CN104318616A - Colored point cloud system and colored point cloud generation method based on same - Google Patents

Abstract

The invention discloses a colored point cloud system and a colored point cloud generation method based on the system. The method includes the steps that a laser scanner acquires laser point cloud data, a digital camera acquires panoramic images, an inertia measurement unit and a GPS acquire position, gesture and time data of the panoramic images, and the position, gesture and time data correspond to the laser point cloud data one to one through a matching unit so that colored point cloud data can be generated. According to the colored point cloud system and the colored point cloud generation method based on the system, because the panoramic camera and the laser scanner are installed on the same measurement trolley, the corresponding relation between all points in laser point cloud and pixels on the panoramic images is deduced according to the panoramic images and the laser point cloud data, the color of the pixels is assigned to corresponding points through a specific algorithm so that colored point cloud data can be generated, and the system and method have great advantages in the aspects of visual display, object classification, object modeling and the like.

Description

Colour point clouds system and the colour point clouds generation method based on this system

Technical field

The present invention relates to a kind of image treatment method, particularly relate to a kind of colour point clouds system and the colour point clouds generation method based on this system.

Background technology

In recent years, the vehicle-mounted mobile mapping system development based on scanning laser sensor, positioning and orientation sensor and digital image sensor integration achieves certain achievement.Laser scanner can obtain intensive cloud data, digital camera can obtain color and vein information, laser point cloud data does not have colouring information separately, the custom of visual interpretation is not met in follow-up processing procedure, and digital image inconvenience directly measures, both combinations more accurately and intuitively can describe atural object.Colour point clouds is the product directly perceived of cloud data and image data fusion, in visual display, object classification, object modeling etc., have very large advantage.

More existing scholars are merged laser point cloud and digital image and have been carried out certain research both at home and abroad at present, different according to the type of digital image, area array CCD (Charge-coupled Device, charge coupled cell) image, linear CCD image and full-view image and laser scanner is mainly divided into merge.Most study be the fusion of CCD images and laser point cloud, for different data characteristicses, based on POS (Point of Sales, point of sales terminal) data or adopt the some method such as cloud and Feature Matching to realize the registration of laser point cloud data and CCD images data, then utilize collinearity equation fusion generation colour point clouds.Linear array CCD camera has the advantages such as frequency acquisition is high, visual angle is wide, overcoming area array CCD camera can not the shortcoming of storage figure picture and output image leak in time, but finds that linear array CCD camera has in actual applications and demarcate the problem such as difficulty, the overall blank level adjustment difficulty of image.The maximum feature of full-view image is that horizontal direction field angle reaches 360 degree, and check in panorama mode, three-dimensional visible is effective.

Summary of the invention

Provide hereinafter about brief overview of the present invention, to provide about the basic comprehension in some of the present invention.Should be appreciated that this general introduction is not summarize about exhaustive of the present invention.It is not that intention determines key of the present invention or pith, and nor is it intended to limit the scope of the present invention.Its object is only provide some concept in simplified form, in this, as the preorder in greater detail discussed after a while.

The invention provides a kind of colour point clouds system, comprising:

Digital camera, for obtaining full-view image with preset frequency;

Laser scanner, for obtaining the laser point cloud data of described full-view image; Inertial Measurement Unit and GPS, described Inertial Measurement Unit and described GPS are for providing the described position and attitude time data of colour point clouds system in moving process based on full-view image;

Matching unit, for by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data.

Present invention also offers the colour point clouds generation method based on colour point clouds system, comprising:

Digital camera obtains full-view image with preset frequency;

Laser scanner obtains laser point cloud data;

Inertial Measurement Unit and GPS obtain the position and attitude time data of full-view image;

Matching unit, by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data.

Colour point clouds system in the present invention and the colour point clouds generation method based on this system, by panorama camera and laser scanner being arranged on same measurement car, according to full-view image and laser point cloud data, by the corresponding relation of pixel on each point in derivation laser point cloud and full-view image, by concrete algorithm, the color of pixel is assigned to corresponding point, thus generates colour point clouds data, in visual display, object classification, object modeling etc., there is very large advantage.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the laser point cloud data schematic diagram obtained in the present invention;

Fig. 2 is the full-view image schematic diagram data obtained in the present invention;

Fig. 3 is coordinate system definition schematic diagram in the present invention;

Fig. 4 is the colour point clouds schematic diagram after merging in the present invention;

Fig. 5 is that in the present invention, colour point clouds generates method step schematic diagram.

Embodiment

For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.The element described in an accompanying drawing of the present invention or a kind of embodiment and feature can combine with the element shown in one or more other accompanying drawing or embodiment and feature.It should be noted that for purposes of clarity, accompanying drawing and eliminate expression and the description of unrelated to the invention, parts known to persons of ordinary skill in the art and process in illustrating.Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under the prerequisite not paying creative work, all belongs to the scope of protection of the invention.

Embodiment one:

The invention provides a kind of colour point clouds system, comprising:

Digital camera, for obtaining full-view image with preset frequency;

Laser scanner, for obtaining the laser point cloud data of described full-view image;

Inertial Measurement Unit and GPS, described Inertial Measurement Unit and described GPS are for providing the described position and attitude time data of colour point clouds system in moving process based on full-view image;

Matching unit, for by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data.

The full-view image that colour point clouds system in the present invention obtains respectively according to panorama camera and laser scanner and laser point cloud generate colour point clouds data by concrete algorithm, in visual display, object classification, object modeling etc., have very large advantage.

Optionally, described laser scanner, described digital camera, described Inertial Measurement Unit and described GPS are spatially positioned in identical platform, and described platform is traverse measurement car.Digital camera and laser scanner are spatially rigidly fixed in identical platform by the present invention, are unified in time by GPS, so in the process of experimental check and data fusion from now on, full-view image and laser point cloud can accuracy registrations.

Described digital camera is panorama camera, native system directly obtains full-view image by using panorama camera, by the registration of the full-view image that do not gather in the same time and laser point cloud, provided the three-dimensional coordinate of corresponding position image by laser point cloud, thus can reduce the coordinate of arbitrfary point in full-view image.

Optionally, described matching unit also for: for described laser point cloud data selects suitable full-view image, be specially:

If object point is not blocked in described full-view image, then according to time of described GPS or the nearest full-view image of each object point of geometric distance chosen distance;

Otherwise, choose the full-view image be not blocked that the object point that is blocked is adjacent.

Can be there is the situation of being blocked by other objects in the object point in the full-view image that digital camera obtains in actual photographed, and the situation of blocking from the image that different angles obtains is different, needs for laser point cloud data selects suitable full-view image.

Optionally, described " by described position and attitude time data and described laser point cloud data one_to_one corresponding, generating colour point clouds data " specifically comprises:

S1: descend coordinate (X to S1 system by the terrestrial coordinate (Xt, Yt, Zt) of object point₁, Y₁, Z₁), described S1 is local space rectangular coordinate system, and wherein (dX, dY, dZ) is the terrestrial coordinate of the current panorama ball centre of sphere;

$\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]=\left[\begin{array}{c}\mathrm{Xt}\\ \mathrm{Yt}\\ \mathrm{Zt}\end{array}\right]-\left[\begin{array}{c}\mathrm{dX}\\ \mathrm{dY}\\ \mathrm{dZ}\end{array}\right]$

S2: by described S1 system coordinate (X₁, Y₁, Z₁) to S2 system coordinate (Xs, Ys, Zs), described S2 is panorama spherical space rectangular coordinate system;

$\left[\begin{array}{c}\mathrm{Xs}\\ \mathrm{Ys}\\ \mathrm{Zs}\end{array}\right]=\left[\begin{array}{ccc}a1& a2& a3\\ b1& b2& b3\\ c1& c2& c3\end{array}\right]\·\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]$

The coefficient that described (a1, a2, a3, b1, b2, b3, c1, c2, c3) is rotation matrix, by three attitude angle roll angles of full-view imageangle of pitch ω, course angle κ determine;

S3: calculate the polar coordinates of corresponding picture point on panorama ball (B, L, R) by described S2 system coordinate (Xs, Ys, Zs), R is the radius of panorama ball;

$B=\left\{\begin{array}{c}\frac{\mathrm{\&pi;}}{2}-{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right),\mathrm{Xs}>0\\ -(\frac{\mathrm{\&pi;}}{2}+{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right)),\mathrm{Xs}<0\end{array}\right.$

$L={\tan }^{-1}\left(\frac{\mathrm{Zs}}{\sqrt{{\mathrm{Xs}}^2+{\mathrm{Ys}}^2}}\right)$

S4: calculate pixel coordinate (m, n) by described B, L, wherein, Width is the wide of described full-view image, and Height is the height of described full-view image;

$m=\frac{\mathrm{Width}}{2}+\frac{B}{2\mathrm{\&pi;}}\&CenterDot;\mathrm{Width}$

$n=\frac{\mathrm{Height}}{2}-\frac{L}{\mathrm{\&pi;}}\&CenterDot;\mathrm{Height}$

S5: for described laser point cloud data composes color, wherein RGB (Xs, Ys, Zs) represents point (Xs, Ys, Zs) RGB color value, N be full-view image numbering, RGB (m, n, N) represent the RGB color value of pixel (m, n) on this full-view image;

RGB(Xs,Ys,Zs)＝RGB(m,n,N)。

According to above-mentioned step, position and attitude time data and laser point cloud data one_to_one corresponding are got up, the pixel coordinate of picture point on the corresponding panorama ball namely calculating object point, and the RGB color value of described picture point is assigned to described object point.

Embodiment two:

As shown in Figure 5, present invention also offers a kind of colour point clouds generation method based on colour point clouds system, comprising:

Digital camera obtains full-view image with preset frequency;

Laser scanner obtains laser point cloud data;

Inertial Measurement Unit and GPS obtain the position and attitude time data of full-view image;

Matching unit, by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data.

Colour point clouds generation method provided by the invention by obtaining full-view image and laser point cloud, by described full-view image and laser point cloud accuracy registration, and based on composing colored algorithm to corresponding laser point cloud, can draw effect merge preferably after colour point clouds.

Be illustrated in figure 1 described laser scanner obtain laser point cloud data schematic diagram, as Fig. 2 be as described in digital camera obtain full-view image schematic diagram data.

Optionally, described laser point cloud data is the data that described laser scanner continuous sweep obtains, and described laser point cloud data form is (x, y, z, t), and wherein x, y, z is three-dimensional coordinate, and t represents GPS second in week.

Optionally, described full-view image is gather once every 5 meters, and the data of described full-view image are through resolving as jpeg format or BMP form.

Optionally, described full-view image position and attitude time data is the filename of each Zhang Quanjing image, latitude and longitude coordinates, three-dimensional rectangular coordinate, attitude angle and GPS second in week, and described attitude angle comprises roll angleangle of pitch ω, course angle κ.

Can relate to multiple coordinate system in colour point clouds generating algorithm, be illustrated in figure 3 the schematic diagram of multiple coordinate system, earth coordinates S-XtYtZt is absolute coordinates, and in laser point cloud data, each object point all uses this coordinate system record;

Local space rectangular coordinate system S1-X₁y₁z₁: the local space rectangular coordinate system that the origin translation of S system and earth coordinates is formed to the current panorama ball centre of sphere;

Panorama spherical space rectangular coordinate system S2-XsYsZs: with the current panorama ball centre of sphere for initial point, Y-axis points to described traverse measurement car route, and X-axis is pointed on the right side of traverse measurement car car body, and Z axis is vertically upward;

Panorama spheric polar coordinate system P: the polar coordinate system being initial point with the panorama centre of sphere;

Full-view image plane coordinate system O-xy: the plane right-angle coordinate taking principal point as initial point.

In laser point cloud data, the coordinate of each point is absolute coordinates, represent the physical location of object point, colour point clouds generation method described in the present invention calculates the corresponding pixel coordinate (m of picture point on full-view image by the principle of conllinear by the absolute coordinates taking moment object point, n), subsequently the color value of the picture point of correspondence is assigned to above-mentioned object point.

Be exactly need to read in above-mentioned full-view image position and attitude time data composing the colored first step for described picture point, namely comprising multiple parameters.

Optionally, described " matching unit, by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data " is front also comprises: for described laser point cloud data selects suitable full-view image, be specially:

If object point is not blocked in described full-view image, then according to time of described GPS or the nearest full-view image of each object point of geometric distance chosen distance;

Otherwise, choose the full-view image be not blocked that the object point that is blocked is adjacent.

In the operating process of reality, distance between laser point cloud data sweep trace is about 0.2 meter, the speed of a motor vehicle of traverse measurement car is about 40km/h, full-view image is then every 5 meters one, and the situation of blocking can be there is in the object point that we need in full-view image, take the situation of blocking in the image of acquisition from different perspectives different, so need for laser point cloud data selects suitable full-view image;

If the object point in described full-view image is not blocked, the then immediate full-view image of each object point of chosen distance, the selection of described immediate full-view image is time according to GPS or geometric distance, select time immediate or in distance immediate full-view image;

If object point has been blocked in described full-view image, then to choose the object point that is blocked adjacent and the full-view image be not blocked.

Optionally, described " matching unit, by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data " specifically comprises:

S1: descend coordinate (X to S1 system by the terrestrial coordinate (Xt, Yt, Zt) of object point₁, Y₁, Z₁) described S1 is local space rectangular coordinate system, wherein (dX, dY, dZ) is the terrestrial coordinate of the current panorama ball centre of sphere;

$\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]=\left[\begin{array}{c}\mathrm{Xt}\\ \mathrm{Yt}\\ \mathrm{Zt}\end{array}\right]-\left[\begin{array}{c}\mathrm{dX}\\ \mathrm{dY}\\ \mathrm{dZ}\end{array}\right]$

S2: by described S1 system coordinate (X₁, Y₁, Z₁) to S2 system coordinate (Xs, Ys, Zs), described S2 is panorama spherical space rectangular coordinate system;

$\left[\begin{array}{c}\mathrm{Xs}\\ \mathrm{Ys}\\ \mathrm{Zs}\end{array}\right]=\left[\begin{array}{ccc}a1& a2& a3\\ b1& b2& b3\\ c1& c2& c3\end{array}\right]\&CenterDot;\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]$

The coefficient that described (a1, a2, a3, b1, b2, b3, c1, c2, c3) is rotation matrix, by three attitude angle roll angles of full-view imageangle of pitch ω, course angle κ determine;

S3: calculate the polar coordinates of corresponding picture point on panorama ball (B, L, R) by described S2 system coordinate (Xs, Ys, Zs), R is the radius of panorama ball;

$B=\left\{\begin{array}{c}\frac{\mathrm{\&pi;}}{2}-{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right),\mathrm{Xs}>0\\ -(\frac{\mathrm{\&pi;}}{2}+{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right)),\mathrm{Xs}<0\end{array}\right.$

$L={\tan }^{-1}\left(\frac{\mathrm{Zs}}{\sqrt{{\mathrm{Xs}}^2+{\mathrm{Ys}}^2}}\right)$

S4: calculate pixel coordinate (m, n) by described B, L, wherein, Width is the wide of described full-view image, and Height is the height of described full-view image;

$m=\frac{\mathrm{Width}}{2}+\frac{B}{2\mathrm{\&pi;}}\&CenterDot;\mathrm{Width}$

$n=\frac{\mathrm{Height}}{2}-\frac{L}{\mathrm{\&pi;}}\&CenterDot;\mathrm{Height}$

S5: for described laser point cloud data compose color wherein RGB (Xs, Ys, Zs) represent point (Xs, Ys, Zs) RGB color value, N is full-view image numbering, RGB (m, n, N) represent the RGB color value of pixel (m, n) on this full-view image;

RGB(Xs,Ys,Zs)＝RGB(m,n,N)。

First by the coordinate conversion of object point under absolute coordinate system in local space rectangular coordinate system S1, conversion method is provided by formula 1;

Then pass through formula 2 by the coordinate conversion under local space rectangular coordinate system S1 in the rectangular coordinate system S2 of panorama spherical space, and the correlation parameter in formula 2 is determined by three attitude angle of formula 4 by full-view image;

The polar coordinates of coordinate on the panorama ball of correspondence in described panorama spherical space rectangular coordinate system S2 are calculated again by formula 4 and formula 5;

Calculate corresponding pixel coordinate according to above-mentioned polar coordinates, the pixel coordinate that above-mentioned object point is corresponding can be known, subsequently according to the pixel coordinate drawn, for described laser point cloud composes color, be illustrated in figure 4 the colour point clouds schematic diagram after fusion.

According to the colour point clouds generation method in the present invention, the registration between laser point cloud and full-view image accurately can be realized.

State in each embodiment on the invention, the sequence number of embodiment and/or sequencing are only convenient to describe, and do not represent the quality of embodiment.The description of each embodiment is all emphasized particularly on different fields, in certain embodiment, there is no the part described in detail, can see the associated description of other embodiments.

Although last it is noted that described the present invention and advantage thereof in detail above, be to be understood that and can carry out various change when not exceeding the spirit and scope of the present invention limited by appended claim, substituting and converting.And scope of the present invention is not limited only to the specific embodiment of process, equipment, means, method and step described by instructions.One of ordinary skilled in the art will readily appreciate that from disclosure of the present invention, can use perform the function substantially identical with corresponding embodiment described herein or obtain and its substantially identical result, existing and that will be developed in the future process, equipment, means, method or step according to the present invention.Therefore, appended claim is intended to comprise such process, equipment, means, method or step in their scope.

Claims (10)

1. a colour point clouds system, is characterized in that, comprising:

Digital camera, for obtaining full-view image with preset frequency;

Laser scanner, for obtaining the laser point cloud data of described full-view image;

Inertial Measurement Unit and GPS, described Inertial Measurement Unit and described GPS are for providing the described position and attitude time data of colour point clouds system in moving process based on full-view image;

Matching unit, for by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data.

2. colour point clouds system according to claim 1, is characterized in that, described laser scanner, described digital camera, described Inertial Measurement Unit and described GPS are spatially positioned in identical platform, and described platform is traverse measurement car.

3. colour point clouds system according to claim 1, is characterized in that, described matching unit also for: for described laser point cloud data selects suitable full-view image, be specially:

If object point is not blocked in described full-view image, then according to time of described GPS or the nearest full-view image of each object point of geometric distance chosen distance;

Otherwise, choose the full-view image be not blocked that the object point that is blocked is adjacent.

4. colour point clouds system according to claim 1, is characterized in that, described " by described position and attitude time data and described laser point cloud data one_to_one corresponding, generating colour point clouds data " specifically comprises:

S1: descend coordinate (X to S1 system by the terrestrial coordinate (Xt, Yt, Zt) of object point₁, Y₁, Z₁), described S1 is local space rectangular coordinate system, and wherein (dX, dY, dZ) is the terrestrial coordinate of the current panorama ball centre of sphere;

$\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]=\left[\begin{array}{c}\mathrm{Xt}\\ \mathrm{Yt}\\ \mathrm{Zt}\end{array}\right]-\left[\begin{array}{c}\mathrm{dX}\\ \mathrm{dY}\\ \mathrm{dZ}\end{array}\right]$

S2: by described S1 system coordinate (X₁, Y₁, Z₁) to S2 system coordinate (Xs, Ys, Zs), described S2 is panorama spherical space rectangular coordinate system;

$\left[\begin{array}{c}\mathrm{Xs}\\ \mathrm{Ys}\\ \mathrm{Zs}\end{array}\right]=\left[\begin{array}{ccc}a1& a2& a3\\ b1& b2& b3\\ c1& c2& c3\end{array}\right]\&CenterDot;\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]$

The coefficient that described (a1, a2, a3, b1, b2, b3, c1, c2, c3) is rotation matrix, by three attitude angle roll angles of full-view imageangle of pitch ω, course angle κ determine;

S3: calculate the polar coordinates of corresponding picture point on panorama ball (B, L, R) by described S2 system coordinate (Xs, Ys, Zs), R is the radius of panorama ball;

$B=\left\{\begin{array}{c}\frac{\mathrm{\&pi;}}{2}-{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right),\mathrm{Xs}>0\\ -(\frac{\mathrm{\&pi;}}{2}+{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right)),\mathrm{Xs}<0\end{array}\right.$

$L={\tan }^{-1}\left(\frac{\mathrm{Zs}}{\sqrt{{\mathrm{Xs}}^2+{\mathrm{Ys}}^2}}\right)$

S4: calculate pixel coordinate (m, n) by described B, L, wherein, Width is the wide of described full-view image, and Height is the height of described full-view image;

$m=\frac{\mathrm{Width}}{2}+\frac{B}{2\mathrm{\&pi;}}\&CenterDot;\mathrm{Width}$

$n=\frac{\mathrm{Height}}{2}-\frac{L}{\mathrm{\&pi;}}\&CenterDot;\mathrm{Height}$

S5: for described laser point cloud data composes color, wherein RGB (Xs, Ys, Zs) represents point (Xs, Ys, Zs) RGB color value, N be full-view image numbering, RGB (m, n, N) represent the RGB color value of pixel (m, n) on this full-view image;

RGB(Xs,Ys,Zs)＝RGB(m,n,N)。

5. one kind based on the colour point clouds generation method of the colour point clouds system described in claim 1-4 any one, it is characterized in that, comprising:

Digital camera obtains full-view image with preset frequency;

Laser scanner obtains laser point cloud data;

Inertial Measurement Unit and GPS obtain the position and attitude time data of full-view image;

Matching unit, by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data.

6. as claimed in claim 5 based on the colour point clouds generation method of colour point clouds system, it is characterized in that, described laser point cloud data is the data that described laser scanner continuous sweep obtains, described laser point cloud data form is (x, y, z, t), wherein x, y, z is three-dimensional coordinate, and t represents GPS second in week.

7. as claimed in claim 5 based on the colour point clouds generation method of colour point clouds system, it is characterized in that, described full-view image is gather once every 5 meters, and the data of described full-view image are through resolving as jpeg format or BMP form.

8. as claimed in claim 5 based on the colour point clouds generation method of colour point clouds system, it is characterized in that, described full-view image position and attitude time data is the filename of each Zhang Quanjing image, latitude and longitude coordinates, three-dimensional rectangular coordinate, attitude angle and GPS second in week, and described attitude angle comprises roll angleangle of pitch ω, course angle κ.

9. as claimed in claim 5 based on the colour point clouds generation method of colour point clouds system, it is characterized in that, described " matching unit is by described position and attitude time data and described laser point cloud data one_to_one corresponding; generate colour point clouds data " is front also to be comprised: for described laser point cloud data selects suitable full-view image, be specially:

If object point is not blocked in described full-view image, then according to time of described GPS or the nearest full-view image of each object point of geometric distance chosen distance;

Otherwise, choose the full-view image be not blocked that the object point that is blocked is adjacent.

10. as claimed in claim 5 based on the colour point clouds generation method of colour point clouds system, it is characterized in that, described " matching unit, by described position and attitude time data and described laser point cloud data one_to_one corresponding, generates colour point clouds data " specifically comprises:

S1: descend coordinate (X to S1 system by the terrestrial coordinate (Xt, Yt, Zt) of object point₁, Y₁, Z₁), described S1 is local space rectangular coordinate system, and wherein (dX, dY, dZ) is the terrestrial coordinate of the current panorama ball centre of sphere;

$\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]=\left[\begin{array}{c}\mathrm{Xt}\\ \mathrm{Yt}\\ \mathrm{Zt}\end{array}\right]-\left[\begin{array}{c}\mathrm{dX}\\ \mathrm{dY}\\ \mathrm{dZ}\end{array}\right]$

S2: by described S1 system coordinate (X₁, Y₁, Z₁) to S2 system coordinate (Xs, Ys, Zs), described S2 is panorama spherical space rectangular coordinate system;

$\left[\begin{array}{c}\mathrm{Xs}\\ \mathrm{Ys}\\ \mathrm{Zs}\end{array}\right]=\left[\begin{array}{ccc}a1& a2& a3\\ b1& b2& b3\\ c1& c2& c3\end{array}\right]\&CenterDot;\left[\begin{array}{c}{X}_1\\ Y_1\\ Z_1\end{array}\right]$

The coefficient that described (a1, a2, a3, b1, b2, b3, c1, c2, c3) is rotation matrix, by three attitude angle roll angles of full-view imageangle of pitch ω, course angle κ determine;

S3: calculate the polar coordinates of corresponding picture point on panorama ball (B, L, R) by described S2 system coordinate (Xs, Ys, Zs), R is the radius of panorama ball;

$B=\left\{\begin{array}{c}\frac{\mathrm{\&pi;}}{2}-{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right),\mathrm{Xs}>0\\ -(\frac{\mathrm{\&pi;}}{2}+{\tan }^{-1}\left(\frac{\mathrm{Ys}}{\mathrm{Xs}}\right)),\mathrm{Xs}<0\end{array}\right.$

$L={\tan }^{-1}\left(\frac{\mathrm{Zs}}{\sqrt{{\mathrm{Xs}}^2+{\mathrm{Ys}}^2}}\right)$

S4: calculate pixel coordinate (m, n) by described B, L, wherein, Width is the wide of described full-view image, and Height is the height of described full-view image;

$m=\frac{\mathrm{Width}}{2}+\frac{B}{2\mathrm{\&pi;}}\&CenterDot;\mathrm{Width}$

$n=\frac{\mathrm{Height}}{2}-\frac{L}{\mathrm{\&pi;}}\&CenterDot;\mathrm{Height}$

S5: for described laser point cloud data composes color, wherein RGB (Xs, Ys, Zs) represents point (Xs, Ys, Zs) RGB color value, N be full-view image numbering, RGB (m, n, N) represent the RGB color value of pixel (m, n) on this full-view image;

RGB(Xs,Ys,Zs)＝RGB(m,n,N)。