both read-only memory and random access memory and provides instructions and data to the processor. The portion of memory may also include non-volatile random access memory. For example, the memory may also store device type information.
Example 4:
the present embodiments provide a readable storage medium storing a computer program for invocation by a processor to implement: a high-resolution satellite image-based footprint camera orientation method.
The computer program is invoked by a processor to implement:
orientation points are extracted on the footprint camera image.
And determining the ground point coordinates of the orientation points with the aid of the high-score satellite images.
And solving the orientation parameters of the footprint camera by utilizing the orientation points on the footprint camera image and the ground point coordinates of the orientation points.
Wherein the computer program, when invoked by a processor to implement an acquisition process of ground point coordinates of the directional point, performs:
the ground point coordinates of each image point in the footprint camera image obtained based on the imaging geometric model of the footprint camera image are used as a medium, the imaging geometric model of the multispectral image is used for calculating the image point coordinates of the ground point coordinates corresponding to the reference image, and then gray level interpolation is carried out on the image points to synthesize a simulation image of the footprint camera image; and then, taking the matching point of the orientation point on the simulated image as a medium, calculating the coordinate of the image point of the orientation point on the multispectral image, determining the coordinate of the image point of the orientation point on the panchromatic image by utilizing the registration relation between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the ground point coordinate of the positioning point by utilizing the imaging geometric model of the panchromatic image.
In other implementations, the computer program is invoked by a processor to implement:
step 1: and carrying out spectrum matching on the footprint camera image and the multispectral image to synthesize a reference image, namely superposing multispectral image wave bands corresponding to the footprint camera image spectrum to generate the reference image.
Step 2: synthesizing a simulation image, namely calculating the ground point coordinates of each image point in the footprint camera image, calculating the coordinates of the ground point coordinates on the reference image according to the imaging geometric model of the spectrum image, and synthesizing the simulation image through gray interpolation.
And step 3: extracting a plurality of interest points from the footprint camera image, and searching the simulation image for matching points of the interest points.
And 4, step 4: and calculating the coordinates of ground points corresponding to the matching points on the simulation image by using an imaging geometric model of the footprint camera image and an external digital elevation model, and calculating the coordinates of image points corresponding to the multispectral image on the basis of the coordinates of the ground points by using an imaging geometric model of the multispectral image, thereby obtaining homonymous point pairs between the footprint camera image and the multispectral image.
And 5: and obtaining homonymous point pairs between the footprint camera image and the panchromatic image by utilizing homonymous point pairs between the footprint camera image and the multispectral image based on the registration relationship between the multispectral image and the panchromatic image.
Step 6: and calculating the ground point coordinates of the orientation points by using the imaging geometric model of the panchromatic image.
And 7: and carrying out high-precision orientation on the footprint camera by using the ground point coordinates of the orientation points and the image point coordinates on the footprint camera image.
It should be understood that the implementation procedures of some steps and whether some steps are executed or not and the execution sequence of some steps can refer to the implementation procedures of the foregoing embodiments.
The readable storage medium is a computer readable storage medium, which may be an internal storage unit of the controller according to any of the foregoing embodiments, for example, a hard disk or a memory of the controller. For example, the terrain feature model constructed in the invention is stored in a hard disk, and then a computer program for executing the fusion step is stored in a memory, so that the fusion process is realized by relying on the memory. The readable storage medium may also be an external storage device of the controller, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the controller. Further, the readable storage medium may also include both an internal storage unit of the controller and an external storage device. The readable storage medium is used for storing the computer program and other programs and data required by the controller. The readable storage medium may also be used to temporarily store data that has been output or is to be output.
Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned readable storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be emphasized that the examples described herein are illustrative and not restrictive, and thus the invention is not to be limited to the examples described herein, but rather to other embodiments that may be devised by those skilled in the art based on the teachings herein, and that various modifications, alterations, and substitutions are possible without departing from the spirit and scope of the present invention.
Claims (10)
1. A footprint camera orientation method based on high-resolution satellite image assistance is characterized by comprising the following steps: the method comprises the following steps:
extracting orientation points from the footprint camera image;
determining the ground point coordinates of the orientation points under the assistance of the high-score satellite images;
solving the orientation parameters of the footprint camera by using the orientation points on the footprint camera image and the ground point coordinates of the orientation points;
the acquisition process of the ground point coordinates of the orientation points comprises the following steps:
superposing multispectral image wave bands corresponding to the footprint camera image spectrum in a high-resolution satellite image to generate a reference image;
calculating the image point coordinates of each image point in the footprint camera image on the reference image by using the imaging geometric model of the multispectral image and taking the ground point coordinates of each image point in the footprint camera image as a medium, and then performing gray level interpolation on the image points to synthesize a simulation image of the footprint camera image;
and then, taking the matching point of the orientation point on the simulated image as a medium, calculating the coordinate of the image point of the orientation point on the multispectral image, determining the coordinate of the image point of the orientation point on the panchromatic image by utilizing the registration relation between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the ground point coordinate of the positioning point by utilizing the imaging geometric model of the panchromatic image.
2. The method of footprint camera orientation of claim 1, in which: the orientation parameters of the footprint camera are based on the constructed observation equation and the error equation thereof, and the orientation point on the image of the footprint camera and the ground point coordinate of the orientation point are optimized to obtain the attitude matrix of the footprint camera;
wherein the observation equation is expressed as:
wherein u is the homogeneous coordinate of the image plane, corresponding to the homogeneous coordinate of the image point on the footprint camera image; m is a scale factor, I is a unit matrix, s is a camera position at the imaging moment, K is a camera matrix, and p represents homogeneous coordinates of a ground point object space and homogeneous coordinates corresponding to ground points;
is a transformation matrix from the geocentric inertial coordinate system to the body coordinate system,
is a transformation matrix from the earth-centered earth-fixed system to the earth-centered inertial system,
a deviation matrix of the orientation parameters to be estimated;
the error equation is expressed as:
wherein v is a residual error, corresponding to a residual error between homogeneous coordinates of an orientation point on the footprint camera image and homogeneous coordinates of the orientation point obtained by using an observation equation; x is an unknown number corresponding to the deviation matrix
Correction numbers of middle three Euler angles, wherein A is a coefficient matrix, and L is a constant part; p is a weight matrix which represents the measurement precision of the image space of the directional point;
performing iterative calculation by using the observation equation and the error equation to update the deviation matrix of the orientation parameter to be estimated, and then performing iterative calculation according to a formula
The pose matrix R of the footprint camera is updated.
3. The method of footprint camera orientation of claim 1, in which: the process of solving the orientation parameters of the footprint camera using the orientation points on the footprint camera image and the ground point coordinates of the orientation points further comprises:
deleting the directional points with residual errors exceeding a preset threshold value by adopting a weight selection iterative method;
and then the orientation parameters of the footprint camera are solved by using the deleted orientation points and the ground point coordinates thereof.
4. The method of footprint camera orientation of claim 1, in which: the registration relationship between the multispectral image and the panchromatic image is as follows:
wherein the content of the first and second substances,
the coordinates of the image points on the full-color image,
is the coordinate of the image point on the multispectral image.
5. The method of footprint camera orientation of claim 1, in which: the extraction rule of the orientation points is as follows: the points with the largest average gradient and no edges in the image interval.
6. The method of footprint camera orientation of claim 1, in which: the synthetic process of the simulation image is as follows;
a) Calculating the ground point coordinates corresponding to each image point on the footprint camera image by using an external digital elevation model based on the imaging geometric model of the footprint camera image;
b) Calculating the image point coordinates of the ground point coordinates on the reference image by using the imaging geometric model of the multispectral image based on the ground point coordinates in the step A;
c) And B, aiming at the image point coordinates in the step B, performing gray level interpolation on the reference image to obtain the gray level of the corresponding image point on the simulation image, namely performing pixel-by-pixel gray level interpolation to generate the simulation image.
7. The method of footprint camera orientation of claim 1, in which: taking the matching point of the orientation point on the simulated image as a medium, and calculating the coordinate of the image point of the orientation point on the multispectral image as follows:
searching on the simulated image, and determining a matching point corresponding to each directional point on the simulated image according to the maximum selection basis of the correlation coefficient; or searching on the simulated image, roughly screening matching points corresponding to each directional point by using correlation coefficients meeting preset coefficient thresholds, and then carrying out fine matching according to a least square method or a phase correlation algorithm to obtain matching points corresponding to each directional point on the simulated image;
then, calculating the ground point coordinates corresponding to the matching points by using the imaging geometric model and the external digital elevation model of the footprint camera image;
based on the ground point coordinates corresponding to the matching points, calculating the image point coordinates of the ground point coordinates corresponding to the multispectral image by using the imaging geometric model of the multispectral image, namely regarding the image point coordinates corresponding to the orientation points on the multispectral image as the image point coordinates;
and then constructing homonymous point pairs between the footprint camera image and the multispectral image by using the orientation points on the footprint camera image and the image point coordinates corresponding to the multispectral image.
8. A system based on the method of orientation of the footprint camera of any of claims 1 to 7, characterized in that: the method comprises the following steps: the system comprises an orientation point extraction module, a ground point coordinate calculation module of orientation points and an orientation module;
the orientation point extraction module is used for extracting orientation points from the footprint camera image;
the ground point coordinate calculation module of the orientation point is used for determining the ground point coordinate of the orientation point under the assistance of the high-score satellite image;
the orientation module is used for solving the orientation parameters of the footprint camera by utilizing the orientation points on the footprint camera image and the ground point coordinates of the orientation points;
the process of acquiring the ground point coordinates of the directional point by the ground point coordinate calculation module of the directional point is as follows:
superposing multispectral image wave bands corresponding to the footprint camera image spectrum in a high-resolution satellite image to generate a reference image;
calculating the image point coordinates of each image point in the footprint camera image on the reference image by using the imaging geometric model of the multispectral image and taking the ground point coordinates of each image point in the footprint camera image as a medium, and then performing gray level interpolation on the image points to synthesize a simulation image of the footprint camera image;
and then, taking the matching point of the orientation point on the simulated image as a medium, calculating the coordinate of the image point of the orientation point on the multispectral image, determining the coordinate of the image point of the orientation point on the panchromatic image by utilizing the registration relation between the multispectral image and the panchromatic image in the high-resolution satellite image, and finally determining the ground point coordinate of the positioning point by utilizing the imaging geometric model of the panchromatic image.
9. An electronic terminal, characterized by: the method comprises the following steps:
one or more processors;
and memory storing one or more computer programs;
wherein the processor invokes the computer program to:
the steps of the method of footprint camera orientation described in any of claims 1 to 6.
10. A readable storage medium, characterized by: a computer program is stored, which is invoked by a processor to implement:
the steps of the method of footprint camera orientation described in any of claims 1 to 6.
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