WO2022077239A1 - 摄像机参数的标定方法、图像处理方法、装置及存储介质 - Google Patents

摄像机参数的标定方法、图像处理方法、装置及存储介质 Download PDF

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Publication number
WO2022077239A1
WO2022077239A1 PCT/CN2020/120707 CN2020120707W WO2022077239A1 WO 2022077239 A1 WO2022077239 A1 WO 2022077239A1 CN 2020120707 W CN2020120707 W CN 2020120707W WO 2022077239 A1 WO2022077239 A1 WO 2022077239A1
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Prior art keywords
camera
calibration
parameters
lens
calibration parameters
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PCT/CN2020/120707
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English (en)
French (fr)
Inventor
张明磊
梁家斌
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深圳市大疆创新科技有限公司
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Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to CN202080015583.9A priority Critical patent/CN113490966B/zh
Priority to PCT/CN2020/120707 priority patent/WO2022077239A1/zh
Publication of WO2022077239A1 publication Critical patent/WO2022077239A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

Definitions

  • the present application relates to the technical field of camera calibration, and in particular, to a camera parameter calibration method, an image processing method, a device and a storage medium.
  • Camera calibration can be used to calculate the parameters required in the mathematical modeling process, including the camera's intrinsic parameters, extrinsic parameters or distortion parameters.
  • the existing camera calibration usually adopts the pre-calibration method, that is, in a specific calibration environment (usually arranged indoors, with a calibration board set at a fixed position), a camera is used to shoot a certain number of images in the calibration environment, and these images are used for calibration.
  • the calibration environment is very different from the application environment, and the calibration parameters calculated by using the images captured in the calibration environment will have errors; in addition, if the lens of the camera is an interchangeable lens, the replacement of the lens will cause a large change in the calibration parameters.
  • the present application provides a camera parameter calibration method, an image processing method, a device and a storage medium.
  • the present application provides a method for calibrating camera parameters, the camera is mounted on a drone, the camera includes a body and a lens, and the method includes:
  • the calibration parameters of the camera are calculated by using the plurality of images, and the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera;
  • the calibration parameters of the camera are transmitted to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identification of the camera.
  • the present application provides an image processing method for processing an image collected by a camera, where the camera includes a body and a lens, and the method includes:
  • the calibration parameter of the camera determines the calibration parameter of the camera corresponding to the lens identification, and the calibration parameter of the camera includes the internal parameter and/or the distortion parameter of the camera;
  • the calibration parameters of the camera are stored in association with the images collected by the camera.
  • the present application provides a camera parameter calibration device, the camera is mounted on a drone, the camera includes a body and a lens, and the device includes: a memory and a processor;
  • the memory is used to store computer programs
  • the processor is configured to execute the computer program and implement the following steps when executing the computer program:
  • the calibration parameters of the camera are calculated by using the plurality of images, and the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera;
  • the calibration parameters of the camera are transmitted to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identifier of the camera.
  • the present application provides an image processing device for processing images collected by a camera, the camera includes a body and a lens, and the device includes: a memory and a processor;
  • the memory is used to store computer programs
  • the processor is configured to execute the computer program and implement the following steps when executing the computer program:
  • the calibration parameter of the camera determines the calibration parameter of the camera corresponding to the lens identification, and the calibration parameter of the camera includes the internal parameter and/or the distortion parameter of the camera;
  • the calibration parameters of the camera are stored in association with the images collected by the camera.
  • the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor enables the processor to calibrate the camera parameters as described above method.
  • the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the image processing method as described above.
  • the embodiments of the present application provide a method for calibrating camera parameters, an image processing method, a device, and a storage medium.
  • the camera is mounted on the unmanned aerial vehicle.
  • the camera includes a body and a lens; the calibration parameters of the camera are calculated by using the plurality of images, and the calibration parameters of the camera include the internal parameters and/or distortion parameters of the camera; the calibration parameters of the camera are It is transmitted to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identifier of the camera.
  • the multiple images used to calculate the calibration parameters of the camera are collected by the camera mounted on the UAV during the movement of the UAV along the preset route, the scene of image collection used for calibration is closer to the actual application Therefore, calculating the calibration parameters of the camera by using multiple images collected in the calibration scene that is closer to the actual application scenario will help to improve the accuracy of the calibration parameters and help ensure the relative accuracy and stability of the calibration parameters;
  • the calibration parameters of the camera are transmitted to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identification of the camera, which is beneficial to realize the matching between the lens and the calibration parameters in the image acquisition system with interchangeable lenses.
  • the user can calibrate by himself, and establish the relationship between the new lens identification and the calibration parameters, without returning to the factory for calibration.
  • the calibration parameters of the camera corresponding to the lens identification are determined, and the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera;
  • the image collected; the calibration parameters of the camera are stored in association with the image collected by the camera. Since the lens is marked with the corresponding calibration parameters of the camera, after the image captured by the camera is acquired, the calibration parameters of the camera are stored in association with the image captured by the camera.
  • the lens can be
  • the collected images can correspond to the calibration parameters of the camera corresponding to the lens, which can avoid the separation of the calibration parameters from the images collected by the lens.
  • the calibration parameters of the corresponding camera can be obtained, so that a more accurate space can be established The mapping relationship between 3D points in and 2D points on the image.
  • FIG. 1 is a schematic flowchart of an embodiment of a method for calibrating camera parameters of the present application
  • FIG. 2 is a schematic flowchart of another embodiment of a method for calibrating camera parameters of the present application
  • FIG. 3 is a schematic flowchart of an embodiment of an image processing method of the present application.
  • FIG. 4 is a schematic structural diagram of an embodiment of an apparatus for calibrating camera parameters of the present application.
  • FIG. 5 is a schematic structural diagram of an embodiment of an image processing apparatus of the present application.
  • Camera calibration can be used to calculate the parameters required in the mathematical modeling process.
  • Existing camera calibration usually adopts a pre-calibration method, that is, in a specific calibration environment, a camera is used to capture a certain number of images of the calibration environment, and these images are used for calibration.
  • the calibration environment is very different from the application environment.
  • the camera is usually relatively far away from the object to be photographed when the drone is shooting, while the camera is usually relatively close to the calibration board during indoor pre-calibration, so the calculated calibration parameters will have errors; if The lens of the camera is an interchangeable lens, and the replacement of the lens will cause a large change in the calibration parameters, so that the unified calibration parameters cannot be used for all lenses, and the re-calibration needs to be returned to the factory.
  • the embodiments of the present application provide a method for calibrating camera parameters, an image processing method, a device, and a storage medium.
  • the camera is mounted on the unmanned aerial vehicle.
  • the camera includes a body and a lens; the calibration parameters of the camera are calculated by using the plurality of images, and the calibration parameters of the camera include the internal parameters and/or distortion parameters of the camera; the calibration parameters of the camera are It is transmitted to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identifier of the camera.
  • the multiple images used to calculate the calibration parameters of the camera are collected by the camera mounted on the UAV during the movement of the UAV along the preset route, the scene of image collection used for calibration is closer to the actual application Therefore, calculating the calibration parameters of the camera by using multiple images collected in the calibration scene that is closer to the actual application scenario will help to improve the accuracy of the calibration parameters and help ensure the relative accuracy and stability of the calibration parameters;
  • the calibration parameters of the camera are transmitted to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identification of the camera, which is beneficial to realize the matching between the lens and the calibration parameters in the image acquisition system with interchangeable lenses.
  • the user can calibrate by himself, and establish the relationship between the new lens identification and the calibration parameters, without returning to the factory for calibration.
  • the calibration parameters of the camera corresponding to the lens identification are determined, and the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera;
  • the image collected; the calibration parameters of the camera are stored in association with the image collected by the camera. Since the lens is marked with the corresponding calibration parameters of the camera, after the image captured by the camera is acquired, the calibration parameters of the camera are stored in association with the image captured by the camera.
  • the lens can be
  • the collected images can correspond to the calibration parameters of the camera corresponding to the lens, which can avoid the separation of the calibration parameters from the images collected by the lens.
  • the calibration parameters of the corresponding camera can be obtained, so that a more accurate space can be established The mapping relationship between 3D points in and 2D points on the image.
  • FIG. 1 is a schematic flowchart of an embodiment of a method for calibrating camera parameters of the present application.
  • the camera is mounted on a drone, and the camera includes a body and a lens.
  • the camera is mounted on the drone. When the drone moves, the camera moves with it.
  • the camera includes a body and a lens. The lens and the body can be fixed or detachable.
  • the method includes: step S101, step S102 and step S103.
  • Step S101 Acquire a plurality of images collected by the camera during the movement of the UAV along a preset route.
  • Step S102 Calculate and obtain calibration parameters of the camera by using the plurality of images, where the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera.
  • the camera when the camera captures images, the camera is mounted on the drone, and the drone moves along a preset route, and the camera captures multiple images in the process of following the movement of the drone.
  • the preset route may be a pre-planned route that facilitates the acquisition of multiple images that can improve the stability and accuracy of the calibration parameters. For example, the drone moves along a preset route, the orientation of the photosensitive elements when the camera captures images is not exactly the same, the orientation of the main optical axis of the camera is not exactly the same, the cameras are not at the same height when capturing images, and so on.
  • External parameters also called external parameter matrix
  • the external parameters can explain how points in the real world (such as points in the world coordinate system) are rotated and translated, and then fall into On a point in another real world (such as a point in the camera coordinate system);
  • internal parameters also known as internal parameter matrix
  • the internal parameters can indicate that after the above (1), the point that falls to another real world ( For example, the point of the camera coordinate system), how does it continue to pass through the lens of the camera and become pixel points through pinhole imaging and electronic conversion;
  • Distortion parameters also called distortion matrix
  • the distortion parameters can explain why the above one The pixel point does not fall in the position where the theoretical calculation should fall, and it also produces a certain offset and deformation.
  • the intrinsic parameters and distortion parameters are parameters related to the characteristics of the camera itself.
  • the calibration parameters of the camera calculated by using the plurality of images mainly include: internal parameters of the camera, or distortion parameters of the camera, or internal parameters and distortion parameters of the camera.
  • f x , f y are the focal lengths of the camera
  • x 0 , y 0 are the coordinates of the principal point of the image
  • s is the coordinate axis tilt parameter, ideally 0.
  • distortion is a shift from a straight line projection. To put it simply, theoretically a straight line projected onto the picture remains a straight line, but in fact a straight line projected onto the picture cannot remain a straight line, which is an optical distortion. Distortion can generally be divided into two categories, including radial distortion and tangential distortion.
  • Real lenses generally have radial distortion and tangential distortion.
  • the distortion parameters include radial distortion coefficients and tangential distortion coefficients, wherein k 1 , k 2 , and k 3 are radial distortion coefficients, and p 1 and p 2 are tangential distortion coefficients.
  • Radial distortion occurs in the process of converting the camera coordinate system to the physical coordinate system of the image, which is mainly caused by the shape of the lens, while tangential distortion occurs in the production process or assembly process of the camera, which is mainly due to the difference between the photoreceptor plane and the lens. caused by parallelism.
  • the scene of image capture used for calibration in this embodiment is closer to the actual application scenario, and the camera on the UAV can be far away from the shooting object, which is helpful. Because of covering the various positions of the sensor, the multiple images collected by the camera during the movement of the UAV along the preset route are obtained, and the multiple images collected in the calibration scene which is closer to the actual application scene are used to calculate The calibration parameters of the camera help to improve the accuracy of the calibration parameters and help to ensure the relative accuracy and stability of the calibration parameters.
  • Step S103 Transmit the calibration parameters of the camera to the camera, so that the camera stores the calibration parameters of the camera in association with the lens identifier of the camera.
  • the lens identifier can be an identifier that can uniquely identify the lens, for example, the lens model, production time, date of manufacture, etc., or a combination thereof, can be used as the lens identifier.
  • the calibration parameters of the camera are transmitted to the camera, so that the camera associates and stores the calibration parameters of the camera and the lens identification of the camera, which is beneficial to realize the difference between the lens and the calibration parameters in the image acquisition system with interchangeable lenses.
  • the matching between different lenses matches the corresponding calibration parameters, and further can also match the images captured by the lens.
  • the user can calibrate by himself, and establish the relationship between the new lens identification and the calibration parameters, without returning to the factory for calibration.
  • the embodiment of the present application acquires multiple images collected by the camera during the movement of the UAV along the preset route, the camera is mounted on the UAV, and the camera includes a body and a lens; the calibration of the camera is calculated by using the multiple images parameters, the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera; the calibration parameters of the camera are transmitted to the camera, so that the camera can compare the calibration parameters of the camera with the camera
  • the lens ID is stored associatively.
  • the multiple images used to calculate the calibration parameters of the camera are collected by the camera mounted on the UAV during the movement of the UAV along the preset route, the scene of image collection used for calibration is closer to the actual application In the scene, the camera on the drone can be far away from the shooting object, which helps to cover the various positions of the sensor. Therefore, using the multiple images collected in the calibration scene that is closer to the actual application scene to calculate the calibration parameters of the camera is helpful.
  • the plurality of images include a first image and a second image
  • the orientations of the photosensitive elements of the camera corresponding to the first image and the second image are different.
  • the principal optical axes of the cameras corresponding to the first image and the second image are oriented differently.
  • the heights of the cameras corresponding to the first image and the second image are different.
  • the photosensitive elements of the camera are uniformly oriented in the same direction, during the solution process using the aerial triangulation algorithm, there are multiple solutions for the calculation of the coordinates of the image principal point of the camera, and the image principal point cannot be correctly self-calibrated.
  • the photosensitive elements of the camera are not always oriented in one direction, and the photosensitive elements of the camera are oriented differently, which is closer to and matches the actual situation of the actual captured image. In this way, the calculated calibration parameters of the camera can be made more accurate and stable, and in particular, it can be helpful for the accurate and stable stabilization of the principal point coordinates x 0 and y 0 in the internal parameters of the camera.
  • the main optical axis of the camera is not always in one direction, and the height of the camera is not always maintained at the same height, which is closer to and matches the actual situation of collecting images, through In this way, the calculated calibration parameters of the camera can be made more accurate and stable, and in particular, it can help to make the focal lengths f x and f y in the internal parameters of the camera accurate and stable.
  • the positioning sensor on the drone can obtain position information.
  • the preset route is a curved route, a tic-tac-toe route or a circumnavigation route. Bending route, tic-tac-toe route, or circumnavigation route, the drone moves along the above-mentioned crooked route, tic-tac-toe route or circumnavigation route, the orientation of the photosensitive element when the camera captures images is not exactly the same, or the main optical axis of the camera is oriented Not exactly the same, or the cameras were not at the same height when the image was captured, etc.
  • the preset route can be: (1) at different flight heights, at a certain inclination angle (for example, the angle between the camera orientation and the vertical direction is 45 degrees or 30 degrees) or other angles); or, (2) acquisition of a five-way inclined flight path for 3D reconstruction; or, (3) a tilt flight path with a tic-tac-toe turning nose; or (4) a cloud-like flight during a tic-tac-toe flight
  • the stage swings in different directions, so that the camera on the head can shoot at a certain angle of inclination; and so on.
  • the shooting parameters when the camera collects the plurality of images meets preset shooting parameter requirements include: the focusing distance of the camera is greater than or equal to a preset distance threshold; The focal length of the camera remains unchanged; or, the shutter speed of the camera is greater than or equal to a preset speed threshold.
  • the shooting parameters can be parameters used by the camera when shooting images, such as shutter, focus distance, aperture, sensitivity (also known as ISO value), exposure value (EV, Exposure Value), whether to turn on the flash, etc.
  • the focusing distance refers to the distance between objects and images. In order to make the image clear, the camera needs to focus to make the image clear within a certain range of depth. The camera is mounted on the drone to collect images, usually far from the object to be photographed, and the photogrammetry specification clearly requires that the focus distance should be set to infinity for image acquisition in aerial surveys.
  • choosing a focus distance greater than or equal to the preset distance threshold helps to calibrate the scene closer to the application scene.
  • the images captured by the camera with the focal length unchanged, and the more stable calibration parameters of the camera are calculated by using these images.
  • the shutter speed of the camera is greater than or equal to the preset speed threshold, so that a clear image can be obtained and motion blur of the image can be reduced as much as possible.
  • the plurality of images are acquired by the camera using a global shutter or a mechanical shutter. In this way, the jelly effect of the imaging can be avoided.
  • the "jelly effect” is usually a phenomenon that occurs when shooting with rolling shutter.
  • the rolling shutter reads pixels in a line-by-line manner. If the object to be photographed moves or vibrates at a high speed relative to the camera, use the rolling shutter to shoot. If the line scan speed is insufficient, the result may appear “slanted”, “wobbly” or “partially exposed”.
  • the global shutter is the parallel reading of pixels on the entire sensor, so it can avoid the jelly effect of imaging.
  • the mechanical shutter can control the light entry time. When shooting fast-moving objects, the light entry time can be controlled very low, and the fast-moving objects can be easily grasped. Therefore, the mechanical shutter can also avoid the jelly effect of imaging.
  • the shooting scene when the camera collects the plurality of images meets the preset shooting scene requirements and the preset shooting scene requirements include: the lighting parameters of the shooting scene meet the preset lighting parameter requirements; or , the elevation parameters of the shooting scene meet the preset elevation parameter requirements.
  • the preset shooting scene requirements may refer to shooting scene requirements that help to collect multiple images that can improve the stability and accuracy of the calibration parameters.
  • the preset shooting scene requirements include but are not limited to: preset lighting parameter requirements, preset elevation parameter requirements, preset shooting object requirements, and so on.
  • the illumination parameters of the shooting scene meet the preset illumination parameter requirements, including but not limited to: the illumination should not be too bright nor too dark, and the image is not overexposed or the brightness is too dark, which is not conducive to calibrating the parameters.
  • the elevation parameter can reflect whether the shooting scene has the characteristics of ups and downs. It can be required that the ground surface has a certain level of ups and downs, such as an urban environment with artificial buildings, so that even if the absolute height of the camera remains unchanged, the height between the camera and the shooting object is changing.
  • the number of the plurality of images is greater than a preset number threshold.
  • the preset number threshold may be determined according to specific conditions, for example, the preset number threshold may be 300 sheets, 500 sheets, and the like.
  • the camera lens is replaceable.
  • the existing calibration method if the lens of the camera is detachable or replaceable, the disassembly or replacement of the lens will cause a large change in the calibration parameters of the camera, and there will be large errors in the parameters pre-calibrated in the factory.
  • the method of example because the calibration parameters of the camera are transmitted to the camera, so that the camera stores the calibration parameters of the camera and the lens identification of the camera in association, which is beneficial to realize the difference between the lens and the calibration parameter in the image acquisition system of the interchangeable lens.
  • the user can calibrate by himself, and establish the relationship between the new lens identification and the calibration parameters, without returning to the factory for calibration.
  • step S103 it is possible to check whether the accuracy of the calibration parameters meets the requirements for use, that is, step S103, before transmitting the calibration parameters of the camera to the camera, further It may include: step S104, as shown in FIG. 2 .
  • Step S104 Check whether the precision of the calibration parameter meets the usage requirements.
  • the transmitting the calibration parameters of the camera to the camera may include: if the accuracy of the calibration parameters of the camera meets the usage requirements, transmitting the calibration parameters of the camera to the camera.
  • the method may further include: if the accuracy of the calibration parameters of the camera does not meet the usage requirements, outputting prompt information, the prompt information is used to prompt the user to re-calibrate. Among them, when re-calibrating, you can change the shooting scene and choose the weather with better lighting.
  • a target point whose actual three-dimensional position is known can be preselected in the shooting scene.
  • the target point needs to be shot, and at least one of the multiple images includes the pixel point corresponding to the target point.
  • the target point can select the image control point and check point of the known three-dimensional position that has been deployed, which can reduce the cost and simplify the process.
  • the checking whether the accuracy of the calibration parameter meets the usage requirements may include: checking the accuracy of the calibration parameter by using the actual three-dimensional position of the target point and the pixel position of the pixel point corresponding to the target point meet the usage requirements.
  • the pixel position of the pixel point calculated by the target point can be obtained, and the calculated pixel position of the pixel point of the target point can be obtained.
  • the position is compared with the pixel position of the pixel corresponding to the target point in the captured image, and it is judged whether the error between the two meets the requirements for use. The accuracy does not meet the requirements for use.
  • the calibration parameters of the camera and the lens identifier of the camera are associated and stored in the storage space of the body in the form of a relationship list. In this way, it is helpful to find the corresponding calibration parameters according to the lens identification of the camera.
  • the lens identifier includes the SN code of the lens.
  • the SN code of the lens is the unique product serial number of the lens, which can uniquely identify the lens. It is usually written near the bayonet of the lens. Through the coding of this serial number, some basic information of the lens and the authenticity of the lens can be queried.
  • the SN code of the lens is used as the lens identification, which can uniquely identify the lens.
  • the transmitting the calibration parameters of the camera to the camera may include: transmitting the calibration parameters of the camera to the control device of the UAV, so that the unmanned The human-machine control device transmits the calibration parameters of the camera to the camera.
  • the control device is a remote controller
  • the device executing the method of this embodiment is a personal computer PC
  • the process of step S103 may be: the PC may first write the calibration parameters into the SD card, store the calibration parameters in the remote controller through the SD card, and then The remote control is transmitted to the drone by wired or wireless means; or, the PC is transferred to the remote control, and the remote control is forwarded to the drone by wired or wireless means; or the PC is directly transmitted to the drone by wireless or wired means UAV; alternatively, it can be transmitted to the UAV, the UAV can transmit it to the camera after receiving it, or it can be directly transmitted to the camera through the above method; and so on.
  • FIG. 3 is a schematic flowchart of an embodiment of the image processing method of the present application.
  • the image processing method of this embodiment is a method on the UAV side, which is used to process the images collected by the camera, that is, the calibration parameter transmission of the camera.
  • the method of performing correlation processing on the captured image After the camera stores the calibration parameters of the camera in association with the lens identifier of the camera, the method of performing correlation processing on the captured image.
  • the camera includes a body and a lens.
  • the content part of the above-mentioned camera parameter calibration method please refer to the content part of the above-mentioned camera parameter calibration method, which will not be repeated here.
  • the following mainly describes in detail the differences between the image processing method according to the embodiment of the present application and the above-mentioned camera parameter calibration method.
  • the method includes: step S201, step S202 and step S203.
  • Step S201 Determine the calibration parameters of the camera corresponding to the lens identification according to the lens identification of the camera, where the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera.
  • Step S202 Acquire an image captured by the camera.
  • Step S203 Associate and store the calibration parameters of the camera with the images collected by the camera.
  • the calibration parameters of the camera corresponding to the lens identification are determined according to the lens identification of the camera, and the calibration parameters of the camera include internal parameters and/or distortion parameters of the camera;
  • the image collected; the calibration parameters of the camera are stored in association with the image collected by the camera. Since the lens is marked with the corresponding calibration parameters of the camera, after the image captured by the camera is acquired, the calibration parameters of the camera are stored in association with the image captured by the camera. In this way, the lens can be
  • the collected images can correspond to the calibration parameters of the camera corresponding to the lens, which can avoid the separation of the calibration parameters from the images collected by the lens.
  • the calibration parameters of the corresponding camera can be obtained, so that a more accurate space can be established The mapping relationship between 3D points in and 2D points on the image.
  • step S203 the storing the calibration parameters of the camera in association with the images collected by the camera may include: storing the calibration parameters of the camera in the XMP field of the image and/or or the Eixf field.
  • XMP Extensible Metadata Platform
  • the extensible metadata platform is a set of standards for the creation, processing and exchange of metadata.
  • metadata such as title, abstract, author, copyright, etc. information
  • the metadata can be used to summarize, classify, search, etc., and various reference materials can also be obtained. , making the process very convenient.
  • XMP is a unified metadata standard.
  • the XMP field of the image is used to save the metadata of the image.
  • the calibration parameters of the camera are stored as metadata in the XMP field of the image, so as to facilitate the subsequent search for the calibration parameters of the camera through the metadata.
  • Eixf Exchangeable image file format
  • Exchangeable image file format is a file format specially set for digital camera photos, which can record the attribute information and shooting data of digital photos. There are fields that identify camera information and lens information.
  • the lens identifier includes the SN code of the lens.
  • the determining the calibration parameters of the camera according to the lens identification of the camera may include: determining the lens identification corresponding to the lens identification according to the lens identification of the camera and a relationship list.
  • Calibration parameters of the camera, the relationship list is used to indicate the corresponding relationship between the lens identifier and the calibration parameter.
  • the relationship list is stored in the storage space of the fuselage.
  • the method may further include: if the lens identifier does not exist in the relationship list, or if there is no calibration parameter of the camera corresponding to the lens identifier, calibrating The initial value of the parameter is stored in association with the image captured by the camera.
  • the initial value of the calibration parameter may be the calibration parameter calibrated when the camera leaves the factory, and is generally stored in a non-volatile storage medium inside the camera body when the camera leaves the factory. If there is no lens identifier in the relationship list, or there is no calibration parameter of the camera corresponding to the lens identifier, the initial value of the calibration parameter is stored in association with the image collected by the camera. When the image for calibration is collected and acquired, the image is stored in the initial value of the calibration parameter.
  • FIG. 4 is a schematic structural diagram of an embodiment of the camera parameter calibration device of the present application.
  • the camera is mounted on a drone, and the camera includes a body and a lens.
  • the camera parameters of this embodiment are The calibration device can perform the steps in the above-mentioned camera parameter calibration method.
  • the relevant content please refer to the relevant content of the above-mentioned camera parameter calibration method, which will not be repeated here.
  • the camera parameter calibration device 100 includes: a memory 1 and a processor 2; the processor 2 and the memory 1 are connected through a bus.
  • the processor 2 may be a microcontroller unit, a central processing unit or a digital signal processor, and so on.
  • the memory 1 may be a Flash chip, a read-only memory, a magnetic disk, an optical disk, a U disk, a mobile hard disk, or the like.
  • the memory 1 is used to store a computer program; the processor 2 is used to execute the computer program and implement the following steps when executing the computer program:
  • the multiple images include a first image and a second image, and the orientations of the photosensitive elements of the camera corresponding to the first image and the second image are different; or, the first image and the second image have different orientations;
  • the principal optical axes of the cameras corresponding to the two images are oriented differently; or the heights of the cameras corresponding to the first image and the second image are different.
  • the preset route is a curved route, a zigzag route or a circumnavigation route.
  • the shooting parameters when the camera collects the multiple images meet the preset shooting parameter requirements include: the focusing distance of the camera is greater than or equal to a preset distance threshold; the focal length of the camera unchanged; or the shutter speed of the camera is greater than or equal to a preset speed threshold.
  • the multiple images are acquired by the camera using a global shutter or a mechanical shutter.
  • the shooting scene when the camera collects the multiple images meets the preset shooting scene requirements
  • the preset shooting scene requirements include: the lighting parameters of the shooting scene meet the preset lighting parameter requirements; or the shooting scene The elevation parameters meet the preset elevation parameter requirements.
  • the number of the plurality of images is greater than a preset number threshold.
  • the lens of the camera can be replaced.
  • the processor when executing the computer program, implements the following steps: checking whether the accuracy of the calibration parameters meets the requirements for use; if the accuracy of the calibration parameters of the camera meets the requirements for use, calibrate the camera parameters are transmitted to the camera.
  • the processor when executing the computer program, implements the following steps: if the accuracy of the calibration parameters of the camera does not meet the usage requirements, output prompt information, where the prompt information is used to prompt the user to re-calibrate.
  • At least one of the multiple images includes a pixel point corresponding to a target point, and the actual three-dimensional position of the target point is known; when the processor executes the computer program, the processor implements the following steps: using the The actual three-dimensional position of the target point and the pixel position of the pixel point corresponding to the target point are used to check whether the accuracy of the calibration parameter meets the requirements for use.
  • the calibration parameters of the camera and the lens identifier of the camera are associated and stored in the storage space of the fuselage in the form of a relationship list.
  • the lens identifier includes the SN code of the lens.
  • the calibration device further includes a communication circuit, and when the processor executes the computer program, the processor implements the following steps: controlling the communication circuit to transmit the calibration parameters of the camera to the control device of the UAV, so that the control device of the drone transmits the calibration parameters of the camera to the camera.
  • FIG. 5 is a schematic structural diagram of an embodiment of an image processing apparatus of the present application.
  • the image processing apparatus is used to process images collected by a camera, and the camera includes a body and a lens.
  • the image processing apparatus of this embodiment may be mounted on a drone, and the image processing apparatus may be an intelligent device capable of processing images captured by a camera, or may be a camera with an image processing function. It should be noted that the image processing apparatus of this embodiment can execute the steps in the above-mentioned image processing method.
  • the relevant content please refer to the relevant content of the above-mentioned image processing method, which will not be repeated here.
  • the image processing apparatus 200 includes: a memory 11 and a processor 22; the processor 22 is connected to the memory 11 through a bus.
  • the processor 22 may be a microcontroller unit, a central processing unit or a digital signal processor, and so on.
  • the memory 11 may be a Flash chip, a read-only memory, a magnetic disk, an optical disk, a U disk, a mobile hard disk, or the like.
  • the memory 11 is used to store a computer program; the processor 22 is used to execute the computer program and implement the following steps when executing the computer program:
  • the calibration parameters of the camera include the internal parameters and/or distortion parameters of the camera; obtain the image collected by the camera;
  • the calibration parameters of the camera are stored in association with the images collected by the camera.
  • the processor when executing the computer program, implements the following steps: storing the calibration parameters of the camera in the XMP field and/or the Eixf field of the image.
  • the lens identifier includes the SN code of the lens.
  • the processor when executing the computer program, implements the following steps: determining the calibration parameters of the camera corresponding to the lens identification according to the lens identification of the camera and a relationship list, and the relationship list is used to indicate Correspondence between lens identification and calibration parameters.
  • the relationship list is stored in the storage space of the fuselage.
  • the processor when executing the computer program, implements the following steps: if there is no lens identifier in the relationship list, or there is no calibration parameter of the camera corresponding to the lens identifier, then the calibration parameter is The initial value is stored in association with the image captured by the camera.
  • the present application also provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor enables the processor to calibrate the camera parameters as described in any one of the above method.
  • the relevant content please refer to the above-mentioned relevant content section, which will not be repeated here.
  • the computer-readable storage medium may be an internal storage unit of the above-mentioned camera parameter calibration device, such as a hard disk or a memory.
  • the computer-readable storage medium may also be an external storage device, such as an equipped plug-in hard disk, smart memory card, secure digital card, flash memory card, and the like.
  • the present application also provides another computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the image processing method described in any one of the above .
  • the relevant content please refer to the above-mentioned relevant content section, which will not be repeated here.
  • the computer-readable storage medium may be an internal storage unit of the above-mentioned image processing apparatus, such as a hard disk or a memory.
  • the computer-readable storage medium may also be an external storage device, such as an equipped plug-in hard disk, smart memory card, secure digital card, flash memory card, and the like.

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Abstract

一种摄像机参数的标定方法、图像处理方法、装置及存储介质，该方法包括：获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像(S101)；利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数(S102)；将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储(S103)。

Description

摄像机参数的标定方法、图像处理方法、装置及存储介质 技术领域
本申请涉及摄像机标定技术领域，尤其涉及一种摄像机参数的标定方法、图像处理方法、装置及存储介质。
背景技术
立体视觉及三维重建相关领域中需要对摄像机成像的过程进行数学建模，以建立空间中的三维点与图像上的二维点之间的映射关系。摄像机标定可用于计算数学建模过程中所需的参数，包括摄像机的内参数、外参数或畸变参数。
现有的摄像机标定通常采用预标定方法，也即在特定的标定环境(通常布置在室内，在固定位置设置有标定板)中用摄像机对标定环境拍摄一定数量的图像，利用这些图像进行标定。但是，标定环境与应用环境差别大，利用标定环境下拍摄的图像计算得到的标定参数会有误差；此外，如果摄像机的镜头为可更换镜头，镜头更换会导致标定参数有较大变化，从而不能用统一的标定参数适用所有的镜头，对新的镜头进行重新标定需要返厂。
发明内容
基于此，本申请提供一种摄像机参数的标定方法、图像处理方法、装置及存储介质。
第一方面，本申请提供一种摄像机参数的标定方法，所述摄像机搭载于无人机，所述摄像机包括机身和镜头，所述方法包括：
获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像；
利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄 像机的标定参数与所述摄像机的镜头标识进行关联存储。
第二方面，本申请提供一种图像处理方法，用于处理摄像机采集的图像，所述摄像机包括机身和镜头，所述方法包括：
根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
获取所述摄像机所采集的图像；
将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。
第三方面，本申请提供一种摄像机参数的标定装置，所述摄像机搭载于无人机，所述摄像机包括机身和镜头，所述装置包括：存储器和处理器；
所述存储器用于存储计算机程序；
所述处理器用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像；
利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。
第四方面，本申请提供一种图像处理装置，用于处理摄像机采集的图像，所述摄像机包括机身和镜头，所述装置包括：存储器和处理器；
所述存储器用于存储计算机程序；
所述处理器用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
获取所述摄像机所采集的图像；
将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。
第五方面，本申请提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如上所述的摄像机参数的标定方法。
第六方面，本申请提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如上所述的图像处理方法。
本申请实施例提供了一种摄像机参数的标定方法、图像处理方法、装置及存储介质，一方面，获取无人机沿预设航线移动的过程中摄像机采集的多个图像，摄像机搭载于无人机，摄像机包括机身和镜头；利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。由于用来计算得到摄像机的标定参数的多个图像是搭载在无人机上的摄像机在无人机沿预设航线移动的过程中所采集的，用于标定的图像采集的场景更加贴近实际的应用场景，因此利用这种更加贴近实际的应用场景的标定场景下采集的多个图像计算摄像机的标定参数，有助于提高标定参数的精度，有助于保证标定参数的相对准确稳定；由于还将摄像机的标定参数传输给所述摄像机，以使得摄像机将摄像机的标定参数与摄像机的镜头标识进行关联存储，这有利于可更换镜头的图像采集***中实现镜头、标定参数之间的匹配。在更换新镜头的情况下，用户可以自行标定，建立新的镜头标识和标定参数的关联关系，而无需返厂标定。另一方面，根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；获取所述摄像机所采集的图像；将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。由于镜头标识有对应的所述摄像机的标定参数，获取到摄像机所采集的图像后，将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储，通过这种方式，能够使该镜头采集的图像均可以对应上该镜头对应的摄像机的标定参数，能够避免标定参数与该镜头采集的图像分离，当利用这些图像时即可得到对应的摄像机的标定参数，从而能够建立更加准确的空间中的三维点与图像上的二维点之间的映射关系。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本申请。
附图说明
为了更清楚地说明本申请实施例技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请摄像机参数的标定方法一实施例的流程示意图；
图2是本申请摄像机参数的标定方法另一实施例的流程示意图；
图3是本申请图像处理方法一实施例的流程示意图；
图4是本申请摄像机参数的标定装置一实施例的结构示意图；
图5是本申请图像处理装置一实施例的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
附图中所示的流程图仅是示例说明，不是必须包括所有的内容和操作/步骤，也不是必须按所描述的顺序执行。例如，有的操作/步骤还可以分解、组合或部分合并，因此实际执行的顺序有可能根据实际情况改变。
立体视觉及三维重建相关领域中需要对摄像机成像的过程进行数学建模，以建立空间中的三维点与图像上的二维点之间的映射关系。摄像机标定可用于计算数学建模过程中所需的参数。现有的摄像机标定通常采用预标定方法，也即在特定的标定环境中用摄像机对标定环境拍摄一定数量的图像，利用这些图像进行标定。但是，标定环境与应用环境差别大，无人机拍摄时摄像机通常距离被拍摄物体相对较远，而室内预标定时摄像机通常距离标定板相对较近，因此计算得到的标定参数会有误差；如果摄像机的镜头为可更换镜头，镜头更换会导致标定参数有较大变化，从而不能用统一的标定参数适用所有的镜头，重新标定需要返厂。
本申请实施例提供了一种摄像机参数的标定方法、图像处理方法、装置及存储介质，一方面，获取无人机沿预设航线移动的过程中摄像机采集的多个图像，摄像机搭载于无人机，摄像机包括机身和镜头；利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。由于用来计算得到摄像机的标定参数的多个图像是搭载在无人机上的摄像机在无人机沿预设航线移动的过程中所采集的，用于标定的图像采集的场景更加贴近实际的应用场景，因此利用这种更加贴近实际的应用场景的标定场景下采集的多个图像计算摄像机的标定参数，有助于提高标定参数的精度，有助于保证标定参数的相对准确稳定；由于还将摄像机的标定参数传输给所述摄像机，以使得摄像机将摄像机的标定参数与摄像机的镜头标识进行关联存储，这有利于可更换镜头的图像采集***中实现镜头、标定参数之间的匹配。在更换新镜头的情况下，用户可以自行标定，建立新的镜头标识和标定参数的关联关系，而无需返厂标定。另一方面，根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；获取所述摄像机所采集的图像；将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。由于镜头标识有对应的所述摄像机的标定参数，获取到摄像机所采集的图像后，将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储，通过这种方式，能够使该镜头采集的图像均可以对应上该镜头对应的摄像机的标定参数，能够避免标定参数与该镜头采集的图像分离，当利用这些图像时即可得到对应的摄像机的标定参数，从而能够建立更加准确的空间中的三维点与图像上的二维点之间的映射关系。
下面结合附图，对本申请的一些实施方式作详细说明。在不冲突的情况下，下述的实施例及实施例中的特征可以相互组合。
参见图1，图1是本申请摄像机参数的标定方法一实施例的流程示意图，所述摄像机搭载于无人机，所述摄像机包括机身和镜头。摄像机搭载于无人机，无人机移动时摄像机跟随移动，摄像机包括机身和镜头，镜头与机身可以是固定连接，也可以是可拆卸连接。
所述方法包括：步骤S101、步骤S102以及步骤S103。
步骤S101：获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像。
步骤S102：利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数。
本实施例中摄像机采集图像时，摄像机搭载在无人机上，且无人机沿预设航线移动，摄像机在跟随无人机移动的过程中采集多个图像。
预设航线可以是预先规划好的、有助于采集能够提高标定参数的稳定性和准确性的多个图像的航线。例如：无人机沿预设航线移动，摄像机采集图像时的感光元件的朝向不完全一致，摄像机的主光轴朝向不完全一致，采集图像时的摄像机不位于同一高度，等等。
通常情况下，通过摄像机标定可以知道:(1)外参数(也称为外参矩阵)，外参数可以说明现实世界的点(例如世界坐标系的点)是怎样经过旋转和平移，然后落到另一个现实世界的点(例如摄像机坐标系的点)上；(2)内参数(也称为内参矩阵)，内参数可以说明经过上述(1)后，那个落到另一个现实世界的点(例如摄像机坐标系的点)，是如何继续经过摄像机的镜头、并通过针孔成像和电子转化而成为像素点的；(3)畸变参数(也称为畸变矩阵)，畸变参数可以说明为什么上面那个像素点并没有落在理论计算该落在的位置上，还产生了一定的偏移和变形。其中，内参数和畸变参数是与摄像机自身特性相关的参数。本实施例中，利用所述多个图像计算得到的所述摄像机的标定参数主要包括：摄像机的内参数，或者摄像机的畸变参数，或者摄像机的内参数和畸变参数。
内参数包括如下：
Figure PCTCN2020120707-appb-000001
其中，f x，f y为摄像机的焦距，x 0、y 0为像主点坐标；s为坐标轴倾斜参数，理想情况下为0。
在几何光学和阴极射线管显示中，畸变是对直线投影的一种偏移。简单来 说，理论上一条直线投影到图片上也保持为一条直线，实际上一条直线投影到图片上不能保持为一条直线，这是一种光学畸变。畸变一般可以分为两大类，包括径向畸变和切向畸变。真实的镜头一般有径向畸变和切向畸变。畸变参数包括径向畸变系数和切向畸变系数，其中k 1、k 2、k 3是径向畸变系数，p 1、p 2是切向畸变系数。径向畸变发生在相机坐标系转图像物理坐标系的过程中，其主要是透镜形状引起的，而切向畸变是发生在摄像机的制作过程或组装过程，其主要是由于感光元平面跟透镜不平行引起的。
相比较于现有技术中标定摄像机时在特定的标定环境采集图像，本实施例用于标定的图像采集的场景更加贴近实际的应用场景，无人机上的摄像机可以距离拍摄物体较远，有助于覆盖传感器的各个位置，因此获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像，利用这种更加贴近实际的应用场景的标定场景下采集的多个图像计算摄像机的标定参数，有助于提高标定参数的精度，有助于保证标定参数的相对准确稳定。
步骤S103：将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。
镜头标识可以是能够唯一标识镜头的标识，例如可以采用镜头的型号、生产时间、出厂日期等，或者它们的组合，作为镜头标识。本实施例中，将摄像机的标定参数传输给所述摄像机，以使得摄像机将摄像机的标定参数与摄像机的镜头标识进行关联存储，这有利于可更换镜头的图像采集***中实现镜头、标定参数之间的匹配，不同的镜头匹配对应的标定参数，进一步还可以匹配该镜头拍摄的图像。在更换新镜头的情况下，用户可以自行标定，建立新的镜头标识和标定参数的关联关系，而无需返厂标定。
本申请实施例获取无人机沿预设航线移动的过程中摄像机采集的多个图像，摄像机搭载于无人机，摄像机包括机身和镜头；利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。由于用来计算得到摄像机的标定参数的多个图像是搭载在无人机上的摄像机在无人机沿预设航线移动的过程中所采集的，用于标定的图像采集的场景更加贴近实际 的应用场景，无人机上的摄像机可以距离拍摄物体较远，有助于覆盖传感器的各个位置，因此利用这种更加贴近实际的应用场景的标定场景下采集的多个图像计算摄像机的标定参数，有助于提高标定参数的精度，有助于保证标定参数的相对准确稳定；由于还将摄像机的标定参数传输给所述摄像机，以使得摄像机将摄像机的标定参数与摄像机的镜头标识进行关联存储，这有利于可更换镜头的图像采集***中实现镜头、标定参数之间的匹配，不同的镜头匹配对应的标定参数，还可以匹配该镜头拍摄的图像。在更换新镜头的情况下，用户可以自行标定，建立新的镜头标识和标定参数的关联关系，而无需返厂标定。
在一实施例中，所述多个图像包括第一图像和第二图像，所述第一图像和所述第二图像对应的所述摄像机的感光元件的朝向不同。或者，所述第一图像和所述第二图像对应的所述摄像机的主光轴朝向不同。或者，所述第一图像和所述第二图像对应的所述摄像机的高度不同。
如果摄像机的感光元件统一朝向统一方向，利用空中三角测量算法求解过程中，对摄像机的像主点坐标的计算存在多解，不能正确自标定出像主点。而且，在实际应用摄像机采集图像的过程中，摄像机的感光元件不总是朝着一个方向，所述摄像机的感光元件的朝向不同，这更加贴近、匹配具体的实际采集图像的情况，通过这种方式，能够使计算得到的摄像机的标定参数更加准确稳定，特别是能够有助于摄像机的内参数中像主点坐标x 0、y 0的准确稳定。
如果摄像机统一朝下(即主光轴的朝向一致)，并且在统一高度下采集图像，利用空中三角测量算法求解过程中，对摄像机焦距的计算存在多解，不能正确自标定出焦距。而且，在实际应用摄像机采集图像的过程中，摄像机的主光轴不总是朝着一个方向，摄像机的高度也不总是维持一个高度，这更加贴近、匹配具体的实际采集图像的情况，通过这种方式，能够使计算得到的摄像机的标定参数更加准确稳定，特别是能够有助于使摄像机的内参数中焦距f x，f y准确稳定。
在一实施例中，摄像机在不同高度采集图像时，无人机上的定位传感器可以获取位置信息。
在一实施例中，所述预设航线为弯折航线、井字型航线或者环绕航线。弯折航线、井字型航线或者环绕航线，无人机沿上述弯折航线、井字型航线或者 环绕航线移动，摄像机采集图像时的感光元件的朝向不完全一致，或者摄像机的主光轴朝向不完全一致，或者采集图像时的摄像机不在同一高度，等等。
例如：以无人机为例，具体应用时，预设航线可以是：(1)不同飞行高度的，以一定倾斜角度(例如摄像机朝向和竖直方向之间的夹角为45度或30度或者其他角度)的环绕航线；或者，(2)采集用于三维重建的五向倾斜航线；或者，(3)井字型掉转机头的倾斜航线；或者(4)井字型飞行过程中云台朝向不同方向摆动，使云台上的摄像机处于一定的倾斜角度拍摄；等等。
在一实施例中，所述摄像机采集所述多个图像时的拍摄参数满足预设拍摄参数要求，所述预设拍摄参数要求包括：所述摄像机的对焦距离大于或等于预设距离阈值；所述摄像机的焦距不变；或者，所述摄像机的快门速度大于或等于预设速度阈值。
拍摄参数可以是摄像机拍摄图像时使用的参数，如快门、对焦距离、光圈、感光度(又称为ISO值)、曝光值(EV，Exposure Value)、是否开闪光灯等。对焦距离是指物象之间的距离，摄像机成像时为了使成像清晰需要对焦使得一定范围的景深成像清晰。摄像机搭载在无人机上采集图像，通常距离拍摄物体较远，并且摄影测量规范中有明确要求航测中图像采集需要将对焦距离设置为无穷远。
因此在拍摄距离较远的拍摄物体时，选择对焦距离大于或等于预设距离阈值，有助于标定场景进一步贴近应用场景。所述摄像机的焦距不变拍摄得到的图像，利用这些图像计算得到更加稳定的摄像机的标定参数。所述摄像机的快门速度大于或等于预设速度阈值，能够获得清晰的图像，能够尽可能减少图像运动模糊。
在一实施例中，所述多个图像是所述摄像机利用全局快门或者机械快门采集得到的。通过这种方式，能够避免成像的果冻效应。
使用图像检测快速移动物体，当被检测物体从画面中快速经过时，物体像果冻一样产生明显的变形，这种现象就是所谓的“果冻效应”。“果冻效应”通常是卷帘快门方式拍摄出现的现象，卷帘快门读取像素点采用逐行的方式，如果被拍摄物体相对于摄像机高速运动或快速振动时，用卷帘快门方式拍摄，逐行扫描速度不够，拍摄结果就可能出现“倾斜”、“摇摆不定”或“部分曝 光”等情况。
全局快门则是整块传感器上的像素点并行读取，因此，能够避免成像的果冻效应。机械快门能够控制光线进入时间，在拍摄快速移动物体时，可以将光线进入时间控制很低，能够轻松抓住急速移动的物体，因此采用机械快门也能够避免成像的果冻效应。
在一实施例中，所述摄像机采集所述多个图像时的拍摄场景满足预设拍摄场景要求，所述预设拍摄场景要求包括：所述拍摄场景的光照参数满足预设光照参数要求；或者，所述拍摄场景的高程参数满足预设高程参数要求。
预设拍摄场景要求可以是指有助于采集能够提高标定参数的稳定性和准确性的多个图像的拍摄场景要求。预设拍摄场景要求包括但不限于：预设光照参数要求、预设高程参数要求、预设拍摄物体要求，等等。所述拍摄场景的光照参数满足预设光照参数要求，包括但不限于：光照不宜过亮也不宜过暗，图像过曝或者亮度太暗都不利于标定参数。高程参数可以体现拍摄场景是否具有高低起伏的特性，可以要求地表有一定高低起伏的场景，例如有人工建筑的城市环境，这样即使摄像机的绝对高度不变，但是摄像机与拍摄物体之间的高度是变化的。
在一实施例中，为获得较好的标定精度，所述多个图像的数量大于预设数量阈值。预设数量阈值可以根据具体情况确定，例如预设数量阈值可以为300张、500张，等等。
在一实施例中，所述摄像机的镜头可更换。采用现有的标定方法，如果摄像机的镜头为可拆卸或者可更换镜头，镜头拆卸或更换镜头会导致摄像机的标定参数有较大变化，出厂预先标定的参数会存在较大误差；通过本申请实施例的方法，由于将摄像机的标定参数传输给所述摄像机，以使得摄像机将摄像机的标定参数与摄像机的镜头标识进行关联存储，这有利于可更换镜头的图像采集***中实现镜头、标定参数之间的匹配，在更换新镜头的情况下，用户可以自行标定，建立新的镜头标识和标定参数的关联关系，而无需返厂标定。
为了保证后续能够更好地利用标定出来的摄像机的标定参数，可以检验所述标定参数的精度是否满足使用要求，即步骤S103，所述将所述摄像机的标定参数传输给所述摄像机之前，还可以包括：步骤S104，如图2所示。
步骤S104：检验所述标定参数的精度是否满足使用要求。
此时步骤S103，所述将所述摄像机的标定参数传输给所述摄像机，可以包括：若所述摄像机的标定参数的精度满足使用要求，则将所述摄像机的标定参数传输给所述摄像机。
若精度不满足使用要求，则可以重新标定，即所述方法还可以包括：若所述摄像机的标定参数的精度不满足使用要求，则输出提示信息，所述提示信息用于提示用户重新标定。其中重新标定时，可以更换拍摄场景及选择光照更好的天气。
为了检验标定参数的精度，可以在拍摄场景中预先选择实际三维位置已知的目标点，在拍摄图像时，需要拍摄目标点，多个图像中的至少一个图像中包括目标点对应的像素点。其中，目标点可以选择已经布控好的已知三维位置的像控点、检查点，能够减少成本，简化流程。
此时步骤S104，所述检验所述标定参数的精度是否满足使用要求，可以包括：利用所述目标点的实际三维位置和所述目标点对应的像素点的像素位置检验所述标定参数的精度是否满足使用要求。
已知目标点的实际三维位置，通过计算得到的摄像机的外参数、内参数、畸变参数，可以得到所述目标点计算出来的像素点的像素位置，将计算出来的目标点的像素点的像素位置和拍摄的图像中目标点对应的像素点的像素位置进行比较，判断两者之间的误差是否满足使用要求，如果满足，则所述标定参数的精度满足使用要求，否则所述标定参数的精度不满足使用要求。
在一实施例中，所述摄像机的标定参数与所述摄像机的镜头标识以关系列表的形式关联存储于所述机身的存储空间。通过这种方式，有助于根据摄像机的镜头标识，查找到对应的标定参数。
其中，所述镜头标识包括所述镜头的SN码。镜头的SN码就是镜头唯一的产品序列号，能够唯一标识镜头，一般会写在镜头的卡口附近，通过这个序列号的编码形式可以查询到镜头的一些基本信息以及镜头的真伪。采用镜头的SN码作为镜头标识，能够唯一识别镜头。
在一实施例中，步骤S103，所述将所述摄像机的标定参数传输给所述摄像机，可以包括：将所述摄像机的标定参数传输给所述无人机的控制装置，以 使得所述无人机的控制装置将所述摄像机的标定参数传输给所述摄像机。例如：控制装置为遥控器，执行本实施例方法的设备为个人计算机PC，步骤S103的过程可以是：PC可以先将标定参数写入SD卡，通过SD卡将标定参数存入遥控器，再由遥控器通过有线或者无线的方式传输给无人机；或者，PC中转到遥控器，由遥控器通过有线或者无线的方式转发给无人机；或者，PC直接通过无线或有线的方式传输给无人机；或者，可以传给无人机，无人机接收之后传输给摄像机，也可以通过上述方式直接传输给摄像机；等等。
参见图3，图3是本申请图像处理方法一实施例的流程示意图，本实施例的图像处理方法是无人机侧的方法，用于处理摄像机采集的图像，即所述摄像机的标定参数传输给所述摄像机，摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储后，对拍摄的图像进行相关处理的方法。所述摄像机包括机身和镜头。本申请实施例图像处理方法与上述的摄像机参数的标定方法中相同的内容的详细说明请参见上述摄像机参数的标定方法内容部分，在此不再赘叙。下面主要详细说明本申请实施例图像处理方法与上述的摄像机参数的标定方法中不相同的内容。
所述方法包括：步骤S201、步骤S202以及步骤S203。
步骤S201：根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数。
步骤S202：获取所述摄像机所采集的图像。
步骤S203：将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。
本申请实施例根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；获取所述摄像机所采集的图像；将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。由于镜头标识有对应的所述摄像机的标定参数，获取到摄像机所采集的图像后，将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储，通过这种方式，能够使该镜头采集的图像均可以对应上该镜头对应的摄像机的标定参数，能够避免标定参数与该镜头采集的图像 分离，当利用这些图像时即可得到对应的摄像机的标定参数，从而能够建立更加准确的空间中的三维点与图像上的二维点之间的映射关系。
在一实施例中，步骤S203，所述将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储，可以包括：将所述摄像机的标定参数存入所述图像的XMP字段和/或Eixf字段。
XMP(Extensible Metadata Platform)：可延伸元数据平台，是关于元数据的创建、处理和交换的一套标准。在制作和管理文档或图像时，如果在相关文件中包含有元数据(如标题、摘要、作者、版权等信息)则可以通过元数据来归纳、分类、搜索等，也能获得各种参考资料，使处理过程变得很方便。XMP是统一的元数据标准。图像的XMP字段用于保存图像的元数据，本申请实施例将所述摄像机的标定参数作为元数据保存在图像的XMP字段，方便后续通过元数据搜索摄像机的标定参数。
Eixf(Exchangeable image file format)：可交换图像文件格式，是专门为数码相机的照片设定的文件格式，可以记录数码照片的属性信息和拍摄数据。其中有标识相机信息和镜头信息的字段。
其中，所述镜头标识包括所述镜头的SN码。
在一实施例中，步骤S201，所述根据所述摄像机的镜头标识，确定所述摄像机的标定参数，可以包括：根据所述摄像机的镜头标识和关系列表，确定所述镜头标识对应的所述摄像机的标定参数，所述关系列表用于指示镜头标识与标定参数的对应关系。可选的，所述关系列表存储于所述机身的存储空间。
如果所述关系列表中没有所述镜头标识，则所述方法还可以包括：若所述关系列表中没有所述镜头标识，或者没有所述镜头标识对应的所述摄像机的标定参数，则将标定参数的初始值与所述摄像机所采集的图像进行关联存储。
标定参数的初始值可以是摄像机出厂时标定好的标定参数，一般在摄像机出厂时存储在摄像机机身内部的非易失存储介质中。若关系列表中没有所述镜头标识，或者没有所述镜头标识对应的所述摄像机的标定参数，则将标定参数的初始值与所述摄像机所采集的图像进行关联存储。在采集并获取用于标定的图像时，图像存入的就是标定参数的初始值。
参见图4，图4是本申请摄像机参数的标定装置一实施例的结构示意图， 所述摄像机搭载于无人机，所述摄像机包括机身和镜头，需要说明的是，本实施例的摄像机参数的标定装置能够执行上述摄像机参数的标定方法中的步骤，相关内容的详细说明，请参见上述摄像机参数的标定方法的相关内容，在此不再赘叙。
所述摄像机参数的标定装置100包括：存储器1和处理器2；处理器2与存储器1通过总线连接。
其中，处理器2可以是微控制单元、中央处理单元或数字信号处理器，等等。
其中，存储器1可以是Flash芯片、只读存储器、磁盘、光盘、U盘或者移动硬盘等等。
所述存储器1用于存储计算机程序；所述处理器2用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像；利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。
其中，所述多个图像包括第一图像和第二图像，所述第一图像和所述第二图像对应的所述摄像机的感光元件的朝向不同；或者，所述第一图像和所述第二图像对应的所述摄像机的主光轴朝向不同；或者所述第一图像和所述第二图像对应的所述摄像机的高度不同。
其中，所述预设航线为弯折航线、井字型航线或者环绕航线。
其中，所述摄像机采集所述多个图像时的拍摄参数满足预设拍摄参数要求，所述预设拍摄参数要求包括：所述摄像机的对焦距离大于或等于预设距离阈值；所述摄像机的焦距不变；或者所述摄像机的快门速度大于或等于预设速度阈值。
其中，所述多个图像是所述摄像机利用全局快门或者机械快门采集得到的。
其中，所述摄像机采集所述多个图像时的拍摄场景满足预设拍摄场景要 求，所述预设拍摄场景要求包括：所述拍摄场景的光照参数满足预设光照参数要求；或者所述拍摄场景的高程参数满足预设高程参数要求。
其中，所述多个图像的数量大于预设数量阈值。
其中，所述摄像机的镜头可更换。
其中，所述处理器在执行所述计算机程序时，实现如下步骤：检验所述标定参数的精度是否满足使用要求；若所述摄像机的标定参数的精度满足使用要求，则将所述摄像机的标定参数传输给所述摄像机。
其中，所述处理器在执行所述计算机程序时，实现如下步骤：若所述摄像机的标定参数的精度不满足使用要求，则输出提示信息，所述提示信息用于提示用户重新标定。
其中，所述多个图像中的至少一个图像中包括目标点对应的像素点，所述目标点的实际三维位置已知；所述处理器在执行所述计算机程序时，实现如下步骤：利用所述目标点的实际三维位置和所述目标点对应的像素点的像素位置检验所述标定参数的精度是否满足使用要求。
其中，所述摄像机的标定参数与所述摄像机的镜头标识以关系列表的形式关联存储于所述机身的存储空间。
其中，所述镜头标识包括所述镜头的SN码。
其中，所述标定装置还包括通信电路，所述处理器在执行所述计算机程序时，实现如下步骤：控制所述通信电路将所述摄像机的标定参数传输给所述无人机的控制装置，以使得所述无人机的控制装置将所述摄像机的标定参数传输给所述摄像机。
参见图5，图5是本申请图像处理装置一实施例的结构示意图，该图像处理装置用于处理摄像机采集的图像，所述摄像机包括机身和镜头。本实施例的图像处理装置可搭载在无人机上，所述图像处理装置可以是能够对摄像机所拍摄的图像进行处理的智能设备，或者也可以是带有图像处理功能的摄像机。需要说明的是，本实施例的图像处理装置能够执行上述图像处理方法中的步骤，相关内容的详细说明，请参见上述图像处理方法的相关内容，在此不再赘叙。
所述图像处理装置200包括：存储器11和处理器22；处理器22与存储器11通过总线连接。
其中，处理器22可以是微控制单元、中央处理单元或数字信号处理器，等等。
其中，存储器11可以是Flash芯片、只读存储器、磁盘、光盘、U盘或者移动硬盘等等。
所述存储器11用于存储计算机程序；所述处理器22用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；获取所述摄像机所采集的图像；将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。
其中，所述处理器在执行所述计算机程序时，实现如下步骤：将所述摄像机的标定参数存入所述图像的XMP字段和/或Eixf字段。
其中，所述镜头标识包括所述镜头的SN码。
其中，所述处理器在执行所述计算机程序时，实现如下步骤：根据所述摄像机的镜头标识和关系列表，确定所述镜头标识对应的所述摄像机的标定参数，所述关系列表用于指示镜头标识与标定参数的对应关系。
其中，所述关系列表存储于所述机身的存储空间。
其中，所述处理器在执行所述计算机程序时，实现如下步骤：若所述关系列表中没有所述镜头标识，或者没有所述镜头标识对应的所述摄像机的标定参数，则将标定参数的初始值与所述摄像机所采集的图像进行关联存储。
本申请还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如上任一项所述的摄像机参数的标定方法。相关内容的详细说明请参见上述相关内容部分，在此不再赘叙。
其中，该计算机可读存储介质可以是上述摄像机参数的标定装置的内部存储单元，例如硬盘或内存。该计算机可读存储介质也可以是外部存储设备，例如配备的插接式硬盘、智能存储卡、安全数字卡、闪存卡，等等。
本申请还提供另一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如上任一项 所述的图像处理方法。相关内容的详细说明请参见上述相关内容部分，在此不再赘叙。
其中，该计算机可读存储介质可以是上述图像处理装置的内部存储单元，例如硬盘或内存。该计算机可读存储介质也可以是外部存储设备，例如配备的插接式硬盘、智能存储卡、安全数字卡、闪存卡，等等。
应当理解，在本申请说明书中所使用的术语仅仅是出于描述特定实施例的目的而并不意在限制本申请。
还应当理解，在本申请说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
以上所述，仅为本申请的具体实施例，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (42)

  1. 一种摄像机参数的标定方法，其特征在于，所述摄像机搭载于无人机，所述摄像机包括机身和镜头，所述方法包括：
    获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像；
    利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
    将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。
  2. 根据权利要求1所述的方法，其特征在于，所述多个图像包括第一图像和第二图像，所述第一图像和所述第二图像对应的所述摄像机的感光元件的朝向不同；或者，所述第一图像和所述第二图像对应的所述摄像机的主光轴朝向不同；或者所述第一图像和所述第二图像对应的所述摄像机的高度不同。
  3. 根据权利要求1所述的方法，其特征在于，所述预设航线为弯折航线、井字型航线或者环绕航线。
  4. 根据权利要求1所述的方法，其特征在于，所述摄像机采集所述多个图像时的拍摄参数满足预设拍摄参数要求，所述预设拍摄参数要求包括：
    所述摄像机的对焦距离大于或等于预设距离阈值；
    所述摄像机的焦距不变；或者
    所述摄像机的快门速度大于或等于预设速度阈值。
  5. 根据权利要求1所述的方法，其特征在于，所述多个图像是所述摄像机利用全局快门或者机械快门采集得到的。
  6. 根据权利要求1所述的方法，其特征在于，所述摄像机采集所述多个图像时的拍摄场景满足预设拍摄场景要求，所述预设拍摄场景要求包括：
    所述拍摄场景的光照参数满足预设光照参数要求；或者
    所述拍摄场景的高程参数满足预设高程参数要求。
  7. 根据权利要求1所述的方法，其特征在于，所述多个图像的数量大于预设数量阈值。
  8. 根据权利要求1所述的方法，其特征在于，所述摄像机的镜头可更换。
  9. 根据权利要求1所述的方法，其特征在于，所述将所述摄像机的标定参数传输给所述摄像机之前，还包括：
    检验所述标定参数的精度是否满足使用要求；
    所述将所述摄像机的标定参数传输给所述摄像机，包括：
    若所述摄像机的标定参数的精度满足使用要求，则将所述摄像机的标定参数传输给所述摄像机。
  10. 根据权利要求9所述的方法，其特征在于，所述方法还包括：
    若所述摄像机的标定参数的精度不满足使用要求，则输出提示信息，所述提示信息用于提示用户重新标定。
  11. 根据权利要求9所述的方法，其特征在于，所述多个图像中的至少一个图像中包括目标点对应的像素点，所述目标点的实际三维位置已知；
    所述检验所述标定参数的精度是否满足使用要求，包括：
    利用所述目标点的实际三维位置和所述目标点对应的像素点的像素位置检验所述标定参数的精度是否满足使用要求。
  12. 根据权利要求1所述的方法，其特征在于，所述摄像机的标定参数与所述摄像机的镜头标识以关系列表的形式关联存储。
  13. 根据权利要求1所述的方法，其特征在于，所述摄像机的标定参数与所述摄像机的镜头标识关联存储于所述机身的存储空间。
  14. 根据权利要求1所述的方法，其特征在于，所述镜头标识包括所述镜头的SN码。
  15. 根据权利要求1所述的方法，其特征在于，所述将所述摄像机的标定参数传输给所述摄像机，包括：
    将所述摄像机的标定参数传输给所述无人机的控制装置，以使得所述无人机的控制装置将所述摄像机的标定参数传输给所述摄像机。
  16. 一种图像处理方法，用于处理摄像机采集的图像，所述摄像机包括机身和镜头，其特征在于，所述方法包括：
    根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
    获取所述摄像机所采集的图像；
    将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。
  17. 根据权利要求16所述的方法，其特征在于，所述将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储，包括：
    将所述摄像机的标定参数存入所述图像的XMP字段和/或Ei xf字段。
  18. 根据权利要求16所述的方法，其特征在于，所述根据所述摄像机的镜头标识，确定所述摄像机的标定参数，包括：
    根据所述摄像机的镜头标识和关系列表，确定所述镜头标识对应的所述摄像机的标定参数，所述关系列表用于指示镜头标识与标定参数的对应关系。
  19. 根据权利要求18所述的方法，其特征在于，所述关系列表存储于所述机身的存储空间。
  20. 根据权利要求19所述的方法，其特征在于，所述方法还包括：
    若所述关系列表中没有所述镜头标识，或者没有所述镜头标识对应的所述摄像机的标定参数，则将标定参数的初始值与所述摄像机所采集的图像进行关联存储。
  21. 一种摄像机参数的标定装置，其特征在于，所述摄像机搭载于无人机，所述摄像机包括机身和镜头，所述装置包括：存储器和处理器；
    所述存储器用于存储计算机程序；
    所述处理器用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
    获取所述无人机沿预设航线移动的过程中所述摄像机采集的多个图像；
    利用所述多个图像计算得到所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
    将所述摄像机的标定参数传输给所述摄像机，以使得所述摄像机将所述摄像机的标定参数与所述摄像机的镜头标识进行关联存储。
  22. 根据权利要求21所述的装置，其特征在于，所述多个图像包括第一图像和第二图像，所述第一图像和所述第二图像对应的所述摄像机的感光元件的朝向不同；或者，所述第一图像和所述第二图像对应的所述摄像机的主光轴朝向不同；或者所述第一图像和所述第二图像对应的所述摄像机的高度不同。
  23. 根据权利要求21所述的装置，其特征在于，所述预设航线为弯折航 线、井字型航线或者环绕航线。
  24. 根据权利要求21所述的装置，其特征在于，所述摄像机采集所述多个图像时的拍摄参数满足预设拍摄参数要求，所述预设拍摄参数要求包括：
    所述摄像机的对焦距离大于或等于预设距离阈值；
    所述摄像机的焦距不变；或者
    所述摄像机的快门速度大于或等于预设速度阈值。
  25. 根据权利要求21所述的装置，其特征在于，所述多个图像是所述摄像机利用全局快门或者机械快门采集得到的。
  26. 根据权利要求21所述的装置，其特征在于，所述摄像机采集所述多个图像时的拍摄场景满足预设拍摄场景要求，所述预设拍摄场景要求包括：
    所述拍摄场景的光照参数满足预设光照参数要求；或者
    所述拍摄场景的高程参数满足预设高程参数要求。
  27. 根据权利要求21所述的装置，其特征在于，所述多个图像的数量大于预设数量阈值。
  28. 根据权利要求21所述的装置，其特征在于，所述摄像机的镜头可更换。
  29. 根据权利要求21所述的装置，其特征在于，所述处理器在执行所述计算机程序时，实现如下步骤：
    检验所述标定参数的精度是否满足使用要求；
    若所述摄像机的标定参数的精度满足使用要求，则将所述摄像机的标定参数传输给所述摄像机。
  30. 根据权利要求29所述的装置，其特征在于，所述处理器在执行所述计算机程序时，实现如下步骤：
    若所述摄像机的标定参数的精度不满足使用要求，则输出提示信息，所述提示信息用于提示用户重新标定。
  31. 根据权利要求29所述的装置，其特征在于，所述多个图像中的至少一个图像中包括目标点对应的像素点，所述目标点的实际三维位置已知；
    所述处理器在执行所述计算机程序时，实现如下步骤：
    利用所述目标点的实际三维位置和所述目标点对应的像素点的像素位置 检验所述标定参数的精度是否满足使用要求。
  32. 根据权利要求21所述的装置，其特征在于，所述摄像机的标定参数与所述摄像机的镜头标识以关系列表的形式关联存储。
  33. 根据权利要求21所述的装置，其特征在于，所述摄像机的标定参数与所述摄像机的镜头标识关联存储于所述机身的存储空间。
  34. 根据权利要求21所述的装置，其特征在于，所述镜头标识包括所述镜头的SN码。
  35. 根据权利要求21所述的装置，其特征在于，所述标定装置还包括通信电路，所述处理器在执行所述计算机程序时，实现如下步骤：
    控制所述通信电路将所述摄像机的标定参数传输给所述无人机的控制装置，以使得所述无人机的控制装置将所述摄像机的标定参数传输给所述摄像机。
  36. 一种图像处理装置，用于处理摄像机采集的图像，所述摄像机包括机身和镜头，其特征在于，所述装置包括：存储器和处理器；
    所述存储器用于存储计算机程序；
    所述处理器用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
    根据所述摄像机的镜头标识，确定所述镜头标识对应的所述摄像机的标定参数，所述摄像机的标定参数包括所述摄像机的内参数和/或畸变参数；
    获取所述摄像机所采集的图像；
    将所述摄像机的标定参数与所述摄像机所采集的图像进行关联存储。
  37. 根据权利要求36所述的装置，其特征在于，所述处理器在执行所述计算机程序时，实现如下步骤：
    将所述摄像机的标定参数存入所述图像的XMP字段和/或Ei xf字段。
  38. 根据权利要求36所述的装置，其特征在于，所述处理器在执行所述计算机程序时，实现如下步骤：
    根据所述摄像机的镜头标识和关系列表，确定所述镜头标识对应的所述摄像机的标定参数，所述关系列表用于指示镜头标识与标定参数的对应关系。
  39. 根据权利要求38所述的装置，其特征在于，所述关系列表存储于所 述机身的存储空间。
  40. 根据权利要求39所述的装置，其特征在于，所述处理器在执行所述计算机程序时，实现如下步骤：
    若所述关系列表中没有所述镜头标识，或者没有所述镜头标识对应的所述摄像机的标定参数，则将标定参数的初始值与所述摄像机所采集的图像进行关联存储。
  41. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如权利要求1-15任一项所述的摄像机参数的标定方法。
  42. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如权利要求16-20任一项所述的图像处理方法。
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