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Hyperspectral geometric correction method for UAV airborne imaging

A geometric correction and unmanned aerial vehicle technology, applied in the field of image processing, can solve the problems of difficult polynomial correction geometric fine correction, high POS accuracy requirements, increased costs, etc., to achieve the effect of improving the accuracy of POS information

Active Publication Date: 2018-12-11
天岸马科技(黑龙江)有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The load of the UAV is low, the stability of the platform is poor, and it is easily affected by airflow and wind speed. However, most hyperspectral imaging adopts the push-broom method, which makes the hyperspectral imaging affected by the attitude of the platform and has a large geometric distortion.
Subsequent geometric correction requires high-precision POS data, but due to the low load of the drone, it is impossible to carry high-precision POS equipment and other equipment
It has caused great difficulties to the practical application of UAV hyperspectral imaging
[0005] The currently used UAV geometric correction method generally simply uses ground control points for polynomial correction, but this method has high requirements for POS accuracy, and the accuracy is greatly affected by the control points
Some people use the frame camera to match and correct the hyperspectral image. However, due to the load of the drone, carrying the frame camera undoubtedly increases the cost and has certain limitations in application.
[0006] Existing low-cost small UAVs are only loaded with low-precision POS position sensors and push-broom hyperspectral imagers. Due to the influence of wind, the images obtained by correcting only based on POS data deviate too much from the actual ones. The distortion is still large, and it is difficult to perform geometric fine correction through polynomial correction, which cannot meet the actual use requirements

Method used

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specific Embodiment approach 1

[0020] The hyperspectral geometric correction method of drone airborne imaging of this embodiment combines figure 1 As shown, the method is implemented through the following steps:

[0021] Step 1: Obtain the POS data of the UAV's low-precision POS sensor: pitch angle Φ, roll angle Ω, azimuth angle Ψ, altitude h, and obtain the UAV GPS information at the same time;

[0022] Step 2: Correct the error of POS data caused by the deviation of the collimation axis;

[0023] Step 3: Preprocess the POS data and hyperspectral images according to the features of the ground features;

[0024] Step 4: Establish a ground coordinate system, and perform geometric correction of the collinear equation based on the corrected POS data;

[0025] Step 5. Ground reference point correction.

specific Embodiment approach 2

[0026] The difference from the first embodiment is that in the hyperspectral geometric correction method for drone airborne imaging in this embodiment, the process of correcting the POS data error caused by the collimation axis deviation in step 2 is:

[0027] Step 2: Use the standard calibration field to obtain the accurate position information of the standard reference object;

[0028] Step 2: Suppose the collimation axis deviation is (ex, ey, ez) and the POS data is (Φ, Ω, Ψ), then the orthogonal transformation matrix R formed by the image attitude angle is expressed as:

[0029]

[0030] Among them, ex is the rotation error in the X direction, ey is the rotation error in the Y direction, and ez is the rotation error in the Z direction;

[0031] It is the transformation matrix from the IMU coordinate system to the object coordinate system, including:

[0032]

[0033] For the transformation matrix from image space to IMU coordinates, there are:

[0034]

[0035] Step two and three, ...

specific Embodiment approach 3

[0039] The difference from the first or second embodiment is that in the hyperspectral geometric correction method for airborne imaging of drones in this embodiment, the process of preprocessing POS data and hyperspectral images according to feature characteristics in step 3 is: The accuracy of the POS attitude data is very low, resulting in large distortion of the ground objects. After the direct correction, the distortion of the ground objects is difficult to recover. Therefore, the following processing is performed on the POS attitude data, see figure 2 :

[0040] Step three: Carry out Kalman filtering on POS data, and carry out differential correction to GPS information; then according to latitude and longitude information

[0041] Calculate the distance between the abscissa and ordinate of the offset of the scan center relative to the initial scan center, and convert the unit to meters;.

[0042] Step 32: Obtain the corner point information of the hyperspectral image through th...

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Abstract

Hyperspectral geometric correction method for UAV airborne imaging. Belongs to the field of image processing. At present, the image obtained based on POS data correction deviates too much from the actual situation, and the scene points, lines, and surfaces are greatly distorted, and it is difficult to perform geometric precision correction through polynomial correction. The method of the invention includes: collecting the position and attitude information of the low-precision POS sensor of the current drone to correct the collimation axis error; preprocessing the POS data according to the corner points and contour information of the ground feature to obtain the corresponding external orientation elements; correcting the collinear equation ; Polynomial correction through ground correction points. This invention takes into account the relationship between the characteristics of natural features and the error of the sensor itself, improves the correction accuracy, and optimizes the low-precision POS data of drone aerial photography. The drone can carry out only low-precision POS sensors and hyperspectral imagers. The precise correction of aerial images provides technical support for the widespread application of current low-cost UAV hyperspectral imaging.

Description

Technical field [0001] The present invention relates to the technical field of image processing, in particular to a method for hyperspectral geometric correction of drone airborne imaging. Background technique [0002] In recent years, the spatial resolution and spectral resolution of imaging hyperspectral have become higher and higher, and it has played a great role in various fields such as agricultural automation and urban planning, and has huge development potential. The current collection of hyperspectral images mainly relies on satellites for collection. The satellite platform has relatively fixed orbits and can only acquire images at a fixed time. It cannot collect information on the spot in real time and is greatly affected by the weather. Requirements on the time resolution of the spectral image. [0003] UAVs have the advantages of high real-time performance, adaptability to various environments, and relatively low prices. With the development of UAV technology, the air...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T2207/30181G06T2207/10016G06T5/80
Inventor 谷延锋王腾飞
Owner 天岸马科技(黑龙江)有限公司
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