CN113762098A - Satellite remote sensing image matching method - Google Patents
Satellite remote sensing image matching method Download PDFInfo
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- CN113762098A CN113762098A CN202110952674.1A CN202110952674A CN113762098A CN 113762098 A CN113762098 A CN 113762098A CN 202110952674 A CN202110952674 A CN 202110952674A CN 113762098 A CN113762098 A CN 113762098A
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Abstract
The invention relates to the technical field of remote sensing images, in particular to a satellite remote sensing image matching method, which comprises the following steps: the data preprocessing includes the steps that firstly, data are acquired, completeness and quality check needs to be conducted on the data after the data are acquired, the data are processed after the data are determined to have no problems, then, the data are subjected to orthography, radiometric proofreading, registration fusion and region cutting in sequence, data correction, image processing, correction transformation function establishment, image correction and image matching are conducted, and matching of an image to be matched and a reference image is achieved according to measured coordinate points. The method can well process the data, and can process and match the complex image data when the satellite remote sensing image is complex, so that the matching accuracy of the satellite remote sensing image is improved when the satellite remote sensing image is complex.
Description
Technical Field
The invention relates to the technical field of remote sensing images, in particular to a satellite remote sensing image matching method.
Background
All films only recording the electromagnetic wave size of various ground features are called remote sensing images, and mainly refer to aerial photos and satellite photos in remote sensing.
When the satellite remote sensing images used at present are matched, the satellite remote sensing images under various conditions cannot be well adapted, so that when the satellite remote sensing images are complex, the satellite remote sensing images cannot be well matched.
Disclosure of Invention
The invention aims to provide a satellite remote sensing image matching method to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a satellite remote sensing image matching method comprises the following steps:
step S1, preprocessing data, namely firstly acquiring data, checking the completeness and quality of the data after the data acquisition is finished, processing the data after the data is determined to have no problem, and then sequentially performing the orthographic correction, the radiation correction, the registration fusion and the region clipping on the data;
step S2, correcting data to make the scale of the topographic map larger than that of the remote sensing image chart, and correcting the topographic map;
step S3, image processing, according to the result of image data preprocessing and data correction, firstly determining whether the image is multi-scene data processing, wherein the multi-scene data processing principle is that images with similar time can be embedded and then geometrically processed; the method comprises the steps of obtaining images with larger time difference, respectively carrying out geometric processing and embedding, then generating images for selecting control points, enhancing the images to improve visual effect, being beneficial to determining ground object points, and selecting TM color synthetic images of a certain time phase as images for selecting the control points;
step S4, a correction transformation function is established to establish a mathematical relationship between image coordinates and ground coordinates, namely a coordinate transformation relationship between an input image and an output image, the corrected image of the boundary range of the corrected digital image is still a digital image which is inconsistent with the shape and direction of the original image, therefore, a certain storage space and a map coordinate definition value of the space boundary must be reserved for the computer output image before correction transformation, namely, the boundary range of the corrected digital image must be predetermined;
step S5, correcting the image, describing the coordinate relationship of the corresponding points before and after correction by polynomial approximation, solving the coefficient in the polynomial by the least square principle by using the image coordinate of the control point and the theoretical coordinate in the reference coordinate system, and then correcting the image geometrically by the polynomial;
step S6, the corrected digital image gray value is resampled, when the coordinate value of the projection point of any pixel in the output image array in the original image is integer, the gray value of the original image on the integer point can be directly taken out and filled in the output image, when the coordinate of the projection point is not integer, the gray value of the projection point is determined according to the gray value of the surrounding array pixels;
step S7, matching the image to be matched with the reference image according to the coordinate points measured in the step S6;
preferably, in step S1, the acquired data includes remote sensing original data, plane control data and elevation data, and the radiometric calibration includes radiometric calibration and atmospheric calibration;
preferably, in step S2, 1: 5 ten thousand topographic map corrections should be applied to map images with a resolution less than 5m, and 1: 1 ten thousand topographic map corrections should be applied to map images with a resolution greater than 5 m;
preferably, in step S4, the corrective transformation function expression is that, starting from the original image array, the correct position of each original pixel point in the ground coordinate system is sequentially determined in the order of row and column:
x＝Fx(x,y)
Y＝Fy(x,y)
in the formula, Fx and Fy are direct correction transformation functions, each pixel is sequentially transformed and corrected according to the array of the original image to obtain the position of the image, and meanwhile, the gray value of the original image is sent to the position of a new image;
preferably, in step S4, the expression of the correction transformation function is that, starting from a blank output image array, the position of each output pixel point in the original image coordinate is also solved in reverse order according to the sequence of rows and columns:
x＝Gx(X,Y)
y＝Gy(X,Y)
because the calculated control point is not necessarily exactly positioned on the center of a certain pixel of the original image, the gray value of the control point must be determined by gray interpolation;
preferably, in the step S5, when selecting the control point, the following principle should be followed:
A. uniform distribution: generally, control points are selected at intersections of four corners and diagonal lines of an image, and then are gradually encrypted to ensure uniform distribution;
B. the characteristics are obvious: selecting the point as far as possible on a fixed ground object intersection, and utilizing a semi-fixed ground object intersection, such as a mountain top and river intersection, under the condition of no accurately positioned mark;
C. sufficient number: the number of control points is preferably about 25-35 per scene, and the number of control points is increased in mountainous areas or hilly areas.
Compared with the prior art, the invention has the beneficial effects that:
1. the satellite remote sensing image matching method can well process data, when the satellite remote sensing image is complex, complex image data can be processed and then matched, and matching accuracy when the satellite remote sensing image is complex is improved.
2. According to the satellite remote sensing image matching method, the image is corrected through the correction transformation function, the corresponding control point is selected from the image, and finally the corrected digital image gray value is resampled, so that the accuracy of the control point is guaranteed, and the matching precision is improved.
Drawings
FIG. 1 is a schematic overall flow chart of the present invention.
Detailed Description
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.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the equipment or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
In the description of this patent, it is noted that unless otherwise specifically stated or limited, the terms "mounted," "connected," and "disposed" are to be construed broadly and can include, for example, fixedly connected, disposed, detachably connected, disposed, or integrally connected and disposed. The specific meaning of the above terms in this patent may be understood by those of ordinary skill in the art as appropriate.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically limited otherwise.
Example 1
Referring to fig. 1, a technical solution provided by the present invention is:
a satellite remote sensing image matching method comprises the following steps:
step S1, preprocessing data, namely firstly acquiring data, checking the completeness and quality of the data after the data acquisition is finished, processing the data after the data is determined to have no problem, and then sequentially performing the orthographic correction, the radiation correction, the registration fusion and the region clipping on the data;
step S2, correcting data to make the scale of the topographic map larger than that of the remote sensing image chart, and correcting the topographic map;
step S3, image processing, according to the result of image data preprocessing and data correction, firstly determining whether the image is multi-scene data processing, wherein the multi-scene data processing principle is that images with similar time can be embedded and then geometrically processed; the method comprises the steps of obtaining images with larger time difference, respectively carrying out geometric processing and embedding, then generating images for selecting control points, enhancing the images to improve visual effect, being beneficial to determining ground object points, and selecting TM color synthetic images of a certain time phase as images for selecting the control points;
step S4, a correction transformation function is established to establish a mathematical relationship between image coordinates and ground coordinates, namely a coordinate transformation relationship between an input image and an output image, the corrected image of the boundary range of the corrected digital image is still a digital image which is inconsistent with the shape and direction of the original image, therefore, a certain storage space and a map coordinate definition value of the space boundary must be reserved for the computer output image before correction transformation, namely, the boundary range of the corrected digital image must be predetermined;
step S5, correcting the image, describing the coordinate relationship of the corresponding points before and after correction by polynomial approximation, solving the coefficient in the polynomial by the least square principle by using the image coordinate of the control point and the theoretical coordinate in the reference coordinate system, and then correcting the image geometrically by the polynomial;
step S6, the corrected digital image gray value is resampled, when the coordinate value of the projection point of any pixel in the output image array in the original image is integer, the gray value of the original image on the integer point can be directly taken out and filled in the output image, when the coordinate of the projection point is not integer, the gray value of the projection point is determined according to the gray value of the surrounding array pixels;
step S7, matching the image to be matched with the reference image according to the coordinate points measured in the step S6;
in the present invention, preferably, in step S1, the acquired data includes remote sensing original data, plane control data and elevation data, and the radiometric calibration includes radiometric calibration and atmospheric calibration;
in the present invention, preferably, in step S2, 1: 5 ten thousand topographic map corrections should be used for image mapping with a resolution less than 5m, and 1: 1 ten thousand topographic map corrections should be used for image mapping with a resolution greater than 5 m;
in the present invention, preferably, in step S4, the corrective transformation function expression is obtained by sequentially finding the correct position of each original pixel point in the ground coordinate system according to the order of rows and columns, starting from the original image array:
x＝Fx(x,y)
Y＝Fy(x,y)
in the formula, Fx and Fy are direct correction transformation functions, each pixel is sequentially transformed and corrected according to the array of the original image to obtain the position of the image, and meanwhile, the gray value of the original image is sent to the position of a new image;
in the present invention, it is preferable that, when the control point is selected in step S5, the following principle should be followed:
A. uniform distribution: generally, control points are selected at intersections of four corners and diagonal lines of an image, and then are gradually encrypted to ensure uniform distribution;
B. the characteristics are obvious: selecting the point as far as possible on a fixed ground object intersection, and utilizing a semi-fixed ground object intersection, such as a mountain top and river intersection, under the condition of no accurately positioned mark;
C. sufficient number: the number of control points is preferably about 25-35 per scene, and the number of control points in mountainous areas or hilly areas is increased properly;
example 2
A satellite remote sensing image matching method comprises the following steps:
step S1, preprocessing data, namely firstly acquiring data, checking the completeness and quality of the data after the data acquisition is finished, processing the data after the data is determined to have no problem, and then sequentially performing the orthographic correction, the radiation correction, the registration fusion and the region clipping on the data;
step S2, correcting data to make the scale of the topographic map larger than that of the remote sensing image chart, and correcting the topographic map;
step S3, image processing, according to the result of image data preprocessing and data correction, firstly determining whether the image is multi-scene data processing, wherein the multi-scene data processing principle is that images with similar time can be embedded and then geometrically processed; the method comprises the steps of obtaining images with larger time difference, respectively carrying out geometric processing and embedding, then generating images for selecting control points, enhancing the images to improve visual effect, being beneficial to determining ground object points, and selecting TM color synthetic images of a certain time phase as images for selecting the control points;
step S4, a correction transformation function is established to establish a mathematical relationship between image coordinates and ground coordinates, namely a coordinate transformation relationship between an input image and an output image, the corrected image of the boundary range of the corrected digital image is still a digital image which is inconsistent with the shape and direction of the original image, therefore, a certain storage space and a map coordinate definition value of the space boundary must be reserved for the computer output image before correction transformation, namely, the boundary range of the corrected digital image must be predetermined;
step S5, correcting the image, describing the coordinate relationship of the corresponding points before and after correction by polynomial approximation, solving the coefficient in the polynomial by the least square principle by using the image coordinate of the control point and the theoretical coordinate in the reference coordinate system, and then correcting the image geometrically by the polynomial;
step S6, the corrected digital image gray value is resampled, when the coordinate value of the projection point of any pixel in the output image array in the original image is integer, the gray value of the original image on the integer point can be directly taken out and filled in the output image, when the coordinate of the projection point is not integer, the gray value of the projection point is determined according to the gray value of the surrounding array pixels;
step S7, matching the image to be matched with the reference image according to the coordinate points measured in the step S6;
in the present invention, preferably, in step S1, the acquired data includes remote sensing original data, plane control data and elevation data, and the radiometric calibration includes radiometric calibration and atmospheric calibration;
in the present invention, preferably, in step S2, 1: 5 ten thousand topographic map corrections should be used for image mapping with a resolution less than 5m, and 1: 1 ten thousand topographic map corrections should be used for image mapping with a resolution greater than 5 m;
in the present invention, preferably, in step S4, the expression of the correction transformation function is based on a blank output image array, and the position of each output pixel point in the original image coordinate is also solved in sequence by row and column:
x＝Gx(X,Y)
y＝Gy(X,Y)
because the calculated control point is not necessarily exactly positioned on the center of a certain pixel of the original image, the gray value of the control point must be determined by gray interpolation;
in the present invention, it is preferable that, when the control point is selected in step S5, the following principle should be followed:
A. uniform distribution: generally, control points are selected at intersections of four corners and diagonal lines of an image, and then are gradually encrypted to ensure uniform distribution;
B. the characteristics are obvious: selecting the point as far as possible on a fixed ground object intersection, and utilizing a semi-fixed ground object intersection, such as a mountain top and river intersection, under the condition of no accurately positioned mark;
C. sufficient number: the number of control points is preferably about 25-35 per scene, and the number of control points is increased in mountainous areas or hilly areas.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A satellite remote sensing image matching method is characterized by comprising the following steps:
step S1, preprocessing data, namely firstly acquiring data, checking the completeness and quality of the data after the data acquisition is finished, processing the data after the data is determined to have no problem, and then sequentially performing the orthographic correction, the radiation correction, the registration fusion and the region clipping on the data;
step S2, correcting data to make the scale of the topographic map larger than that of the remote sensing image chart, and correcting the topographic map;
step S3, image processing, according to the result of image data preprocessing and data correction, firstly determining whether the image is multi-scene data processing, wherein the multi-scene data processing principle is that images with similar time can be embedded and then geometrically processed; the method comprises the steps of obtaining images with larger time difference, respectively carrying out geometric processing and embedding, then generating images for selecting control points, enhancing the images to improve visual effect, being beneficial to determining ground object points, and selecting TM color synthetic images of a certain time phase as images for selecting the control points;
step S4, a correction transformation function is established to establish a mathematical relationship between image coordinates and ground coordinates, namely a coordinate transformation relationship between an input image and an output image, the corrected image of the boundary range of the corrected digital image is still a digital image which is inconsistent with the shape and direction of the original image, therefore, a certain storage space and a map coordinate definition value of the space boundary must be reserved for the computer output image before correction transformation, namely, the boundary range of the corrected digital image must be predetermined;
step S5, correcting the image, describing the coordinate relationship of the corresponding points before and after correction by polynomial approximation, solving the coefficient in the polynomial by the least square principle by using the image coordinate of the control point and the theoretical coordinate in the reference coordinate system, and then correcting the image geometrically by the polynomial;
step S6, the corrected digital image gray value is resampled, when the coordinate value of the projection point of any pixel in the output image array in the original image is integer, the gray value of the original image on the integer point can be directly taken out and filled in the output image, when the coordinate of the projection point is not integer, the gray value of the projection point is determined according to the gray value of the surrounding array pixels;
in step S7, matching the image to be matched with the reference image is performed according to the coordinate points measured in step S6.
2. The satellite remote sensing image matching method according to claim 1, wherein: in the step S1, the acquired data includes remote sensing raw data, plane control data and elevation data, and the radiometric proofreading includes radiometric calibration and atmospheric proofreading.
3. The satellite remote sensing image matching method according to claim 1, wherein: in step S2, 1: 5 ten thousand topographic map corrections should be applied to map images with a resolution less than 5m, and 1: 1 ten thousand topographic map corrections should be applied to map images with a resolution greater than 5 m.
4. The satellite remote sensing image matching method according to claim 1, wherein: in the step S4, the corrective transformation function expression is to calculate the correct position of each original pixel point in the ground coordinate system in sequence according to the sequence of rows and columns from the original image array:
x＝Fx(x,y)
Y＝Fy(x,y)
in the formula, Fx and Fy are direct correction transformation functions, each pixel is sequentially transformed and corrected according to the array of the original image to obtain the position of the image, and meanwhile, the gray value of the original image is sent to the position of a new image.
5. The satellite remote sensing image matching method according to claim 1, wherein: in step S4, the correction transformation function expression is based on the blank output image array, and the position of each output pixel point in the original image coordinate is reversely calculated in sequence according to the sequence of rows and columns:
x＝Gx(X,Y)
y＝Gy(X,Y)
in the formula, Gx and Gy are indirect correction transformation functions, and the brightness values on the original image point positions calculated by the formula are taken out and filled back to the corresponding pixel point positions in the blank output image dot matrix.
6. The satellite remote sensing image matching method according to claim 1, wherein: in the step S5, when selecting the control point, the following principle should be followed:
A. uniform distribution: generally, control points are selected at intersections of four corners and diagonal lines of an image, and then are gradually encrypted to ensure uniform distribution;
B. the characteristics are obvious: selecting the point as far as possible on a fixed ground object intersection, and utilizing a semi-fixed ground object intersection, such as a mountain top and river intersection, under the condition of no accurately positioned mark;
C. sufficient number: the number of control points is preferably about 25-35 per scene, and the number of control points is increased in mountainous areas or hilly areas.
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