CN114562982A

CN114562982A - Weighting method and device for optical and SAR heterogeneous satellite image combined adjustment

Info

Publication number: CN114562982A
Application number: CN202210226596.1A
Authority: CN
Inventors: 李莹莹; 吕守业; 吴昊; 汪源; 张彪; 李谦; 冯鑫; 王永刚; 林郁卓越
Original assignee: Beijing Institute of Remote Sensing Information
Current assignee: Beijing Institute of Remote Sensing Information
Priority date: 2022-03-09
Filing date: 2022-03-09
Publication date: 2022-05-31
Anticipated expiration: 2042-03-09
Also published as: CN114562982B

Abstract

The invention discloses a method and a device for weighting the joint adjustment of an optical and SAR heterogeneous satellite image, wherein the method comprises the following steps: constructing an SAR image and optical image heterology regional net adjustment model; solving a weight matrix of an error equation set of image space compensation parameters according to the prior positioning accuracy of the SAR image and the optical image; updating the weight value of the object compensation parameter; the device comprises: the SAR image and optical image heterogeneous area network adjustment model building module, the weight matrix solving module of an error equation set of image space compensation parameters and the weight updating module of the image space compensation parameters. The method controls the contribution degree of optical and SAR image sources with different geometric qualities to positioning calculation, thereby constructing a more stable adjustment model and improving the positioning precision of heterogeneous image combined adjustment.

Description

Weighting method and device for optical and SAR heterogeneous satellite image combined adjustment

Technical Field

The invention relates to the technical field of SAR image processing, in particular to a weighting method and a weighting device for optical and SAR heterogeneous satellite image joint adjustment.

Background

Currently, optical satellite images and SAR satellite images are two major image sources for performing stereoscopic mapping of satellites. The joint processing of homologous data remains the main means in the field of remote sensing stereo imaging. The three-dimensional positioning by using the optical satellite image and the SAR satellite image has the advantages and disadvantages: the optical satellite images have high signal-to-noise ratio and are intuitive to interpret, but under the condition that the intersection angles of a plurality of optical satellite images participating in the stereo positioning are small, the positioning result of directly carrying out block adjustment cannot meet the requirement of the stereo positioning precision. The SAR satellite image has the all-weather unique advantage all the day, the unique side-looking characteristic is highly sensitive, the optical remote sensing can be well supplemented along with the great improvement of the resolution ratio of the satellite-borne SAR, the aim of auxiliary positioning is achieved, and when the SAR satellite image is used for positioning, because the positioning process does not need attitude information, the SAR satellite image has higher uncontrolled geometric positioning precision after system calibration. The SAR image and the optical image are combined to carry out three-dimensional positioning, the control effect of the SAR image with high geometric accuracy in the whole area network can be exerted, and the distance imaging mode of the SAR image and the central projection of the optical image are completely different, so that the advantages can be complemented by combining the SAR image and the optical image, and the three-dimensional observation structure can be effectively improved.

In the process of the combined adjustment of the optical and SAR heterogeneous satellite images, because the optical images participating in the adjustment and the SAR images have different self geometric qualities, the contribution to the adjustment precision is very different, and the imaging geometric models of the optical and SAR images are different, the influence of the corresponding monoscopic geometric positioning error on the adjustment is also different, but the existing adjustment method does not consider the different factors, and the adjustment is carried out based on the image non-difference input assumption, so that the existing combined adjustment method of the optical and SAR heterogeneous satellite images has lower precision.

Disclosure of Invention

The invention aims to solve the technical problem that the existing optical and SAR heterogeneous satellite image combined adjustment method does not consider the self geometric quality, imaging geometric model and monoscopic geometric positioning error of an optical image and an SAR image which participate in adjustment, so that the combined adjustment precision is lower.

In order to solve the above technical problem, considering that the autonomous positioning accuracy of each type of satellite is relatively stable for a relatively long time, the prior value thereof can reflect the positioning accuracy of the participating adjustment image itself to a large extent. In order to improve the joint positioning accuracy, the invention respectively considers the influence brought by the positioning accuracy of the optical image and the SAR image in the adjustment model, constructs a stable adjustment model, provides a method for differentially setting the observed value weight in the joint adjustment model according to the prior positioning accuracy of the optical image and the SAR image, and constructs a more stable adjustment model by controlling the contribution degree of optical image and SAR image sources with different geometric qualities to positioning calculation, thereby improving the positioning accuracy of the heterogeneous image joint adjustment.

The embodiment of the invention discloses a method for determining the weight of the joint adjustment of an optical and SAR heterogeneous satellite image, which comprises the following steps:

s1, constructing an SAR image and optical image heterogeneous block adjustment model, which comprises the following steps:

s11, solving the parameters of SAR (Synthetic Aperture Radar) image and RPC (Rational Polynomial Coefficients) model of optical image. And generating corresponding image coordinates and virtual control point pair sets corresponding to the ground coordinates based on the rigorous imaging geometric models of the SAR image and the optical image respectively, and solving coefficients of the RPC model function by using the point pair sets and adopting a fitting method to obtain RPC model functions s (B, L, H) and L (B, L, H) of the corresponding images. And (s, L) is a two-dimensional image coordinate of the image point in the satellite image, and (B, L, H) is a ground coordinate of the ground point corresponding to the image point in the image under a longitude and latitude coordinate system. The RPC model function is used for converting ground coordinates in a longitude and latitude coordinate system into two-dimensional image coordinates.

S12，

For the measured two-dimensional image coordinates of the ith image point on the jth image, the ground coordinates of the image point corresponding to the ground point are (B)_k,L_k,H_k) And k is the serial number of the ground point, an affine transformation model is utilized to construct an image space compensation function model of the optical image and the SAR satellite image, and a measurement error equation of the ith image point is constructed as follows:

wherein ,s^(j)(B_k,L_k,H_k) and l^(j)(B_k,L_k,H_k) To coordinate the ground point (B)_k,L_k,H_k) Substituting the result into the RPC model function of the j image,

the measured coordinate error of the ith image point on the jth image,

the image space compensation parameter of the jth image is obtained.

Carrying out derivation and linearization processing on the measurement error equation of the ith image point to obtain an error equation:

in the formula ,

RPC model for jth imageType function to ground point coordinates (B)_k,L_k,H_k) The partial derivative of (a) of (b),

the amount of correction for the unknown is,

is an initial value of ground coordinates according to the k-th ground point

And the image space compensation parameter initial value of the jth image

Calculating an initial value of the two-dimensional image coordinate of the ith image point on the jth image, wherein the calculation process is represented as:

wherein ,

the initial value of the image space compensation parameter of the jth image is obtained.

And S13, constructing an image point coordinate measurement error equation set of the optical image and the SAR image with the overlapped area.

For n image points in the image, constructing a corresponding image point coordinate measurement error equation set, wherein the expression is as follows:

wherein ,A_G and A_AIs a coefficient matrix of the error equation system, Δ x_GIs the correction of the coordinates of the ground points, Δ x_AFor the image space compensation parameter correction quantity, for the image point coordinate measurement error equation set, its corresponding weight matrix is P_I，L_IRepresenting a measurement of the coordinates of the image point,

representing an initial value of the measured value of the coordinates of the image point.

S14, taking the image space compensation parameter in the measurement error equation as the virtual observation value of the image space affine transformation parameter, constructing the error equation set of the image space compensation parameter, the expression is,

wherein I is an identity matrix and V_AThe observation error of the virtual observation value of the image space affine transformation parameter is expressed as follows:

L_Athe virtual observed value of the image space affine transformation parameter is expressed as follows:

the initial value of the virtual observed value is obtained, the value of the initial value is continuously corrected in iteration, and the expression is as follows:

the weight matrix of the error equation set of the image space compensation parameters is P_A；

S15, constructing a heterology image weighted area network adjustment equation set without control points according to the image point coordinate measurement error equation set and the error equation set of the image space compensation parameters, wherein the expression is as follows:

the weight matrix of the adjustment equation set of the weighted area network of the heterogeneous image

P_I and P_ARespectively, calculating the weight matrix of the error equation set of the image point coordinate measurement and the error equation set of the image space compensation parameters by an iterative method to obtain delta x in the adjustment equation set of the weighted area network of the heterogeneous image_G and Δx_A。

And S2, solving a weight matrix of an error equation set of the image space compensation parameters according to the prior positioning accuracy of the SAR image and the optical image.

The image point coordinate measurement weight of the image is the reciprocal of the error in the corresponding image point coordinate measurement value. Weight matrix P_IThe diagonal elements are weights corresponding to the measured values of the coordinates of the image points, and a weight matrix P_IAnd the other element of (b) is 0. For the weight matrix P_ARespectively determining the middle error and the weight matrix P of each image space compensation parameter according to the prior precision information of the image_AThe weight of each image space compensation parameter in (1) is the inverse of the error in (P), and the weight matrix_AThe diagonal elements are weights corresponding to image space compensation parameters, weight matrix P_AAnd the other element of (b) is 0.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining the median error of each image space compensation parameter according to the prior precision information of the image includes:

constant term a of image space compensation parameter₀ and b₀The image tracking method is characterized by respectively representing the translation information of the satellite along the row direction and the column direction, and the translation information is determined by the prior absolute positioning accuracy of the image in the row direction and the column direction. For an optical image, calculating the median error of a constant term of an image space compensation parameter of the optical image according to the prior positioning precision of the image in the row direction and the column direction and the known resolution of the image in the row direction and the column direction;

for SAR images, a first constant term of an image space compensation parameter represents translation information of a satellite along a row direction,calculating the middle error of the first constant term of the image space compensation parameter according to the prior positioning precision of the image row direction and the known resolution of the image row direction, and reflecting the measurement error of the distance to the slant distance R by the second constant term of the image space compensation parameter, thereby positioning the prior positioning precision sigma of the image column direction_YMultiplied by the image angle of incidence alpha_incThe mean error of the second constant term for determining the image space compensation parameter is obtained by calculation.

The primary term of the image space compensation parameter represents the zooming and rotating errors of the image, the prior relative positioning precision of the image is determined by the error nominal value of the satellite platform, and the medium error of the primary term of the image space compensation parameter is determined according to the maximum influence quantity of the precision on the image and the image size.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, after a weight matrix of an error equation set of an image space compensation parameter is solved according to prior positioning accuracy of an SAR image and an optical image, a cross-correlation matrix of the image space compensation parameter is calculated by using a pixel value vector of a row where an image point related to a ground point target is located, a feature matrix of a corresponding dimension is extracted according to the number of the weight values of the image space compensation parameter, the feature matrix is used as a weighting matrix, and the weight values of the image space compensation parameter are sequentially weighted and updated, so as to obtain the updated weight values of the image space compensation parameter.

As an alternative implementation manner, in the first aspect of the embodiment of the present invention, the pixel value vector a of the corresponding line in the image for the image point related to the ground point target is_iI ═ 1,2, …, N is the number of pixel points associated with the ground point target, all pixel value vectors are represented as the acquisition data matrix a:

A＝[a₁,a₂,…,a_N]，

and (3) calculating a cross-correlation matrix R of the acquired data matrix A to obtain:

R＝A^TA，

wherein, the element R of the ith row and the jth column of the cross-correlation matrix R_ij＝a_ia_j ^TColumn vector a_jThe pixels of the corresponding line in the image of the jth image point related to the ground point targetValue vector, adopting principal component analysis method to make dimensionality reduction treatment for collected data matrix, and extracting its characteristic matrix, said process includes the following steps:

performing characteristic decomposition on the cross-correlation matrix R to obtain N characteristic vectors and characteristic values, screening the characteristic vectors according to the size of the characteristic values, and marking a characteristic matrix E formed by screening M characteristic vectors larger than a certain threshold as:

E＝[v₁,v₂,…,v_M]，

wherein ,v_kRepresenting the kth feature vector, wherein k is 1,2, …, and M, the feature vectors are column vectors, and M is the number of weights of image space compensation parameters; taking the characteristic matrix E as a weighting matrix, and performing weighting updating on a vector a formed by weights of the image compensation parameters, namely:

b＝E^Ta，

and obtaining the weight vector b of the updated image space compensation parameter.

The second aspect of the embodiment of the invention discloses a weighting device for the joint adjustment of an optical and SAR heterogeneous satellite image, which comprises: the SAR image and optical image heterogeneous regional net adjustment model building module, the weight matrix solving module of an error equation set of image space compensation parameters and the weight updating module of the image space compensation parameters. And the weight matrix solving module of the error equation set of the image space compensation parameters is used for solving the weight matrix of the error equation set of the image space compensation parameters according to the prior positioning precision of the SAR image and the optical image.

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the SAR image and optical image heterogeneous block adjustment model building module is configured to build a SAR image and optical image heterogeneous block adjustment model, and an implementation process of the SAR image and optical image heterogeneous block adjustment model building module includes:

and (3) solving the parameters of an SAR (Synthetic Aperture Radar) image and RPC (Rational Polynomial Coefficients) models of the optical image. And generating corresponding image coordinates and virtual control point pair sets corresponding to the ground coordinates based on the rigorous imaging geometric models of the SAR image and the optical image respectively, and solving coefficients of the RPC model function by using the point pair sets and adopting a fitting method to obtain RPC model functions s (B, L, H) and L (B, L, H) of the corresponding images. And (s, L) is a two-dimensional image coordinate of the image point in the satellite image, and (B, L, H) is a ground coordinate of the ground point corresponding to the image point in the image under a longitude and latitude coordinate system. The RPC model function is used for converting ground coordinates in a longitude and latitude coordinate system into two-dimensional image coordinates.

For the measured coordinates of the ith image point on the jth image, the ground coordinates of the image point corresponding to the ground point are (B)_k,L_k,H_k) And k is the serial number of the ground point, an affine transformation model is utilized to construct an image space compensation function model of the optical image and the SAR satellite image, and a measurement error equation of the ith image point is constructed as follows:

is the measured coordinate error of the ith image point on the jth image,

the image space compensation parameter of the jth image is obtained.

in the formula ,

RPC model function vs. ground point coordinates for jth image (B)_k,L_k,H_k) The partial derivative of (a) of (b),

the amount of correction for the unknown is,

is an initial value of ground coordinates according to the k-th ground point

And the image space compensation parameter initial value of the jth image

wherein ,

And constructing an image point coordinate measurement error equation set of the optical image and the SAR image with the overlapped area.

For n image points in the image, constructing a corresponding image point coordinate measurement error equation set, wherein the expression of the equation set is as follows:

wherein ,A_G and A_AIs a coefficient matrix of the error equation system, Δ x_GIs the correction of the coordinates of the ground points, Δ x_ACompensating the parameter correction for the image space, forThe image point coordinate measurement error equation set has a weight matrix of P_I，L_IRepresenting a measurement of the coordinates of the image point,

Taking the image space compensation parameters in the measurement error equation as the virtual observed values of the image space affine transformation parameters, constructing an error equation set of the image space compensation parameters, wherein the expression is as follows,

wherein I is an identity matrix, V_AThe observation error of the virtual observation value of the image space affine transformation parameter is expressed as follows:

According to the image point coordinate measurement error equation set and the error equation set of image space compensation parameters, constructing a different-source image weighted area network adjustment equation set without control points, wherein the expression is as follows:

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the weight matrix solving module of the error equation set of the image space compensation parameter is configured to solve the weight matrix of the error equation set of the image space compensation parameter according to the a priori positioning accuracy of the SAR image and the optical image, and specifically includes:

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the determining the median error of each image space compensation parameter according to the prior accuracy information of the image includes:

constant term a of image space compensation parameter₀ and b₀The image tracking method is characterized by respectively representing the translation information of the satellite along the row direction and the column direction, and the translation information is determined by the prior absolute positioning accuracy of the image in the row direction and the column direction. For optical images, according to shadowCalculating the median error of constant terms of image space compensation parameters of the image space compensation parameters according to the prior positioning precision in the image row direction and the image column direction and the known resolution in the image row direction and the image column direction;

for SAR images, a first constant term of an image space compensation parameter represents translation information of a satellite along a row direction, a medium error of the first constant term of the image space compensation parameter is calculated according to the prior positioning precision of the image row direction and the known resolution of the image row direction, and a second constant term of the image space compensation parameter reflects a measurement error of a distance direction slant distance R, so that the prior positioning precision sigma of the image column direction is adjusted_YMultiplied by the image angle of incidence alpha_incThe mean error of the second constant term for determining the image space compensation parameter is obtained by calculation.

The primary term of the image space compensation parameter represents the zooming and rotating errors of the image, the prior relative positioning accuracy of the image is determined by the error nominal value of the satellite platform, and the medium error of the primary term of the image space compensation parameter is determined according to the maximum influence quantity of the accuracy on the image and the image size.

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the weight updating module of the image space compensation parameter calculates the cross-correlation matrix by using the pixel value vector of the row where the image point related to the ground point target is located after solving the weight matrix of the error equation set of the image space compensation parameter according to the prior positioning accuracy of the SAR image and the optical image, extracts the feature matrix of the corresponding dimension according to the number of the weights of the image space compensation parameter, uses the feature matrix as the weighting matrix, and sequentially performs weighting update on the weights of the image space compensation parameter to obtain the updated weight of the image space compensation parameter.

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the weight updating module of the image space compensation parameter updates the pixel value vector a of the corresponding line in the image of the image point related to the ground point target_iI ═ 1,2, …, N is the number of pixels associated with the ground point target, and all pixel value vectors are represented as the acquisition data matrix a:

A＝[a₁,a₂,…,a_N]，

R＝A^TA，

wherein, the element R of the ith row and the jth column of the cross-correlation matrix R_ij＝a_ia_j ^TColumn vector a_jExpressing the pixel value vector of the corresponding row of the jth image point related to the ground point target in the image, adopting a principal component analysis method to perform dimensionality reduction on an acquired data matrix, and extracting a characteristic matrix of the acquired data matrix, wherein the process specifically comprises the following steps:

performing characteristic decomposition on the cross-correlation matrix R to obtain N characteristic vectors and characteristic values, screening the characteristic vectors according to the size of the characteristic values, and screening out a characteristic matrix E consisting of M characteristic vectors larger than a certain threshold value as follows:

E＝[v₁,v₂,…,v_M]，

b＝E^Ta，

The invention discloses a weighting device for the joint adjustment of the images of the optical and SAR heterogeneous satellites in a third aspect, which comprises:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute part or all of the steps of the weighting method for the optical and SAR heterogeneous satellite image joint adjustment disclosed by the first aspect of the embodiment of the invention.

In a fourth aspect, the present invention discloses a computer storage medium, which stores computer instructions, and when the computer instructions are called, the computer instructions are used to perform some or all of the steps in the method for weighting joint adjustment of optical and SAR heterogeneous satellite images disclosed in the first aspect of the embodiments of the present invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

the embodiment of the invention provides support for the construction of the adjustment model based on the optical and SAR heterogeneous multi-view images. According to the embodiment of the invention, the degree of contribution of the optical and SAR image sources with different geometric qualities to positioning calculation is controlled by differently setting the observed value weights of the optical and SAR images in the adjustment model, so that a more stable adjustment model is constructed, and the positioning precision of the heterogeneous image combined adjustment is improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a schematic flow chart of a weighting method for joint adjustment of optical and SAR heterogeneous satellite images according to an embodiment of the present invention;

fig. 2 is a schematic composition diagram of a weighting device for joint adjustment of optical and SAR heterogeneous satellite images according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or apparatus that comprises a list of steps or elements is not limited to those listed but may alternatively include other steps or elements not listed or inherent to such process, method, product, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments. The following are detailed below.

FIG. 1 is a schematic flow chart of a weighting method for joint adjustment of optical and SAR heterogeneous satellite images according to an embodiment of the present invention; fig. 2 is a schematic composition diagram of a weighting device for joint adjustment of optical and SAR heterogeneous satellite images according to an embodiment of the present invention.

Example one

The embodiment discloses a weighting method for joint adjustment of an optical and SAR heterogeneous satellite image, which comprises the following steps:

s11, solving the parameters of SAR (Synthetic Aperture Radar) and RPC (Rational Polynomial Coefficients) models of optical images. And generating corresponding image coordinates and virtual control point pair sets corresponding to the ground coordinates based on the rigorous imaging geometric models of the SAR image and the optical image respectively, and solving coefficients of the RPC model function by using the point pair sets and adopting a fitting method to obtain RPC model functions s (B, L, H) and L (B, L, H) of the corresponding images. And (s, L) is a two-dimensional image coordinate of the image point in the satellite image, and (B, L, H) is a ground coordinate of the ground point corresponding to the image point in the image under a longitude and latitude coordinate system. The RPC model function is used for converting ground coordinates under a longitude and latitude coordinate system into two-dimensional image coordinates, and the RPC model associates a target image point (s, L) with ground coordinates (B, L, H) thereof in a mode of a ratio of a cubic polynomial of the ground coordinates.

S12，

the error of the measured coordinate of the ith image point on the jth image is minimized during the adjustment of the local area network,

the image space compensation parameter of the jth image and the ground point coordinate (B) corresponding to the ith image point_k,L_k,H_k) The method is obtained by solving through a subsequent block adjustment method.

Δs^j(s, l) and Δ l^j(s, l) is an image space compensation function of the jth image, which is obtained by using an affine transformation model, and the expression of which is as follows:

in the formula ,

the amount of correction for the unknown is,

is an initial value of ground coordinates according to the k-th ground point

And the image space compensation parameter initial value of the jth image

wherein ,

And S13, constructing an image point coordinate measurement error equation set of the optical image and the SAR image with the overlapped area. Optical image and SThe AR images are related to each other through connection points measured on the images. The connection points are matched homonymous feature points in the overlapping area. For m images, all n image points on the image correspond to s ground points, Δ x_GThe coordinate correction quantity of the s ground points is expressed as follows:

Δx_G＝[ΔB₁,ΔL₁,ΔH₁,…,ΔB_s,ΔL_s,ΔH_s]^T，

Δx_Athe image space compensation parameter correction quantity of the m images is expressed as follows:

is provided with

And

is the coefficient matrix of the error equation for the ith image point.

Is the measurement error of the pixel coordinate of the ith pixel,

the error equation of the ith image point is expressed as

And respectively constructing and integrating the error equations for the n image points to obtain an image point coordinate measurement error equation set corresponding to the n image points.

setting the initial value of the virtual observed value as 0, and continuously correcting the value in iteration, wherein the expression is as follows:

P_I and P_ARespectively, calculating the weight matrix of the error equation set of the image point coordinate measurement and the error equation set of the image space compensation parameters by an iterative method to obtain delta x in the adjustment equation set of the weighted area network of the heterogeneous image_G and Δx_A. The iterative method can adopt a least square method and the like.

The error in the pixel coordinate measurements is related to the accuracy of manual measurements or automatic matching, usually less than 1 pixel, and is determined essentially by the optical/SAR image source and resolution, so that the error in the pixel measurements can be determined to be a constant value for the same type of image source. The image point coordinate measurement weight of the image is the reciprocal of the error in the corresponding image point coordinate measurement value. Weight matrix P_IThe diagonal elements are weights corresponding to the measured values of the coordinates of the image points, and a weight matrix P_IAnd the other element of (b) is 0. For the weight matrix P_ARespectively determining the middle error and the weight matrix P of each image space compensation parameter according to the prior precision information of the image_AThe weight of each image space compensation parameter in (1) is the inverse of the error in (P), and the weight matrix_AThe diagonal elements are weights and moments corresponding to image space compensation parametersArray P_AAnd the other element of (b) is 0.

As an optional implementation manner, in this embodiment, the respectively determining the median error of each image space compensation parameter according to the prior precision information of the image includes:

constant term a of image space compensation parameter₀ and b₀The image tracking method is characterized by respectively representing the translation information of the satellite along the row direction and the column direction, and the translation information is determined by the prior absolute positioning accuracy of the image in the row direction and the column direction. For optical images, the prior positioning precision sigma is determined according to the row direction and the column direction of the image_X、σ_YAnd the known resolution R of the image in the row direction and the column direction_X、R_YCalculating a₀ and b₀Is calculated by the process of

wherein ,

denotes a₀In the case of a medium error of (2),

denotes b₀A median error of (2);

for SAR images, constant term a of image space compensation parameter₀Representing the translation information of the satellite along the line direction, and according to the prior positioning precision sigma of the image line direction_XAnd a known resolution R of the image line direction_XCalculating a₀Is small. Constant term b of image space compensation parameter₀Reflecting the measurement error of the distance to the slant distance R, and therefore by using the prior positioning precision sigma of the image column direction_YMultiplied by the image angle of incidence alpha_incThe sine value of the signal is calculated to obtain the error in the determination, the calculation formula is,

wherein ,

denotes a₀In the case of a medium error of (2),

denotes b₀A median error of (2); the slant distance refers to the distance from the ground point to the satellite.

First order term a of image space compensation parameter₁、a₂、b₁ and b₂Representing the scaling and rotation errors of the image, which for optical satellite images depends on the focal length error, lens distortion, satellite radial position error and gyro drift. For SAR imaging, this error depends on the pulse repetition frequency error, range-wise sampling frequency error, satellite radial position error, and satellite along-the-track velocity error. Determining the prior relative positioning precision of the image according to the error nominal value of the satellite platform, and determining the median error of a primary term of the image space compensation parameter according to the maximum influence quantity of the precision on the image and the image size; assuming that the maximum influence of this precision on the image is M pixels, a is determined according to M and the image size₁、a₂、b₁、b₂Has a medium error of

In the formula, Height and Width are Height and Width of the image.

As an optional implementation manner, in this embodiment, in order to improve the positioning accuracy of the joint adjustment of the different-source images, a cross-correlation matrix of a pixel value vector of a row where an image point related to a ground point target is located is calculated by using the pixel value vector, a feature matrix of a corresponding dimension is extracted according to the number of weights of image space compensation parameters, the feature matrix is used as a weighting matrix, and the weights of the image space compensation parameters are sequentially weighted and updated to obtain updated weights of the image space compensation parameters.

As an alternative implementation, in this embodiment, the image points related to the ground point target are usedThe pixel value vector a of the corresponding line in the image_iI ═ 1,2, …, N is the number of pixels associated with the ground point target, and all pixel value vectors are represented as the acquisition data matrix a:

a＝[a₁,a₂,…,a_N]，

R＝a^Ta，

wherein, the element R of the ith row and the jth column of the cross-correlation matrix R_ij＝a_ia_j ^TColumn vector a_jExpressing the pixel value vector of the corresponding row of the jth image point related to the ground point target in the image, performing dimensionality reduction processing on the collected data matrix by adopting a principal component analysis method, and extracting a characteristic matrix of the collected data matrix, wherein the process specifically comprises the following steps:

E＝[v₁,v₂,…,v_M]，

b＝E^Ta，

The experimental results of the optical and SAR image joint adjustment positioning using the method are given below. After the optical/SAR images participating in the prior information joint positioning test are subjected to on-orbit geometric calibration, the geometric information is shown in the following table and comprises 1 scene SAR image and 1 scene optical image in a certain area. The constant term weight of the image space compensation parameter virtual observation value is determined according to the prior plane positioning precision, and the primary term weight is determined according to the maximum pixel offset of the image, namely the relative median error. And combining the SAR-262 image with the CCD-513 image, adjusting the weight of the virtual observed value of the SAR/optical image space compensation parameter in the combination, and observing the influence of the prior precision information of the image on the combined positioning precision. The maximum pixel offset of the first term is fixedly set to be 2 pixels, the positioning accuracy of the SAR/optical image prior plane is changed from 0.5 meter to 200 meters respectively, adjustment of a local area network is carried out according to the legal weight of the method, errors in plane and elevation positioning under different constant term weight configurations are counted, and the optimal weight range set when the highest accuracy is obtained is basically consistent with the image prior positioning accuracy. Table 1 shows the positioning accuracy (meter) under different constant term accuracy configurations of SAR-262/CCD-513.

TABLE 1 SAR-262/CCD-513 positioning accuracy (meter) under different constant term accuracy configuration

The constant term weight is fixedly set as the positioning accuracy of the CCD and SAR image prior planes, the maximum pixel offset caused by the primary term of the image space compensation parameter is changed from 0.5 pixel to 200 pixels, the adjustment of the area network is carried out according to the legal weight of the method, and the errors in the planes/elevations under different primary term weight configurations are counted. It can be found that when the maximum offset caused by the first order is set to 0.5-2 pixels, the joint positioning has better and stable result, the plane precision is preferably 2 meters, and the elevation precision is preferably 1.7 meters. The results also show that the image distortion used in this experiment is small in intra-scene distortion, and the image distortion is basically a translation. Table 2 shows the positioning accuracy (meters) of SAR-262/CCD-513 in different primary accuracy configurations.

TABLE 2 SAR-262/CCD-513 location accuracy (meter) under different primary item accuracy configuration

Therefore, the embodiment of the invention provides support for the adjustment model construction based on the optical and SAR heterogeneous multi-view images. According to the embodiment of the invention, the degree of contribution of the optical and SAR image sources with different geometric qualities to positioning calculation is controlled by differently setting the observed value weights of the optical and SAR images in the adjustment model, so that a more stable adjustment model is constructed, and the positioning precision of the heterogeneous image combined adjustment is improved.

Example two

The second aspect of the embodiment of the invention discloses a weighting device for the joint adjustment of an optical and SAR heterogeneous satellite image, which comprises: the SAR image and optical image heterogeneous area network adjustment model building module, the weight matrix solving module of an error equation set of image space compensation parameters and the weight updating module of the image space compensation parameters. And the weight matrix solving module of the error equation set of the image space compensation parameters is used for solving the weight matrix of the error equation set of the image space compensation parameters according to the prior positioning precision of the SAR image and the optical image.

As an optional implementation manner, in this embodiment, the SAR image and optical image heterogeneous local area network adjustment model building module is configured to build a SAR image and optical image heterogeneous local area network adjustment model, and an implementation process of the SAR image and optical image heterogeneous local area network adjustment model building module includes:

For the measured two-dimensional image coordinates of the ith image point on the jth image, the ground coordinates of the image point corresponding to the ground point are (B)_k,L_k,H_k) K is the serial number of the ground point, and an affine transformation model is utilized to construct an optical image and an SARAn image space compensation function model of the satellite image is used for constructing a measurement error equation of the ith image point as follows:

is the measured coordinate error of the ith image point on the jth image,

the image space compensation parameter of the jth image is obtained.

And (3) carrying out derivation and linearization processing on the measurement error equation of the ith image point to obtain an error equation:

in the formula ,

the amount of correction for the unknown is,

as an initial value based on the ground coordinates of the kth ground point

And the image space compensation parameter initial value of the jth image

wherein ,

wherein ,A_G and A_AIs a coefficient matrix of the error equation system, Δ x_GIs the correction of the coordinates of the ground points, Δ x_AFor the image space compensation parameter correction, for the image point coordinate measurement error equation set, the corresponding weight matrix is P_I，L_IRepresenting a measurement of the coordinates of the image point,

wherein, I is an identity matrix,V_Athe observation error of the virtual observation value of the image space affine transformation parameter is expressed as follows:

As an optional implementation manner, in this embodiment, the weight matrix solving module of the error equation set of the image space compensation parameter is configured to solve the weight matrix of the error equation set of the image space compensation parameter according to the a priori positioning accuracy of the SAR image and the optical image, and specifically includes:

constant term a of image space compensation parameter₀ and b₀The image tracking method is characterized by respectively representing the translation information of the satellite along the row direction and the column direction, and the translation information is determined by the prior absolute positioning accuracy of the image in the row direction and the column direction. For an optical image, calculating the medium error of a constant term of an image space compensation parameter according to the prior positioning precision of the image row direction and the image column direction and the known resolution of the image row direction and the image column direction;

As an optional implementation manner, in this embodiment, the weight updating module of the image space compensation parameter calculates a cross-correlation matrix of the weight matrix of the error equation set of the image space compensation parameter according to the prior positioning accuracy of the SAR image and the optical image by using a pixel value vector of a row where an image point related to the ground point target is located, extracts a feature matrix of a corresponding dimension according to the number of the weights of the image space compensation parameter, uses the feature matrix as a weighting matrix, and sequentially performs weighting update on the weights of the image space compensation parameter to obtain the updated weights of the image space compensation parameter.

As an optional implementation manner, in this embodiment, the weight updating module of the image space compensation parameter updates the pixel value vector a of the corresponding line in the image of the image point related to the ground point target_iI ═ 1,2, …, N is the number of pixels associated with the ground point target, and all pixel value vectors are represented as the acquisition data matrix a:

A＝[a₁,a₂,…,a_N]，

R＝A^TA，

E＝[v₁,v₂,…,v_M]，

b＝E^Ta，

EXAMPLE III

The embodiment discloses another weighting device for the joint adjustment of the images of the optical and SAR heterogeneous satellites, which comprises:

a memory storing executable program code;

a processor coupled with the memory;

Example four

The embodiment of the invention discloses a computer storage medium, which stores computer instructions, and when the computer instructions are called, the computer instructions are used for executing part or all of the steps of the weighting method for the optical and SAR heterogeneous satellite image joint adjustment disclosed by the first aspect of the embodiment of the invention.

The above-described embodiments of the apparatus are merely illustrative, and the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above detailed description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. Based on such understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, where the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc-Read-Only Memory (CD-ROM), or other disk memories, CD-ROMs, or other magnetic disks, A tape memory, or any other medium readable by a computer that can be used to carry or store data.

Finally, it should be noted that: the method and device for weighting the joint adjustment of the images of the optical and SAR heterogeneous satellites disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used for illustrating the technical solution of the present invention, not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A weighting method for joint adjustment of optical and SAR heterogeneous satellite images is characterized by comprising the following steps:

s1, constructing an SAR image and optical image heterogeneous block adjustment model;

2. The method for weighting the joint adjustment of the optical and SAR heterologous satellite images according to claim 1, wherein said step S1 comprises:

s11, solving rational polynomial models, namely RPC (remote procedure call), of the SAR image and the optical image; generating corresponding image coordinates and virtual control point pair sets corresponding to the ground coordinates based on the rigorous imaging geometric models of the SAR image and the optical image respectively, solving coefficients of the RPC model function by using the point pair sets and adopting a fitting method to obtain RPC model functions s (B, L, H) and L (B, L, H) of the corresponding images; (s, L) is a two-dimensional image coordinate of an image point in the satellite image, and (B, L, H) is a ground coordinate of a ground point corresponding to the image point in the image under a longitude and latitude coordinate system; the RPC model function is used for converting ground coordinates under a longitude and latitude coordinate system into two-dimensional image coordinates;

S12，

is the measured coordinate error of the ith image point on the jth image,

the image space compensation parameter of the jth image;

in the formula ,

the amount of correction for the unknown is,

is an initial value of ground coordinates according to the k-th ground point

And the image space compensation parameter initial value of the jth image

wherein ,

the image space compensation parameter initial value of the jth image is obtained;

s13, constructing an image point coordinate measurement error equation set of the optical image and the SAR image with the overlapped area;

wherein ,A_G and A_AIs a coefficient matrix of the error equation system, Δ x_GIs the ground point coordinate correction, Δ x_AFor the image space compensation parameter correction quantity, for the image point coordinate measurement error equation set, its corresponding weight matrix is P_I，L_IRepresenting a measurement of the coordinates of the image point,

representing an initial value of the image point coordinate measurement value;

the expression is the initial value of the virtual observed value:

P_I and P_AWeight matrixes of the image point coordinate measurement error equation set and the error equation set of the image space compensation parameters are respectively calculated, and delta x in the heterology image weighted area network adjustment equation set is solved through an iteration method_G and Δx_A。

3. The method for weighting the joint adjustment of the optical and SAR heterologous satellite images according to claim 1, wherein said step S2 comprises:

the image point coordinate measurement weight of the image is the reciprocal of the error in the corresponding image point coordinate measurement value; weight matrix P_IThe diagonal elements are weights corresponding to the measured values of the coordinates of the image points, and a weight matrix P_IIs 0; for the weight matrix P_ARespectively determining the middle error and the weight matrix P of each image space compensation parameter according to the prior precision information of the image_AThe weight of each image space compensation parameter in (1) is the inverse of the error in (P), and the weight matrix_AThe diagonal elements are weights corresponding to image space compensation parameters, weight matrix P_AAnd the other element of (b) is 0.

4. The method for weighting the joint adjustment of the images of the optical and SAR heterogeneous satellites according to claim 3, wherein the determining the mean error of each image space compensation parameter according to the prior accuracy information of the images comprises:

constant term a of image space compensation parameter₀ and b₀Respectively representing the translation amount information of the satellite along the row direction and the column direction, which is determined by the prior absolute positioning precision of the image in the row direction and the column direction; for optical images, the prior positioning precision and the prior positioning precision in the row direction and the column direction of the imageCalculating the mean error of constant terms of image space compensation parameters of the images according to the known resolution in the row direction and the column direction of the images;

for SAR images, a first constant term of an image space compensation parameter represents translation information of a satellite along a row direction, a medium error of the first constant term of the image space compensation parameter is calculated according to the prior positioning precision of the image row direction and the known resolution of the image row direction, and a second constant term of the image space compensation parameter reflects a measurement error of a distance direction slant distance R, so that the prior positioning precision sigma of the image column direction is adjusted_YMultiplied by the image angle of incidence alpha_incCalculating to obtain the medium error of a second constant term for determining the image space compensation parameter of the sine value;

5. The method as claimed in claim 1, wherein after solving a weight matrix of an error equation set of the image space compensation parameters according to the prior positioning accuracy of the SAR image and the optical image, the method calculates a cross-correlation matrix of the image space compensation parameters by using pixel value vectors of rows where image points related to the ground point target are located, extracts feature matrices of corresponding dimensions according to the number of the weight values of the image space compensation parameters, uses the feature matrices as weighting matrices, and sequentially performs weighting update on the weight values of the image space compensation parameters to obtain updated weight values of the image space compensation parameters.

6. The method for weighting jointly the adjustment of the optical and SAR heterologous satellite images according to claim 5, characterized in that the vectors of pixel values a of the corresponding rows in the images for the pixels associated with the ground point target are obtained_iI ═ 1,2, …, N is the number of pixels associated with the ground point target, and all pixel value vectors are represented as the acquisition data matrix a:

A＝[a₁,a₂,…,a_N]，

R＝A^TA，

E＝[v₁,v₂,…,v_M]，

b＝E^Ta，

7. An optical and SAR heterogeneous satellite image joint adjustment weighting device, characterized in that the device comprises: the SAR image and optical image heterogeneous area network adjustment model building module, the weight matrix solving module of an error equation set of image space compensation parameters and the weight updating module of the image space compensation parameters; and the weight matrix solving module of the error equation set of the image space compensation parameters is used for solving the weight matrix of the error equation set of the image space compensation parameters according to the prior positioning precision of the SAR image and the optical image.

8. The weighting device for jointly adjusting the adjustment of the SAR heterogeneous satellite images according to claim 7, wherein the SAR image and optical image heterogeneous area network adjustment model constructing module is used for constructing the SAR image and optical image heterogeneous area network adjustment model, and the implementation process comprises:

solving RPC model parameters of the SAR image and the optical image; generating corresponding image coordinates and virtual control point pair sets corresponding to the ground coordinates based on the rigorous imaging geometric models of the SAR image and the optical image respectively, solving coefficients of the RPC model function by using the point pair sets and adopting a fitting method to obtain RPC model functions s (B, L, H) and L (B, L, H) of the corresponding images; (s, L) is a two-dimensional image coordinate of an image point in the satellite image, and (B, L, H) is a ground coordinate of a ground point corresponding to the image point in the image under a longitude and latitude coordinate system; the RPC model function is used for converting ground coordinates under a longitude and latitude coordinate system into two-dimensional image coordinates;

is the measured coordinate error of the ith image point on the jth image,

the image space compensation parameter of the jth image;

in the formula ,

RPC model function vs. ground point coordinates for jth image (B)_k,L_k,H_k) The partial derivative of (a) is,

the amount of correction for the unknown is,

is an initial value of ground coordinates according to the k-th ground point

And the image space compensation parameter initial value of the jth image

wherein ,

constructing an image point coordinate measurement error equation set of the optical image and the SAR image with the overlapped area;

representing an initial value of the image point coordinate measurement value;

the expression is the initial value of the virtual observed value:

P_I and P_ARespectively, calculating the weight matrix of the error equation set of the image point coordinate measurement and the error equation set of the image space compensation parameters by an iterative method to obtain delta x in the adjustment equation set of the weighted area network of the heterogeneous image_G and Δx_A；

The weight matrix solving module of the error equation set of the image space compensation parameters is used for solving the weight matrix of the error equation set of the image space compensation parameters according to the prior positioning accuracy of the SAR image and the optical image, and specifically comprises the following steps:

the image point coordinate measurement weight of the image is the reciprocal of the error in the corresponding image point coordinate measurement value; weight matrix P_IThe diagonal elements are weights corresponding to the measured values of the coordinates of the image points, and a weight matrix P_IIs 0; for the weight matrix P_ARespectively determining the middle error and the weight matrix P of each image space compensation parameter according to the prior precision information of the image_AThe weight of each image space compensation parameter in (1) is the inverse of the error in (P), and the weight matrix_AOn the diagonalThe elements are weights corresponding to the image space compensation parameters, a weight matrix P_AIs 0;

the weight updating module of the image space compensation parameter calculates a cross-correlation matrix of the weight matrix of an error equation set of the image space compensation parameter by using a pixel value vector of a row where an image point related to a ground point target is located after solving the weight matrix of the error equation set of the image space compensation parameter according to the prior positioning precision of the SAR image and the optical image, extracts a feature matrix of a corresponding dimension according to the number of the weights of the image space compensation parameter, takes the feature matrix as a weighting matrix, and sequentially performs weighting updating on the weights of the image space compensation parameter to obtain the updated weights of the image space compensation parameter.

9. A weighting device for joint adjustment of optical and SAR heterologous satellite images, the device comprising:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute part or all of the steps of the weighting method for the optical and SAR heterogeneous satellite image joint adjustment disclosed in any one of claims 1 to 6.

10. A computer storage medium storing computer instructions which, when invoked, are adapted to perform some or all of the steps of the method for weighting joint adjustment of optical and SAR heterologous satellite images as disclosed in any one of claims 1 to 6.