CN102645209B - Joint positioning method for spatial points by means of onboard LiDAR point cloud and high resolution images - Google Patents

Joint positioning method for spatial points by means of onboard LiDAR point cloud and high resolution images Download PDF

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CN102645209B
CN102645209B CN201210122111.0A CN201210122111A CN102645209B CN 102645209 B CN102645209 B CN 102645209B CN 201210122111 A CN201210122111 A CN 201210122111A CN 102645209 B CN102645209 B CN 102645209B
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cloud
ball
points
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CN102645209A (en
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钟良
马力
汤璇
支晓栋
刘鹏飞
刘永亮
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CHANGJIANG SPACE INFORMATION TECHNOLOGY ENGINEERING Co Ltd (WUHAN)
Changjiang Institute of Survey Planning Design and Research Co Ltd
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CHANGJIANG SPACE INFORMATION TECHNOLOGY ENGINEERING Co Ltd (WUHAN)
Changjiang Institute of Survey Planning Design and Research Co Ltd
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Abstract

A joint positioning method for spatial points by means of onboard LiDAR point cloud and high resolution images includes the steps: denoising original LiDAR data; generating a high-precision DEM (digital elevation model); manually supplementing elements of exterior orientation of images acquired by high-precision POS (point-of-sale) data; calculating object-side coordinates (X, Y and Z) of identical points by means of multi-image forward intersection after calculating initial values by means of two-image forward intersection by the aid of two optional points among the selected identical points; and obtaining precise object-side coordinates (X, Y and Z') corresponding to the identical points by the aid of the object-side coordinates of the identical points solved by means of previous multi-image forward intersection. By means of multi-image forward intersection realized on the premise of elevation constraint of the LiDAR point cloud, object-side coordinates of acquired image points are quite high in plane precision and elevation precision.

Description

Airborne LiDAR point cloud and high resolution image carry out the combined positioning-method of spatial point
Technical field
Patent of the present invention relates to airborne LiDAR technical field of data processing, relates in particular to a kind of pinpoint method of associating that integrated LiDAR cloud data and high resolution image carry out spatial point.
Background technology
Airborne LiDAR is a kind of novel active airborne remote sensing earth observation technology, by carry high-resolution digital camera make flight just can synchronous acquisition to laser point cloud and aerial image, the POS system of carrying due to airborne LiDAR has inertial navigation and GPS positioning function, therefore can directly obtain three-dimensional point cloud information and high resolving power boat sheet and the elements of exterior orientation thereof of high spatial resolution, can carry out high-precision direct geo-location in theory, if do not processed in the situation of overall adjustment but carry out the very long and loaded down with trivial details sky of interior industry three, the realistic accuracy of the elements of exterior orientation of the high resolution image that it obtains must be subject to the combined influence of accidental error and systematic error, make traditional biplate forward intersection be difficult to reach the target of the direct geo-location of high precision, cannot meet the demand of current remote sensing mapping.
Summary of the invention
The plane precision of the direct geographic positioning for tradition based on biplate forward intersection and vertical accuracy be not high problem, utilization of the present invention with the airborne LiDAR of high resolution CCD camera boat fly in journey can synchronous acquisition to the feature of high-precision laser point cloud and aerial image, in order to realize the target of the high-precision direct geo-location of quick obtaining, the elevation information of having introduced laser point cloud carries out elevation constraint to the adjustment result of the multi-disc forward intersection of high resolution image, thereby realize the high precision volume coordinate of quick obtaining picture point, it is a kind of integrated high precision of multi-sensor data advantage, direct geographic positioning fast.
For achieving the above object, the present invention has adopted following technical scheme: airborne LiDAR point cloud and high resolution image carry out the combined positioning-method of spatial point,
1, original laser radar (LiDAR) data de-noising step, this step adopts k nearest neighbor ball denoise algorithm, removes the noise existing in some cloud;
2, high accuracy number ground model DEM (digital elevation model) generates step, the laser radar data of this step after to denoising, adopt triangulation network progressive encryption iterative filtering method to obtain beating laser spots on the ground, and interpolation generate high accuracy number ground model dem data;
3, manually selecting, after the initial point of same place, to be aided with the elements of exterior orientation of high precision image that POS system is obtained, all the other points of semi-automatic selection same place in looking aviation image across air strips more.
4, by any two points in the same place of choosing, utilize biplate forward intersection to calculate after initial value, utilize multi-disc forward intersection method to calculate the object coordinates (X, Y, Z) of same place.
The object coordinates of the same place 5, solving by the forward intersection of previous step multi-disc, according to its planimetric coordinates (X, Y) in the high accuracy DEM data that value is obtained at second step, interpolation obtains accurate height value Z ', complete elevation constraint, thereby obtain the accurate object coordinates (X that same place is corresponding, Y, Z ').
In technique scheme, described k nearest neighbor ball method is carried out cloud data denoising step and is:
First data point set carries out space lattice division, imaginary Existential Space ball, and take current measuring point as the centre of sphere, radius is got respectively measuring point to the distance of six of place cube grids;
Get the Spatial Sphere of radius minimum, carry out K-neighbor search in the grid interfering with it, the search of setting up if meet stops principle, stops search;
Otherwise, thereby the Spatial Sphere of getting larger radius is set up the contiguous ball of the K of point to be located; A cloud is being carried out in the process of noise processed, the distance size of the point in the k nearest neighbor ball of point to be located and foundation judges whether this point to be located is noise.
In technique scheme, the step that generates high accuracy DEM after described triangulation network progressive encryption iterative filtering is:
1. raw data is carried out utmost point low spot and the aerial point in k nearest neighbor ball filtering processing rejecting data;
2. the outsourcing rectangle of construction data, the height value on four summits of this outsourcing rectangle is set according to arest neighbors criterion, then outsourcing rectangle is carried out to triangulation, and using it as initial ground surface model;
3. data are carried out to graticule mesh tissue, grid should be slightly larger than the size of maximum buildings in a territory, cloud sector, and wherein the minimum point in each grid is millet cake initially, and the initially millet cake of choosing is joined in TIN;
4. calculate each point to the angle on the leg-of-mutton distance at its place and it and an Atria summit, if the value calculating is less than predefined threshold condition, joined in TIN;
5. repeat 4. until do not have new point to join in TIN;
6. the ground point interpolation of obtaining generates the as far as possible little DEM of Grid size.
Tool of the present invention has the following advantages: 1) by LiDAR point cloud, to carry out plane precision and the vertical accuracy of object coordinates of the accessed picture point of the multi-disc forward intersection that realizes under the prerequisite of elevation constraint very high in the present invention.2) utilize the present invention can reduce in a large number that airborne remote sensing field operation is controlled, the workload of translocation, at large scale, become even can cancel field operation aspect figure and control, shorten greatly aerial survey drafting period and expense.3) by accurate directly geographic positioning, save field operation and lay reference mark, avoid sky three operations that tradition is complicated, time-consuming, " short, adaptable and fast " advantage that makes airborne LiDAR obtain achievement can better be brought into play and be embodied.
Accompanying drawing explanation
Fig. 1 is the schematic diagram that is related to of noise spot and neighborhood around in the present invention.
Fig. 2 is iteration triangulation network filtering schematic diagram in the present invention.
Fig. 3 is projection coefficient method schematic diagram.
Fig. 4 is the pinpoint method flow diagram of associating that a kind of airborne laser cloud data provided by the invention and high resolution image data are carried out spatial point.
In Fig. 1, d represents distance, and centre point is current measuring point, and other point is search point;
Embodiment
A kind of airborne LiDAR point cloud provided by the invention and high resolution image carry out the pinpoint method of associating of spatial point, its essence is to utilize the advantage of multiple data sources, be to utilize the advantage of vertical accuracy of cloud data and the plane precision advantage that object coordinates that the forward intersection of high resolution image multi-disc is obtained has, finally realize the quick multi-disc forward intersection of high precision based on airborne LiDAR cloud data constraint, thereby reach the object of the direct geo-location of high precision.
Below in conjunction with accompanying drawing, describe performance of the present invention in detail, but they do not form limitation of the invention, only for example, simultaneously by illustrating that advantage of the present invention will become more clear and easily understand.
A kind of airborne laser cloud data provided by the invention and high resolution image data are carried out the pinpoint method of associating of spatial point, comprise the following steps:
(1) original LiDAR (laser radar) data de-noising:
If cloud data existence is starkly lower than or the utmost point low spot of projecting environment and aerial point, meeting considerable influence post-processing algorithm precision is therefore removed these noise spots before data processing.This method surveys by setting up k nearest neighbor ball the noise of removing in some cloud, and first data point set carries out space lattice division, imaginary Existential Space ball, and take current measuring point as the centre of sphere, radius is got respectively measuring point to the distance of six of place cube grids.Get the Spatial Sphere of radius minimum, carry out K-neighbor search in the grid interfering with it, the search of setting up if meet stops principle, stops search; Otherwise, thereby the Spatial Sphere of getting larger radius is set up the contiguous ball of the K of point to be located.A cloud is being carried out in the process of noise processed, the distance size that mainly depends on the point in the k nearest neighbor ball of point to be located and foundation judges whether this point to be located is noise (as shown in Figure 1).
(2) high accuracy DEM generates
Utilizing the filtering of the iteration triangulation network to obtain after the point set of ground, ground point collection interpolation is obtained to Grid DEM.Committed step is the filtering of the iteration triangulation network, the steps include: that 1. raw data being carried out to the filtering of k nearest neighbor ball processes utmost point low spot (noise spot that elevation is very low) and the aerial point (noise spot that elevation is very high) (this step completes in the 1st step) of rejecting in data; 2. the outsourcing rectangle of construction data, the height value on four summits of this outsourcing rectangle is set according to arest neighbors criterion, then outsourcing rectangle is carried out to triangulation, and using it as initial ground surface model (as in Fig. 2 a); 3. data are carried out to graticule mesh tissue, grid should be slightly larger than the size of maximum buildings in a territory, cloud sector, and wherein the minimum point in each grid is millet cake initially, and the initially millet cake of choosing is joined in TIN (TIN); 4. calculate each point to the angle on the leg-of-mutton distance at its place and it and an Atria summit, if the value calculating is less than predefined threshold condition, joined (as the b in Fig. 2) in TIN; 5. repeat 4. until do not have new point to join (as the c in Fig. 2) in TIN; 6. the ground point interpolation of obtaining generates the as far as possible little DEM of Grid size.
(3) same place is chosen
From have degree of precision elements of exterior orientation across the semi-automatic same place of choosing the multi-view images of air strips, while choosing, should guarantee as far as possible to choose the sub-pixel precision of same place.Because many baselines forward intersection its precision in the situation that elements of exterior orientation is certain depends on the measurement accuracy of same place to a great extent.
(4) multi-disc forward intersection
In the error equation of multi-disc forward intersection, object point is to obtain with the approximate value substitution collinearity equation of required value, by collinearity equation linearization, can obtain the error equation of multi-disc forward intersection: to each picture point, can list two error equations (as formula 1).If certain point appears in n width sequential images, can list 2n equation, therefore can ask by least square adjustment solution.While resolving, should be noted 2 points:
1: first utilize projection coefficient method (as formula 2) to calculate initial value.
2: the angle that also needs to obtain by photo centre and selected picture point any two light in corresponding image rays before calculating, if angle is less than 15 ° one (being picture point) removing in these two light, and then reexamine, finally make to look in light after every angle between two is all greater than 15 ° more and carry out again multi-disc forward intersection.
u x = - ∂ x ∂ X dX - ∂ x ∂ Y dY - ∂ x ∂ Z dZ - L x
(formula 1)
u y = - ∂ y ∂ X dX - ∂ y ∂ Y dY - ∂ y ∂ Z - L y
X in formula 1 and y are picpointed coordinates, X, and Y, Z is object point volume coordinate corresponding to picture point, Lx, Ly is matrix observed reading, u x, u yit is the correction of matrix.
X = X S 1 + N 1 X 1 = X S 2 + N 2 X 1 Y = Y S 1 + N 1 Y 1 = Y S 2 + N 2 Y 1 Z = Z S 1 + N 1 Z 1 = Z S 2 + N 2 Z 1 (formula 2)
Projection coefficient method as shown in Figure 3.S 1, S 2be respectively the projection centre of left and right image, Bx, By, Bz, is photographic base component, m1, m2 is respectively the conformation of object space point M on the image of left and right, X 1, Y 1, Z 1, X 2, Y 2, Z 2, be m1, the empty auxiliary coordinate of picture of m2, N 1, N 2expression projects to ground spot projection coefficient by left picture point and right picture point.
In computation process, picture point will be considered the known system error correction due to the geometric distortion of lens or measuring instrument, to weaken their impact.Conventionally principal point offset, radial distortion is poor and deflection photogrammetric distortion parameter is provided by manufacturer, the picture point of utilizing radial distortion formula (formula 3) to solve collinearity equation in this algorithm compensates.
Δ x r = ( x - x 0 ) ( K 1 · r 2 + K 2 · r 4 + K 3 · r 6 + O [ r 8 ] ) Δ y r = ( y - y 0 ) ( K 1 · r 2 + K 2 · r 4 + K 3 · r 6 + O [ r 8 ] ) (formula 3)
R wherein 2=(x-x 0) 2+ (y-y 0) 2, (x 0, y 0) be principal point coordinate, Ki is distortion factor, i is 1,2,3.
(5) elevation constraint
Object coordinates (the X of the same place of obtaining by the forward intersection of previous step multi-disc, Y, Z), according to (X, Y) thus in the high accuracy DEM data that coordinate figure generates in the 2nd step, carrying out interpolation obtains more accurate height value Z ', thereby complete elevation constraint, form new high precision object coordinates (X corresponding to same place, Y, Z '), realize the direct geo-location of high precision.

Claims (1)

1. airborne LiDAR point cloud and high resolution image carry out the combined positioning-method of spatial point, it is characterized in that it comprises the steps:
1) original LiDAR data de-noising step, this step adopts k nearest neighbor ball denoise algorithm, removes the noise existing in some cloud, and wherein, described k nearest neighbor ball method is carried out cloud data denoising step and is:
First data point set carries out space lattice division, imaginary Existential Space ball, and take current measuring point as the centre of sphere, radius is got respectively measuring point to the distance of six of place cube grids;
Get the Spatial Sphere of radius minimum, carry out K-neighbor search in the grid interfering with it, the search of setting up if meet stops principle, stops search;
Otherwise, thereby the Spatial Sphere of getting larger radius is set up the contiguous ball of the K of point to be located; A cloud is being carried out in the process of noise processed, the distance size of the point in the k nearest neighbor ball of point to be located and foundation judges whether this point to be located is noise;
2) high accuracy number ground model DEM generates step, the laser radar data of this step after to denoising, adopt triangulation network progressive encryption iterative filtering method to obtain beating laser spots on the ground, and interpolation generates high accuracy number ground model dem data, wherein, the step that generates high accuracy DEM after described triangulation network progressive encryption iterative filtering is:
1. raw data is carried out to the filtering of k nearest neighbor ball and process utmost point low spot and the aerial point of rejecting in data;
2. the outsourcing rectangle of construction data, the height value on four summits of this outsourcing rectangle is set according to arest neighbors criterion, then outsourcing rectangle is carried out to triangulation, and using it as initial ground surface model;
3. data are carried out to graticule mesh tissue, grid should be slightly larger than the size of maximum buildings in a territory, cloud sector, and wherein the minimum point in each grid is millet cake initially, and the initially millet cake of choosing is joined in TIN;
4. calculate each point to the angle on the leg-of-mutton distance at its place and it and an Atria summit, if the value calculating is less than predefined threshold condition, joined in TIN;
5. repeat 4. until do not have new point to join in TIN;
6. the ground point interpolation of obtaining generates the as far as possible little DEM of Grid size;
3) manually selecting, after the initial point of same place, to be aided with the elements of exterior orientation of high precision image that POS system is obtained, all the other points of semi-automatic selection same place in looking aviation image across air strips more;
4) by any two points in the same place of choosing, utilize biplate forward intersection to calculate after initial value, utilize multi-disc forward intersection method to calculate the object coordinates (X, Y, Z) of same place;
5) object coordinates of the same place solving by the forward intersection of previous step multi-disc, according to its planimetric coordinates (X, Y) in the high accuracy DEM data that value is obtained at second step, interpolation obtains accurate height value Z', complete elevation constraint, thereby obtain the accurate object coordinates (X that same place is corresponding, Y, Z').
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