CN112254812B - Method, device and equipment for calculating overlapping region of camera spectral bands and storage medium - Google Patents
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Abstract
The invention discloses a method, a device and equipment for calculating a camera spectrum overlapping region and a storage medium. The calculation method comprises the following steps: step S1: dividing an image plane into a plurality of spectral band; step S2: acquiring a first image surface characteristic point of a spectrum band in an image surface coordinate system and determining a characteristic point to be calculated; and step S3: establishing an image-object model and calculating ground characteristic points of the characteristic points to be calculated under an earth inertia coordinate system; and step S4: after the preset imaging interval time, establishing an object-image model and calculating a second image surface characteristic point of the ground characteristic point under an image surface coordinate system; step S5: when the feature point to be calculated and the second image plane feature point have an overlapping region along the vertical rail direction, acquiring the overlapping region; step S6: and acquiring a third image surface feature point of the overlapping region and taking the third image surface feature point as a feature point to be calculated, and circularly executing the steps S3-S5 until the overlapping regions of all the spectral band bands are acquired, and calculating the overlapping rate. Through the mode, the method can improve the calculation precision and has stronger adaptability.
Description
Technical Field
The invention relates to the technical field of optical remote sensing camera imaging, in particular to a method, a device, equipment and a storage medium for calculating a camera spectrum overlapping region.
Background
The spectral resolution and spectral range of the remote sensing camera are important technical indexes. The multispectral camera divides incident full-wave band or wide-wave band light signals into a plurality of narrow-wave band light beams, and the light beams enter different detectors or detection surfaces, so that images of different spectral wave bands are obtained. At present, the multispectral imaging technology is deeply applied to multiple industry fields of social life such as precision agriculture, forestry resources, water conservancy environment, disaster assessment and the like. The area array multispectral remote sensing camera can be divided into three types: the first is a multi-lens type multispectral camera. The system comprises a plurality of lenses, wherein each lens is provided with a light filter respectively and allows light with a narrow spectrum to pass through, the lenses shoot the same scene at the same time and record image information of a plurality of different spectral bands at the same time; the second is a beam splitting type multi-spectral camera. It adopts a lens to shoot scenery, uses a light splitter to separate the light from scenery into several wave band light beams, and uses a multi-plate detector to record the optical information of every wave band. The third is to cover the filter on the detector directly, to coat the filter with customized strip, to realize multi-spectrum imaging only with single lens single detector. The camera has the characteristics of simple structure, high stability, low cost and easy realization, and is increasingly applied to the field of space remote sensing along with the continuous improvement of the coating process.
A plurality of bands are divided on a detector through coating, corresponding to different spectral band ranges, band images of a plurality of spectral bands can be generated by the same exposure imaging, and in order to realize multispectral fusion, overlapping of coverage areas of the spectral bands must be ensured. Therefore, the coincidence of the multispectral bands needs to be realized by reasonably arranging the imaging interval time, and in the process, the overlapping rate of coverage areas needs to be analyzed, and the imaging interval time can be adjusted according to the situation. At present, most of remote sensing camera imaging coverage rate calculation adopts related third party integrated software or a static geometry drawing mode, and the former is not easy to expand functions and is not suitable for complex application scenes; the model of the latter model is simple in structure, but the considered dynamic factors are few, the calculation accuracy is poor, and the model is only suitable for simple estimation.
Disclosure of Invention
The invention provides a method, a device and equipment for calculating a camera spectrum overlapping region and a storage medium, which can improve the calculation precision, are suitable for the satellite large-angle maneuvering imaging working condition, and have stronger adaptability compared with the traditional estimation method.
In order to solve the technical problems, the invention adopts a technical scheme that: a method for calculating the overlapping coverage of the camera spectrum is provided, which comprises the following steps:
step S1: establishing an image surface coordinate system on a detector, and dividing an image surface into a plurality of uniform spectral band strips;
step S2: acquiring first image surface characteristic points of the spectral band under the image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points;
and step S3: acquiring a first working condition of the camera and the satellite, establishing an image-object model according to the first working condition, and calculating the ground characteristic point of the characteristic point to be calculated under the earth inertia coordinate system through the image-object model;
and step S4: after a preset imaging interval time, acquiring a second working condition of the camera and the satellite, establishing an object-image model according to the second working condition, and calculating a second image plane characteristic point of the ground characteristic point under the image plane coordinate system through the object-image model;
step S5: when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction, acquiring an overlapping region between a spectral band where the feature point to be calculated is located and an adjacent spectral band;
step S6: and acquiring a third image surface feature point of the overlapping region, taking the third image surface feature point as the feature point to be calculated, and executing the steps S3-S5 in a circulating manner until the overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
According to an embodiment of the present invention, before step S5, the method further includes:
judging whether the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction;
and when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are not overlapped along the vertical rail direction, reducing the preset imaging interval time, and executing the step S4 again.
According to an embodiment of the present invention, in step S6, a ratio of an area of the overlap region to an area of any one of the spectral bands is calculated in the image plane coordinate system, and an overlap ratio of the overlap region is obtained.
According to an embodiment of the present invention, after step S6, the method further includes:
step S7: and gradually increasing the preset imaging interval time, and circularly executing the steps S4-S6 until the overlapping rate is maximum.
According to an embodiment of the invention, step S3 further comprises:
calculating a first coordinate of the optical center of the camera under the earth inertial coordinate system according to the first working condition;
performing coordinate transformation of the image plane coordinate system and the earth inertia coordinate system according to the first coordinate, and calculating a second coordinate of the feature point to be calculated under the earth inertia coordinate system;
and calculating a first ground characteristic point of the characteristic point to be calculated under the earth inertia coordinate system according to the first coordinate and the second coordinate.
According to an embodiment of the invention, step S4 further comprises:
calculating a second ground characteristic point of the characteristic point to be calculated under the earth inertial coordinate system after the preset imaging interval time according to the first ground characteristic point, the preset imaging interval time and the second working condition;
calculating a third coordinate of the optical center of the camera under the earth inertial coordinate system according to the second working condition;
calculating a fourth coordinate of the feature point to be calculated in the earth inertial coordinate system after a preset imaging interval time;
and calculating a second image surface characteristic point corresponding to the first ground characteristic point in the image surface coordinate system according to the second ground characteristic point, the third coordinate and the fourth coordinate.
According to an embodiment of the invention, the first operating condition and the second operating condition each comprise: the attitude angle of the rolling satellite, the attitude angle of the pitching satellite, the attitude angle of the yawing satellite, the flight speed, the earth-center distance of the orbit of the satellite, the inclination angle of the orbit, the amplitude angle of the orbit of the satellite, the latitude of the point under the satellite, the installation information of the focal plane of the camera, the focal length, the imaging mode and the rotation angular rate of the earth.
In order to solve the technical problem, the invention adopts another technical scheme that: a computing device for overlapping coverage of camera spectral bands is provided, comprising:
the dividing module is used for establishing an image plane coordinate system on the detector and dividing the image plane into a plurality of uniform spectral band;
the determining module is used for acquiring first image surface characteristic points of the spectral band under the image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points;
the first calculation module is used for acquiring a first working condition of the camera and the satellite, establishing an image-object model according to the first working condition and calculating the ground characteristic point of the characteristic point to be calculated under the earth inertial coordinate system through the image-object model;
the second calculation module is used for acquiring a second working condition of the camera and the satellite after a preset imaging interval time, establishing an object-image model according to the second working condition and calculating a second image plane feature point of the ground feature point under the image plane coordinate system through the object-image model;
the acquisition module is used for acquiring an overlapping region between a spectral band where the feature point to be calculated is located and an adjacent spectral band when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction;
and the circulating calculation module is used for acquiring a third image surface feature point of the overlapping region, taking the third image surface feature point as the feature point to be calculated, circularly executing the steps executed by the first calculation module, the second calculation module and the acquisition module until the overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
In order to solve the technical problems, the invention adopts another technical scheme that: there is provided a computer device comprising: the device comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the method for calculating the overlapping region of the camera spectrum when executing the computer program.
In order to solve the technical problems, the invention adopts another technical scheme that: there is provided a storage medium storing a program file capable of implementing the above-described method of calculating a region of overlap of camera bands.
The beneficial effects of the invention are: under different working conditions, image-object conversion and object-image conversion of two adjacent frames are sequentially completed by establishing mathematical models, and the calculation of the overlapped areas of different spectral bands at different moments is unified on an image plane coordinate system, so that the method is more intuitive and improves the calculation precision; compared with the traditional estimation method, the calculation method is suitable for the satellite large-angle maneuvering imaging working condition and has stronger adaptability.
Drawings
FIG. 1 is a flow chart illustrating a method for calculating an overlapping region of camera spectral bands according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of the spectral distribution structure at the focal plane of the detector in an embodiment of the present invention;
FIG. 3 is a diagram of a division structure of a band of a ground imaging spectrum in an embodiment of the present invention;
FIG. 4 is a flowchart illustrating step S103 according to the first embodiment of the present invention;
FIG. 5 is a flowchart illustrating step S104 according to the first embodiment of the present invention;
FIG. 6 is a flowchart illustrating a method for calculating an overlapping region of camera spectral bands according to a second embodiment of the present invention;
FIG. 7 is a flowchart illustrating a method for calculating an overlapping region of camera spectral bands according to a third embodiment of the present invention;
FIG. 8 is a schematic diagram of a computing device for calculating the overlap region of the camera spectrum according to an embodiment of the present invention;
FIG. 9 is a schematic structural diagram of a computer apparatus according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram of a storage medium according to an embodiment 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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The terms "first", "second" and "third" in the present invention 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," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise. All directional indicators (such as up, down, left, right, front, and back) in the embodiments of the present invention are only used to explain the relative position relationship between the components, the movement, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indicator is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, 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.
Fig. 1 is a flowchart illustrating a method for calculating a region of overlapping camera spectral ranges according to a first embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 1 if the results are substantially the same. As shown in fig. 1, the method comprises the steps of:
step S101: and establishing an image plane coordinate system on the detector, and dividing the image plane into a plurality of uniform spectral band.
The camera of the embodiment is an area array multispectral remote sensing camera. In step S101, the image plane is divided into a plurality of spectral bands, such as L1, L2.. Ln, on average according to the required number of spectra. The spectral bands are shaped like rectangles, as shown in fig. 2 and fig. 3, 3 spectra correspond to 3 spectral bands, there is an overlapping region between two adjacent spectral bands of two adjacent frames, and the spectral band with the most forward imaging position along the flight direction of the satellite is defined as the first spectral band, such as L1.
Step S102: and acquiring first image surface characteristic points of the spectral band in an image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points.
In step S102, to simplify the calculation, four vertices of the spectral band are selected as a subset of the feature points of the first image plane, such as P 1 (P 1a ,P 1b ,P 1c ,P 1d ) The coordinates of each vertex in the image plane coordinate system are represented by (x, y), such as P 1a (x 1 ,y 1 ). In this embodiment, the first image plane feature point on the first spectral band in step S101 is determined as the first feature point to be calculated, that is, the first feature point to be calculated is P 1 (P 1a ,P 1b ,P 1c ,P 1d )。
Step S103: the method comprises the steps of obtaining a first working condition of a camera and a satellite, establishing an image-object model according to the first working condition, and calculating ground characteristic points of characteristic points to be calculated under an earth inertia coordinate system through the image-object model.
In step S103, the first operating condition includes: the attitude angle of the satellite roll, the attitude angle of the satellite pitch, the attitude angle of the satellite yaw, the flight speed, the earth center distance of the satellite orbit, the orbit inclination angle, the amplitude angle of the satellite orbit, the latitude of the satellite point, the installation information of the focal plane of the camera, the focal length, the imaging mode and the rotation angular rate of the earth. Referring to fig. 4, step S103 further includes the following steps:
step S1031: and calculating a first coordinate of the optical center of the camera under an earth inertia coordinate system according to the first working condition.
In step S1031, the first coordinate is O 1a (x o1 ,y o1 ,z o1 ) Wherein, in the process,
O 1a =(R r1 ·R i ·M l ) T ·
M l =[0 0 Height]
wherein, height is the earth center distance of the satellite orbit, i is the orbit inclination angle, rout1 is the satellite orbit amplitude angle, rout1= pi-arcsin (sin (geolati)/sin (i, i)), and geolati is the latitude of the satellite point.
Step S1032: performing coordinate transformation of an image surface coordinate system and an earth inertia coordinate system according to the first coordinate, and calculating a second coordinate of the feature point to be calculated under the earth inertia coordinate system;
in step S1032, one point P in the subset of feature points to be calculated is used 1a (x 1 ,y 1 ) For example, the second coordinate is D 1a (x p1 ,y p1 ,z p1 ) And transforming the coordinate system into the earth inertia coordinate system through the image plane coordinate system: d 1a =(R r1 ·R i ) T ·A 1 T ·[x 1 y 1 f] T +O 1a Wherein f is the camera focal length;
wherein,is the satellite roll attitude angle, theta 1 Is the satellite pitch attitude angle, Ψ 1 Is the satellite yaw attitude angle.
Step S1033: and calculating a first ground characteristic point of the characteristic point to be calculated under the earth inertial coordinate system according to the first coordinate and the second coordinate.
In step S1033, the first ground feature point is set to G 1 (G 1a ,G 1b ,G 1c ,G xd ) Wherein with P 1a (x 1 ,y 1 ) Corresponding feature point is G 1a (x g1 ,y g1 ,z g1 ) And establishing a collinear equation according to the first coordinate and the second coordinate to obtain:
(x p1 -x o1 )(z g1 -z o1 )=(x g1 -x o1 )(z p1 -z o1 )
(y p1 -y o1 )(z g1 -z o1 )=(y g1 -y o1 )(z p1 -z o1 )
due to x g1 、y g1 、z g1 All on the ellipsoid of the earth, and the simultaneous equation of the ellipsoid of the earth can be solved to obtain the equation P 1a (x 1 ,y 1 ) Corresponding ground feature point G 1a (x g1 ,y g1 ,z g1 ) Similarly, the characteristic point P to be calculated is solved in the same way 1 (P 1a ,P 1b ,P 1c ,P 1d ) First ground characteristic point G in earth inertial coordinate system 1 (G 1a ,G 1b ,G 1c ,G 1d )。
Step S104: and after the preset imaging interval time, acquiring a second working condition of the camera and the satellite, establishing an object-image model according to the second working condition, and calculating a second image surface characteristic point of the ground characteristic point in the image surface coordinate system through the object-image model.
In step S104, the second operating condition includes: the attitude angle of the satellite roll, the attitude angle of the satellite pitch, the attitude angle of the satellite yaw, the flight speed, the earth center distance of the satellite orbit, the orbit inclination angle, the amplitude angle of the satellite orbit, the latitude of the satellite point, the installation information of the focal plane of the camera, the focal length, the imaging mode and the rotation angular rate of the earth. Referring to fig. 5, step S104 further includes the following steps:
step S1041: calculating a second ground characteristic point of the characteristic point to be calculated under the earth inertia coordinate system after the preset imaging interval time according to the first ground characteristic point, the preset imaging interval time and a second working condition;
in step S1041, the preset imaging interval time is used for imaging two adjacent framesThe interval time is that after the preset imaging interval time, the motion of the earth and the satellite under the earth inertial coordinate system changes, and after the preset imaging interval time, the second ground characteristic point corresponding to the characteristic point to be calculated is G 2 (G 2a ,G 2b ,G 2c ,G 2d ) With one point P of the subset of feature points to be calculated 1a (x 1 ,y 1 ) For example, after a predetermined imaging interval, P is compared with 1a (x 1 ,y 1 ) Corresponding feature point is G 2a ,
Wherein, ω is the rotation angular rate of the earth, and Δ T is a preset imaging interval time.
In the same way, according to the first ground characteristic point G 1 (G 1a ,G 1b ,G 1c ,G 1d ) The second ground characteristic point G can be obtained according to the steps 2 (G 2a ,G 2b ,G 2c ,G 2d )。
Step S1042: calculating a third coordinate of the optical center of the camera under an earth inertia coordinate system according to a second working condition;
in step S1042, after the preset imaging interval time, the third coordinate is O 2a (x o2 ,y o2 ,z o2 ) Wherein O is 2a =(R r2 ·R i ·M l ) T ·,O 2a And O 1a The calculation methods are similar and will not be described herein again.
Step S1043: calculating a fourth coordinate of the feature point to be calculated in the earth inertial coordinate system after the preset imaging interval time;
in step S1043, the fourth coordinate is D 2a (x p2 ,y p2 ,z p2 ) The coordinate transformation is: d 2a =(R r2 ·R i ) T ·A 2 T ·[x y f] T +O 2a Wherein the ratio of (x,y) is the point G with the ground feature 1a (x g1 ,y g1 ,z g1 ) Corresponding image plane point, A 2 And the above A 1 The calculation methods are similar and will not be described herein again.
Step S1044: and calculating a second image surface feature point corresponding to the first ground feature point in the image surface coordinate system according to the second ground feature point, the third coordinate and the fourth coordinate.
In step S1044, the second image plane feature point is set to Q 1 (Q 1a ,Q 1b ,Q 1c ,Q 1d ) Wherein, with the ground feature point G 1a (x g1 ,y g1 ,z g1 ) Corresponding image point is Q 1a (x, y), establishing a collinear equation according to the second ground characteristic point, the third coordinate and the fourth coordinate to obtain:
(x p2 -x o2 )(z g2 -z o2 )=(x g2 -x o2 )(z p2 -z o2 )
(y p2 -y o2 )(z g2 -z o2 )=(y g2 -y o2 )(z p2 -z o2 )
solving to obtain Q 1a (x, y), repeating the steps, and solving the first ground characteristic point G one by one 1 (G 1a ,G 1b ,G 1c ,G 1d ) Corresponding second image surface characteristic point Q 1 (Q 1a ,Q 1b ,Q 1c ,Q 1d )。
Step S105: and when the region corresponding to the feature point to be calculated and the region corresponding to the second image surface feature point are overlapped along the vertical rail direction, acquiring an overlapping region between the spectral band where the feature point to be calculated is located and the adjacent spectral band.
In step S105, when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point overlap in the vertical rail direction, it indicates that the images formed by each exposure of the spectral band L1 on the image plane overlap, and since each spectral band is divided uniformly and only the imaging position is distinguished from the front and back, it can be ensured that the images formed by two adjacent exposures of other spectral bands have a heavy imageAnd no leakage is caused by folding. The overlapping region of the present embodiment is the overlapping region of the spectral band L1 and L2 on the image plane, i.e. the overlapping region P 2 ' second image plane characteristic point Q of spectral band L1 1 First image surface characteristic point P of spectral band L2 2 Of intersection, i.e. P 2 ′=Q 1 ∩P 2 。
Step S106: and acquiring a third image surface feature point of the overlapping region, taking the third image surface feature point as a feature point to be calculated, and executing the steps S103-S105 in a circulating manner until the overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
In step S106, P is added 2 ' as a third image plane feature point, and using the third image plane feature point as a feature point to be calculated, steps S103-S105 are executed in a loop, and when an overlap region P between a spectral band where the feature point to be calculated is located and a last spectral band is obtained n ' thereafter, P is calculated in the image plane coordinate system n ' the area is the area of the overlapped region of different spectral bands, and the overlapping ratio is the area of the overlapped region calculated under the image plane coordinate systemTo the area of any bandIn a ratio of
In the solving process, the parameters such as the attitude angle of the satellite, the flight speed, the orbit height and the like in the imaging process are considered to be in an ideal unchanged state, but in an actual situation, particularly, the attitude of the satellite has control errors and measurement errors within a certain range, and the calculation of an overlapping area is greatly influenced by the fluctuation of the attitude, so that the problem is solved by a monte carlo method.
According to the method for calculating the overlapping region of the camera spectrum band, the image-object conversion and the object-image conversion of two adjacent frames are sequentially completed by establishing the mathematical model under different working conditions, the overlapping region calculation of different spectrum band bands at different moments is unified to the image plane coordinate system, the method is more visual, and the calculation accuracy is improved; compared with the traditional estimation method, the calculation method is suitable for the satellite large-angle maneuvering imaging working condition and has stronger adaptability.
Fig. 6 is a flowchart illustrating a method for calculating a region of overlapping camera spectral ranges according to a second embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 6 if the substantially same result is obtained. As shown in fig. 6, the method includes the steps of:
step S601: an image plane coordinate system is established on a detector, and the image plane is divided into a plurality of uniform spectral band.
In this embodiment, step S601 in fig. 6 is similar to step S101 in fig. 1, and for brevity, is not described herein again.
Step S602: and acquiring first image surface characteristic points of the spectral band in an image surface coordinate system, and determining characteristic points to be calculated from the first image surface characteristic points.
In this embodiment, step S602 in fig. 6 is similar to step S102 in fig. 1, and for brevity, is not described herein again.
Step S603: the method comprises the steps of obtaining a first working condition of a camera and a satellite, establishing an image-object model according to the first working condition, and calculating ground characteristic points of characteristic points to be calculated under an earth inertia coordinate system through the image-object model.
In this embodiment, step S603 in fig. 6 is similar to step S103 in fig. 1, and for brevity, is not described herein again.
Step S604: and after the preset imaging interval time, acquiring a second working condition of the camera and the satellite, establishing an object-image model according to the second working condition, and calculating a second image surface characteristic point of the ground characteristic point in the image surface coordinate system through the object-image model.
In this embodiment, step S604 in fig. 6 is similar to step S104 in fig. 1, and for brevity, is not repeated herein.
Step S605: and when the region corresponding to the feature point to be calculated and the region corresponding to the second image surface feature point are overlapped along the vertical rail direction, acquiring an overlapping region between the spectral band where the feature point to be calculated is located and the adjacent spectral band.
In this embodiment, step S605 in fig. 6 is similar to step S105 in fig. 1, and for brevity, is not repeated herein.
Step S606: and acquiring a third image surface feature point of the overlapping region, taking the third image surface feature point as a feature point to be calculated, and executing the steps S603-S605 in a circulating manner until the overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
In this embodiment, step S606 in fig. 6 is similar to step S106 in fig. 1, and is not repeated herein for brevity.
Step S607: the preset imaging interval time is increased step by step, and steps S604 to S606 are executed in a loop until the overlapping rate is maximized.
In step S607, in the case that the single spectral band does not have a leak, the larger the preset imaging interval time is, the higher the overlapping rate of the multi-spectral band is, so by gradually increasing the preset imaging interval time, the optimal value of the overlapping rate can be obtained by iterative solution.
The method for calculating the overlapping region of the camera spectral bands in the second embodiment of the invention is based on the first embodiment, and by gradually increasing the preset imaging interval time under the condition that a single spectral band is not leaky, iterative solution can be performed to obtain the optimal value of the overlapping rate.
Fig. 7 is a flowchart illustrating a method for calculating a region of overlapping camera spectral ranges according to a third embodiment of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 7 if the results are substantially the same. As shown in fig. 7, the method includes the steps of:
step S701: and establishing an image plane coordinate system on the detector, and dividing the image plane into a plurality of uniform spectral band.
In this embodiment, step S701 in fig. 7 is similar to step S101 in fig. 1, and for brevity, is not described herein again.
Step S702: and acquiring first image surface characteristic points of the spectral band in an image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points.
In this embodiment, step S702 in fig. 7 is similar to step S102 in fig. 1, and is not repeated herein for brevity.
Step S703: the method comprises the steps of obtaining a first working condition of a camera and a satellite, establishing an image-object model according to the first working condition, and calculating ground characteristic points of characteristic points to be calculated under an earth inertia coordinate system through the image-object model.
In this embodiment, step S703 in fig. 7 is similar to step S103 in fig. 1, and for brevity, is not described herein again.
Step S704: and after the preset imaging interval time, acquiring a second working condition of the camera and the satellite, establishing an object-image model according to the second working condition, and calculating a second image surface characteristic point of the ground characteristic point in the image surface coordinate system through the object-image model.
In this embodiment, step S704 in fig. 7 is similar to step S104 in fig. 1, and for brevity, is not described herein again.
Step S705: and judging whether the region corresponding to the feature point to be calculated and the region corresponding to the second image surface feature point are overlapped along the vertical rail direction.
In step S705, when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point do not overlap in the vertical rail direction, step S706 is performed. When the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point overlap in the vertical rail direction, step S707 is executed.
Step S706: the preset imaging interval time is reduced and step S704 is re-executed.
Step S707: and acquiring an overlapping region between the spectral band where the characteristic point to be calculated is located and the adjacent spectral band.
In this embodiment, step S707 in fig. 7 is similar to step S105 in fig. 1, and for brevity, is not described herein again.
Step S708: and acquiring a third image surface characteristic point of the overlapping region, taking the third image surface characteristic point as a characteristic point to be calculated, and circularly executing the steps S703-S705 and S707 until an overlapping region between the spectral band where the characteristic point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
In this embodiment, step S708 in fig. 7 is similar to step S106 in fig. 1, and for brevity, is not described herein again.
The method for calculating the overlapping region of the camera spectral bands according to the third embodiment of the present invention optimizes the overlapping rate by adjusting the preset imaging interval time on the basis of the first embodiment,
fig. 8 is a schematic structural diagram of a computing device for overlapping coverage of camera spectral bands according to an embodiment of the present invention. As shown in fig. 8, the apparatus 80 includes a dividing module 81, a determining module 82, a first calculating module 83, a second calculating module 84, an obtaining module 85, and a loop calculating module 86.
The dividing module 81 is configured to establish an image plane coordinate system on the detector, and divide the image plane into a plurality of uniform spectral bands.
And the determining module 82 is used for acquiring first image surface characteristic points of the spectral band in the image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points.
And the first calculation module 83 is configured to acquire a first working condition of the camera and the satellite, establish an image-object model according to the first working condition, and calculate the ground feature point of the feature point to be calculated in the earth inertia coordinate system through the image-object model.
And a second calculating module 84, configured to obtain a second working condition of the camera and the satellite after a preset imaging interval time elapses, establish an object-image model according to the second working condition, and calculate a second image plane feature point of the ground feature point in the image plane coordinate system through the object-image model.
The obtaining module 85 is configured to obtain an overlapping region between a spectrum band where the feature point to be calculated is located and an adjacent spectrum band when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction.
And the circulating calculation module 86 is configured to acquire a third image surface feature point of the overlapping region, use the third image surface feature point as a feature point to be calculated, and circularly execute the steps executed by the first calculation module, the second calculation module and the acquisition module until an overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculate an overlapping rate of the overlapping region.
Referring to fig. 9, fig. 9 is a schematic structural diagram of a computer device according to an embodiment of the present invention. As shown in fig. 9, the computer device 90 includes a processor 91 and a memory 92 coupled to the processor 91.
The memory 92 stores program instructions for implementing the method for calculating the camera spectral band overlap region according to any of the embodiments described above.
The processor 91 is operative to execute program instructions stored by the memory 92 to calculate a camera spectral band overlap region.
The processor 91 may also be referred to as a CPU (Central Processing Unit). The processor 91 may be an integrated circuit chip having signal processing capabilities. The processor 91 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Referring to fig. 10, fig. 10 is a schematic structural diagram of a storage medium according to an embodiment of the invention. The storage medium of the embodiment of the present invention stores a program file 11 capable of implementing all the methods described above, where the program file 11 may be stored in the storage medium in the form of a software product, and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a portable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The above description is only an embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are included in the scope of the present invention.
Claims (10)
1. A method for calculating a region of overlapping camera spectral regions, comprising:
step S1: establishing an image plane coordinate system on a detector, and dividing an image plane into a plurality of uniform spectral band;
step S2: acquiring first image surface characteristic points of the spectral band under the image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points;
and step S3: acquiring a first working condition of the camera and the satellite, establishing an image-object model according to the first working condition, and calculating the ground characteristic point of the characteristic point to be calculated under the earth inertia coordinate system through the image-object model;
and step S4: after a preset imaging interval time, acquiring a second working condition of the camera and the satellite, establishing an object-image model according to the second working condition, and calculating a second image plane characteristic point of the ground characteristic point under the image plane coordinate system through the object-image model;
step S5: when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction, acquiring an overlapping region between a spectral band where the feature point to be calculated is located and an adjacent spectral band;
step S6: and acquiring a third image surface feature point of the overlapping region, taking the third image surface feature point as the feature point to be calculated, and executing the steps S3-S5 in a circulating manner until the overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
2. The computing method according to claim 1, further comprising, before step S5:
judging whether the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction;
and when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are not overlapped along the vertical rail direction, reducing the preset imaging interval time, and executing the step S4 again.
3. The calculation method according to claim 1, wherein in step S6, a ratio of an area of the overlap region to an area of any one of the spectral bands is calculated in the image plane coordinate system, and an overlap ratio of the overlap region is obtained.
4. The computing method according to claim 1, further comprising, after step S6:
step S7: and gradually increasing the preset imaging interval time, and circularly executing the steps S4-S6 until the overlapping rate is maximum.
5. The computing method according to claim 1, wherein step S3 further comprises:
calculating a first coordinate of the optical center of the camera under the earth inertial coordinate system according to the first working condition;
performing coordinate transformation of the image plane coordinate system and the earth inertia coordinate system according to the first coordinate, and calculating a second coordinate of the feature point to be calculated under the earth inertia coordinate system;
and calculating a first ground characteristic point of the characteristic point to be calculated under the earth inertia coordinate system according to the first coordinate and the second coordinate.
6. The computing method according to claim 5, wherein step S4 further comprises:
calculating a second ground characteristic point of the characteristic point to be calculated under the earth inertia coordinate system after the preset imaging interval time according to the first ground characteristic point, the preset imaging interval time and the second working condition;
calculating a third coordinate of the optical center of the camera under the earth inertial coordinate system according to the second working condition;
calculating a fourth coordinate of the feature point to be calculated in the earth inertial coordinate system after a preset imaging interval time;
and calculating a second image surface characteristic point corresponding to the first ground characteristic point in the image surface coordinate system according to the second ground characteristic point, the third coordinate and the fourth coordinate.
7. The method of claim 1, wherein the first operating condition and the second operating condition each comprise: the attitude angle of the satellite roll, the attitude angle of the satellite pitch, the attitude angle of the satellite yaw, the flight speed, the earth center distance of the satellite orbit, the orbit inclination angle, the amplitude angle of the satellite orbit, the latitude of the satellite point, the installation information of the focal plane of the camera, the focal length, the imaging mode and the rotation angular rate of the earth.
8. A computing device for overlapping coverage of camera spectral bands, comprising:
the dividing module is used for establishing an image plane coordinate system on the detector and dividing the image plane into a plurality of uniform spectral band strips;
the determining module is used for acquiring first image surface characteristic points of the spectral band under the image surface coordinate system and determining characteristic points to be calculated from the first image surface characteristic points;
the first calculation module is used for acquiring a first working condition of the camera and the satellite, establishing an image-object model according to the first working condition and calculating the ground characteristic point of the characteristic point to be calculated in an earth inertial coordinate system through the image-object model;
the second calculation module is used for acquiring a second working condition of the camera and the satellite after a preset imaging interval time, establishing an object-image model according to the second working condition and calculating a second image plane feature point of the ground feature point under the image plane coordinate system through the object-image model;
the acquisition module is used for acquiring an overlapping region between a spectral band where the feature point to be calculated is located and an adjacent spectral band when the region corresponding to the feature point to be calculated and the region corresponding to the second image plane feature point are overlapped along the vertical rail direction;
and the circulating calculation module is used for acquiring a third image surface feature point of the overlapping region, taking the third image surface feature point as the feature point to be calculated, circularly executing the steps executed by the first calculation module, the second calculation module and the acquisition module until the overlapping region between the spectral band where the feature point to be calculated is located and the last spectral band is acquired, and calculating the overlapping rate of the overlapping region.
9. A computer device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor when executing the computer program implements the method of calculating the camera spectral band overlap region according to any of the claims 1-7.
10. A storage medium characterized by storing a program file capable of implementing a method of calculating the camera spectral band overlap region according to any one of claims 1 to 7.
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