CN111696156A - Control point-free remote sensing image coordinate conversion method - Google Patents
Control point-free remote sensing image coordinate conversion method Download PDFInfo
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- CN111696156A CN111696156A CN202010546990.4A CN202010546990A CN111696156A CN 111696156 A CN111696156 A CN 111696156A CN 202010546990 A CN202010546990 A CN 202010546990A CN 111696156 A CN111696156 A CN 111696156A
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Abstract
The invention discloses a remote sensing image coordinate conversion method without a control point, which comprises the steps of obtaining grid vector data and a remote sensing image under a source coordinate system, and converting the grid vector data into a grid under a target coordinate system; selecting source correction points under a source grid coordinate system; matching the source correction point with the homonymous target correction point; correcting and registering the remote sensing image; acquiring two sets of control points under a source coordinate system and a target coordinate system; acquiring control points and coordinates in an image range under a target coordinate system, and checking the precision of the converted image; and carrying out precision inspection on the converted remote sensing image according to the control point coordinates. In order to realize the high-precision and high-efficiency coordinate conversion of the remote sensing image, the invention provides a control point-free method for carrying out the coordinate conversion of the remote sensing image, and the coordinate conversion of the aerial image is realized by adopting a regular or irregular grid to carry out geometric correction on the image, thereby greatly improving the efficiency on the premise of ensuring the precision.
Description
Technical Field
The invention relates to a remote sensing image coordinate conversion method, belongs to the field of image processing, and particularly relates to a control point-free remote sensing image coordinate conversion method.
Background
The remote sensing image is an image obtained by shooting a ground or aerial target from the air by using a special aerial camera arranged on a satellite or an aircraft. Depending on the photographic subject and direction, vertical photography, oblique photography, and aerial photography can be classified. Can reduce the field operation amount, lighten the labor intensity, is not limited by geographical environment conditions, and has the advantages of rapidness, accuracy, economy and the like. The device is widely used for surveying and mapping maps, geology, hydrology, mineral reserves and forest resource examination, agricultural yield assessment, large-scale factory and town planning, railway, highway, high-voltage transmission line and oil pipeline exploration and line selection, weather forecast, environment monitoring and the like, and can also be used for aerial reconnaissance, news reporting, movie and television film shooting. The remote sensing images are based on a local surveying and mapping benchmark or a national uniform surveying and mapping benchmark, the local surveying and mapping benchmark changes, or in order to adapt to the development requirement of a digital region, the existing image results need to be converted into a certain surveying and mapping benchmark, which involves the conversion of a coordinate system of the images.
The existing remote sensing image coordinate transformation method mainly comprises the following steps: (1) the translation transformation method realizes coordinate transformation through image translation, but when a central meridian is transformed, the coordinate translation cannot meet the requirements of achievement precision and edge connection precision. (2) The similarity transformation method realizes the transformation of coordinates by transformation such as translation, rotation, scale expansion and the like and resampling. (3) And the affine transformation method realizes the coordinate transformation by solving the affine transformation relation between the two coordinate systems and resampling. However, the resampling will lose image texture information, the affine transformation has lateral stretching, the relative position relationship of the ground objects is changed greatly, and the loss of high-frequency information is more serious than that of the similarity transformation.
Disclosure of Invention
In order to solve the defects of the technology, the invention provides a control point-free remote sensing image coordinate transformation method.
In order to solve the technical problems, the invention adopts the technical scheme that: a control point-free remote sensing image coordinate conversion method comprises the following steps:
step S1, obtaining grid vector data and remote sensing images under a source coordinate system, and converting the grid vector data into grids under a target coordinate system; the grid divides the region space into a plurality of grid units, and each grid unit corresponds to a space range;
s2, selecting a source correction point under a source grid coordinate system; firstly, superposing a remote sensing image and a source coordinate grid to enable the grid range to completely cover the remote sensing image, and then selecting nodes as source correction points according to the grid;
step S3, matching the source correction point with the homonymous target correction point; matching the selected source correction points with the homonymous target correction points in the target coordinate system one by one;
s4, correcting and registering the remote sensing image; correcting and registering the selected source correction point and the target correction point to generate a coordinate conversion file;
step S5, two sets of control points under a source coordinate system and a target coordinate system are obtained; acquiring control points and coordinates in an image range under a target coordinate system, and checking the precision of the converted image;
and step S6, carrying out precision inspection on the converted remote sensing image according to the control point coordinates.
The grid selected in the step S1 is a grid with a regular shape or a grid with an irregular shape; the mesh divides the region space into regular or irregular mesh units.
Further, the regular-shaped mesh includes squares, rectangles, and triangles.
The method for correcting the registration in step S4 includes:
the correction registration adopts a plane four-parameter conversion model, and the matrix expression is as follows:
the algebraic expression is:
in the formula, Δ x and Δ y are translation parameters and the unit is meter; a is a rotation parameter in radians; k is a scale parameter; x1 and y1 are new plane rectangular coordinates, x0 and y0 are original plane rectangular coordinates, and the coordinate unit is meter.
And in the step S6, performing geometric accuracy inspection on the converted remote sensing image according to the control point coordinates.
Further, the method for geometric accuracy inspection comprises the following steps:
acquiring coordinates of a detection point by utilizing a high-precision or same-precision orthophoto image result or acquiring coordinates of the detection point in the field through field operation, selecting a plane detection point, wherein the positions of the plane detection point are uniformly distributed and selected on an image characteristic point as much as possible, and the image characteristic point comprises a linear ground object, an obvious spine intersection point of the image, and an obvious corner point or an inflection point of the ground object;
and II, comparing the collected plane detection points with the positions of the same-name points in the result, and calculating the error in the plane position of the ground object point.
The invention has the following beneficial effects: aiming at the defects of the existing remote sensing image coordinate conversion method, the invention provides a control point-free method for converting the remote sensing image coordinate in order to realize the high-precision and high-efficiency coordinate conversion of the remote sensing image, and the coordinate conversion of the aerial image is realized by adopting a regular or irregular grid to carry out geometric correction on the image, thereby greatly improving the efficiency on the premise of ensuring the precision.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a schematic explanatory diagram of step S2.
Fig. 3 is a schematic explanatory diagram of step S3.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 shows a control point-free remote sensing image coordinate transformation method, which includes the steps of:
step S1, obtaining grid vector data and remote sensing images under a source coordinate system, and converting the grid vector data into grids under a target coordinate system; the selected grids can be grids with regular shapes or grids with irregular shapes. Wherein the regularly shaped mesh comprises: square, rectangular, triangular, etc. The grid divides the region space into regular or irregular grid units, each grid unit corresponding to a space range.
The remote sensing IMAGE is an IMAGE obtained by shooting through a remote sensing satellite or an aerial camera, and is generally in a TIFF or IMAGE format; and converting the grid vector data by adopting professional coordinate conversion software.
S2, selecting a source correction point under a source grid coordinate system; as shown in fig. 2, the remote sensing image and the source coordinate grid are firstly superimposed to make the grid range completely cover the remote sensing image, and then nodes with a certain density are selected as source correction points according to the grid.
Step S3, matching the source correction point with the homonymous target correction point; as shown in fig. 3, the selected source correction points are matched with the homonymous target correction points in the target coordinate system one by one.
S4, correcting and registering the remote sensing image; and carrying out correction and registration on the selected source correction point and the target correction point to generate a coordinate conversion file.
The correction registration adopts a plane four-parameter conversion model, and the matrix expression is as follows:
the algebraic expression is:
in the formula, Δ x and Δ y are translation parameters and the unit is meter; a is a rotation parameter in radians; k is a scale parameter; x1 and t1 are new plane rectangular coordinates, x0 and y0 are original plane rectangular coordinates, and the coordinate unit is meter.
Step S5, two sets of control points under a source coordinate system and a target coordinate system are obtained; and acquiring control points and coordinates in the image range under the target coordinate system for checking the precision of the converted image.
And step S6, carrying out precision inspection on the converted remote sensing image according to the control point coordinates. And carrying out geometric accuracy inspection on the converted remote sensing image according to the control point coordinates.
The detection method comprises the following steps:
acquiring coordinates of a detection point by utilizing a high-precision or same-precision orthophoto image result or acquiring coordinates of the detection point in the field through field operation, selecting a plane detection point, wherein the positions of the plane detection point are uniformly distributed and selected on an image characteristic point as much as possible, and the image characteristic point comprises a linear ground object, an obvious spine intersection point of the image, and an obvious corner point or an inflection point of the ground object;
and II, comparing the collected plane detection points with the positions of the same-name points in the result, and calculating the error in the plane position of the ground object point.
The above embodiments are not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art may make variations, modifications, additions or substitutions within the technical scope of the present invention.
Claims (6)
1. A control point-free remote sensing image coordinate transformation method is characterized in that: the method comprises the following steps:
step S1, obtaining grid vector data and remote sensing images under a source coordinate system, and converting the grid vector data into grids under a target coordinate system; the grid divides the region space into a plurality of grid units, and each grid unit corresponds to a space range;
s2, selecting a source correction point under a source grid coordinate system; firstly, superposing a remote sensing image and a source coordinate grid to enable the grid range to completely cover the remote sensing image, and then selecting nodes as source correction points according to the grid;
step S3, matching the source correction point with the homonymous target correction point; matching the selected source correction points with the homonymous target correction points in the target coordinate system one by one;
s4, correcting and registering the remote sensing image; correcting and registering the selected source correction point and the target correction point to generate a coordinate conversion file;
step S5, two sets of control points under a source coordinate system and a target coordinate system are obtained; acquiring control points and coordinates in an image range under a target coordinate system, and checking the precision of the converted image;
and step S6, carrying out precision inspection on the converted remote sensing image according to the control point coordinates.
2. The control point-free remote sensing image coordinate transformation method according to claim 1, characterized in that: the grid selected in the step S1 is a grid with a regular shape or a grid with an irregular shape; the mesh divides the region space into regular or irregular mesh units.
3. The control point-free remote sensing image coordinate transformation method according to claim 2, characterized in that: the regular-shaped mesh includes squares, rectangles, and triangles.
4. The control point-free remote sensing image coordinate transformation method according to claim 1, characterized in that: the method for correcting the registration in step S4 includes:
the correction registration adopts a plane four-parameter conversion model, and the matrix expression is as follows:
the algebraic expression is:
in the formula, Δ x and Δ y are translation parameters and the unit is meter; a is a rotation parameter in radians; k is a scale parameter; x is the number of1，y1As new plane rectangular coordinates, x0，y0Is the rectangular coordinate of the original plane, and the coordinate unit is meter.
5. The control point-free remote sensing image coordinate transformation method according to claim 1, characterized in that: and in the step S6, performing geometric accuracy inspection on the converted remote sensing image according to the control point coordinates.
6. The control point-free remote sensing image coordinate transformation method according to claim 5, characterized in that: the method for testing the geometric accuracy comprises the following steps:
acquiring coordinates of a detection point by utilizing a high-precision or same-precision orthophoto image result or acquiring coordinates of the detection point in the field through field operation, selecting a plane detection point, wherein the positions of the plane detection point are uniformly distributed and selected on an image characteristic point as much as possible, and the image characteristic point comprises a linear ground object, an obvious spine intersection point of the image, and an obvious corner point or an inflection point of the ground object;
and II, comparing the collected plane detection points with the positions of the same-name points in the result, and calculating the error in the plane position of the ground object point.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112381941A (en) * | 2021-01-15 | 2021-02-19 | 武汉鸿宇飞规划设计技术有限公司 | Aviation flight image coordinate correction method |
| CN113762098A (en) * | 2021-08-19 | 2021-12-07 | 北京和德宇航技术有限公司 | Satellite remote sensing image matching method |
| CN114399541A (en) * | 2021-12-29 | 2022-04-26 | 北京师范大学 | Regional coordinate conversion method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102073990A (en) * | 2010-11-26 | 2011-05-25 | 中国科学院遥感应用研究所 | System framework and method for automatic geometric correction of remote sensing images |
| US20130039599A1 (en) * | 2010-04-30 | 2013-02-14 | The Ritsumeikan Trust | Image transforming device, electronic device, image transforming method, image transforming program, and recording medium whereupon the program is recorded |
| CN103383773A (en) * | 2013-03-26 | 2013-11-06 | 中国科学院遥感与数字地球研究所 | Automatic ortho-rectification frame and method for dynamically extracting remote sensing satellite image of image control points |
| CN110378001A (en) * | 2019-07-11 | 2019-10-25 | 中国空间技术研究院 | A kind of Pillarless caving remote sensing satellite geometric positioning accuracy analysis method |
| CN110966991A (en) * | 2019-11-21 | 2020-04-07 | 中国人民解放军国防科技大学 | Single unmanned aerial vehicle image positioning method without control point |
-
2020
- 2020-06-16 CN CN202010546990.4A patent/CN111696156B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130039599A1 (en) * | 2010-04-30 | 2013-02-14 | The Ritsumeikan Trust | Image transforming device, electronic device, image transforming method, image transforming program, and recording medium whereupon the program is recorded |
| CN102073990A (en) * | 2010-11-26 | 2011-05-25 | 中国科学院遥感应用研究所 | System framework and method for automatic geometric correction of remote sensing images |
| CN103383773A (en) * | 2013-03-26 | 2013-11-06 | 中国科学院遥感与数字地球研究所 | Automatic ortho-rectification frame and method for dynamically extracting remote sensing satellite image of image control points |
| CN110378001A (en) * | 2019-07-11 | 2019-10-25 | 中国空间技术研究院 | A kind of Pillarless caving remote sensing satellite geometric positioning accuracy analysis method |
| CN110966991A (en) * | 2019-11-21 | 2020-04-07 | 中国人民解放军国防科技大学 | Single unmanned aerial vehicle image positioning method without control point |
Non-Patent Citations (3)
| Title |
|---|
| N.ZHANG等: "An Improved Approach for Coordinate Conversion Between Adjacent Universal Transverse Mercator Coordinate Zones", 《TRANSACTIONS OF THE ASAE》 * |
| 廖学军,张赢: "一种无精确地面控制点的航空影像处理方案", 装备指挥技术学院学报, no. 03 * |
| 张标等: "一种改进的基于格网的坐标转换方法", 《测绘与空间地理信息》, pages 3 - 4 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112381941A (en) * | 2021-01-15 | 2021-02-19 | 武汉鸿宇飞规划设计技术有限公司 | Aviation flight image coordinate correction method |
| CN112381941B (en) * | 2021-01-15 | 2021-03-26 | 武汉鸿宇飞规划设计技术有限公司 | Aviation flight image coordinate correction method |
| CN113762098A (en) * | 2021-08-19 | 2021-12-07 | 北京和德宇航技术有限公司 | Satellite remote sensing image matching method |
| CN114399541A (en) * | 2021-12-29 | 2022-04-26 | 北京师范大学 | Regional coordinate conversion method and device |
| CN114399541B (en) * | 2021-12-29 | 2022-10-21 | 北京师范大学 | Regional coordinate conversion method and device |
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