CN106651786B - The processing method of riverbank region point cloud data - Google Patents
The processing method of riverbank region point cloud data Download PDFInfo
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- CN106651786B CN106651786B CN201610973335.0A CN201610973335A CN106651786B CN 106651786 B CN106651786 B CN 106651786B CN 201610973335 A CN201610973335 A CN 201610973335A CN 106651786 B CN106651786 B CN 106651786B
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- 238000000034 method Methods 0.000 claims abstract description 11
- 238000005070 sampling Methods 0.000 claims description 8
- 238000001914 filtration Methods 0.000 abstract description 6
- 230000007704 transition Effects 0.000 abstract description 4
- 238000012545 processing Methods 0.000 description 4
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- 238000012986 modification Methods 0.000 description 2
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- G06T2207/10028—Range image; Depth image; 3D point clouds
Abstract
The present invention provides a kind of processing method of riverbank region point cloud data, comprising: for riverbank region inner boundary sub-line described in every section, samples m sampled point, assigns height value to each sampled point；For each data point of the point cloud in the riverbank subregion, searching and matching method is closed on by sampled point, search the sampled point nearest apart from data point P, judge whether the height value of data point P is less than the height value of sampled point R, if it is less than, it then show that data point P is the conclusion of exceptional data point, filters out data point P；Otherwise, retain data point P.It has the advantage that on the basis of guaranteeing the smooth transition of riverbank region elevation, realizes efficient filtering noise data, inhibit the surface noise data of riverbank area three-dimensional model being building up to, improve the precision for the riverbank area three-dimensional model being building up to.
Description
Technical field
The invention belongs to Point Cloud Processing technical fields, and in particular to a kind of processing side of riverbank region point cloud data
Method.
Background technique
With the development of computer graphics techniques, point cloud data becomes more and more general in modeling and rendering research application
And.
Currently, when using riverbank region point cloud data building riverbank area three-dimensional model, due to riverbank region point cloud number
According to there are noises, therefore, noise data is mainly removed using Manual intervention method, has that noise data filter effect is low asks
Topic.
Summary of the invention
In view of the defects existing in the prior art, the present invention provides a kind of processing method of riverbank region point cloud data, can have
Effect solves the above problems.
The technical solution adopted by the invention is as follows:
The present invention provides a kind of processing method of riverbank region point cloud data, comprising the following steps:
Step 1, the original point cloud data in target riverbank region is obtained；
Step 2, the original point cloud data is pre-processed, obtains pretreated point cloud data；
Step 3, limb recognition is carried out to the pretreated point cloud data, recognizes several marginal points；Successively connect
Each marginal point is connect, riverbank region inner edge boundary line is obtained；
Step 4: according to riverbank provincial characteristics, the riverbank region inner edge boundary line being divided into several segments riverbank region inner edge
Boundary's sub-line；
Step 5, for riverbank region inner boundary sub-line described in every section, following steps are performed both by:
Step 5.1, it navigates to initial data point A and terminates data point B, meanwhile, get the height value of initial data point A
With the height value for terminating data point B；If the height value of initial data point A is less than the height value for terminating data point B；
Step 5.2, by the 1st preset rules, it is upsampled to m sampled point in the riverbank region inner boundary sub-line, m is certainly
So number；According to the height value of initial data point A and the height value of end data point B, height value is assigned to each sampled point,
Make by from initial data point A to the direction for terminating data point B, the height value of each sampled point gradually increases；
Step 5.3, it is determined outside the region of riverbank by the 2nd preset rules in the outside of the riverbank region inner boundary sub-line
Boundary's sub-line；Region between the riverbank region inner boundary sub-line and the riverbank area outer sub-line is riverbank sub-district
Domain；For each data point of the point cloud in the riverbank subregion, it is denoted as data point P, closes on search matching by sampled point
Method searches the sampled point nearest apart from data point P, is denoted as sampled point R；Then, judge data point P height value whether
Less than the height value of sampled point R, if it is less, showing that data point P is the conclusion of exceptional data point, data point P is filtered out；It is no
Then, retain data point P；
It so constantly recycles, until the equal matching judgment of all data points in the subregion of riverbank is primary；Return again to step
6；
Step 6, filtered data point in the sampled point and riverbank subregion in riverbank region inner boundary sub-line is formed
Eventually for the point cloud data of modeling.
Preferably, in step 2, the original point cloud data is pre-processed, specifically:
The ground classification data for obtaining original point cloud data, according to ground classification data, by non-riverbank region point cloud data
It filters out, obtains riverbank region point cloud data.
Preferably, in step 5.2, by the 1st preset rules, m is upsampled in the riverbank region inner boundary sub-line and is adopted
Sampling point refers to:
Sampling step length is set according to dem data plane precision, by the sampling step length, inner boundary in the riverbank region
Line is upsampled to m sampled point.
Preferably, in step 5.2, height value is assigned to each sampled point, further includes:
Sampled point Q1, sampled point are successively denoted as by the direction apart from initial data point A from the near to the distant for m sampled point
Q2 ... sampled point Qm；
Then: the height value of sampled point Q1-initial data point A height value=sampled point Q2 height value-sampled point Q1
Height value-sampled point Qm elevation of height value=sampled point Q3 height value-sampled point Q2 height value ... end data point B
Value.
Preferably, in step 5.3, river is determined in the outside of the riverbank region inner boundary sub-line by the 2nd preset rules
Bank area outer sub-line, specifically:
According to dem data precision, riverbank width value is set；According to the riverbank width value, determine outside the riverbank region
Boundary sub-line is substantially parallel the riverbank area outer sub-line with the riverbank region inner boundary sub-line, also, the river
The distance of bank area outer sub-line to the riverbank region inner boundary sub-line is equal to the riverbank width value.
Preferably, after step 3, further includes:
According to riverbank region inner edge boundary line, corresponding river region planar data are constructed；
River region planar data are filtered by spatial relationship, the point cloud data in river region is filtered out.
The processing method of riverbank region provided by the invention point cloud data has the advantage that
On the basis of guaranteeing the smooth transition of riverbank region elevation, realizes efficient filtering noise data, inhibit to be building up to
Riverbank area three-dimensional model surface noise data, improve the precision for the riverbank area three-dimensional model being building up to.
Detailed description of the invention
Fig. 1 is the flow chart of the processing method of riverbank region provided by the invention point cloud data.
Specific embodiment
In order to which the technical problems, technical solutions and beneficial effects solved by the present invention is more clearly understood, below in conjunction with
Accompanying drawings and embodiments, the present invention will be described in further detail.It should be appreciated that specific embodiment described herein only to
It explains the present invention, is not intended to limit the present invention.
The present invention provides a kind of processing method of riverbank region point cloud data, is guaranteeing the smooth transition of riverbank region elevation
On the basis of, it realizes efficient filtering noise data, inhibits the surface noise data of riverbank area three-dimensional model being building up to, improve
The precision for the riverbank area three-dimensional model being building up to.
With reference to Fig. 1, the processing method of riverbank region point cloud data the following steps are included:
Step 1, the original point cloud data in target riverbank region is obtained；
Step 2, the original point cloud data is pre-processed, obtains pretreated point cloud data；
In this step, following methods can be used, original point cloud data is pre-processed:
The ground classification data for obtaining original point cloud data, according to ground classification data, by non-riverbank region point cloud data
It filters out, obtains riverbank region point cloud data.Point cloud data ground classification data is obtained, point cloud data amount can be reduced, and then improve
Subsequent step is to Point Cloud Processing efficiency.
Step 3, limb recognition is carried out to the pretreated point cloud data, recognizes several marginal points；Successively connect
Each marginal point is connect, riverbank region inner edge boundary line is obtained；
Step 4: according to riverbank provincial characteristics, the riverbank region inner edge boundary line being divided into several segments riverbank region inner edge
Boundary's sub-line；
Step 5, for riverbank region inner boundary sub-line described in every section, following steps are performed both by:
Step 5.1, it navigates to initial data point A and terminates data point B, meanwhile, get the height value of initial data point A
With the height value for terminating data point B；If the height value of initial data point A is less than the height value for terminating data point B；
Step 5.2, by the 1st preset rules, it is upsampled to m sampled point in the riverbank region inner boundary sub-line, m is certainly
So number；For example, sampling step length is set according to dem data plane precision, by the sampling step length, in riverbank region inner boundary
Sub-line is upsampled to m sampled point.
According to the height value of initial data point A and the height value of end data point B, elevation is assigned to each sampled point
Value makes by from initial data point A to the direction for terminating data point B, and the height value of each sampled point gradually increases；
Height value is assigned to each sampled point, further includes:
Sampled point Q1, sampled point are successively denoted as by the direction apart from initial data point A from the near to the distant for m sampled point
Q2 ... sampled point Qm；
Then: the height value of sampled point Q1-initial data point A height value=sampled point Q2 height value-sampled point Q1
Height value-sampled point Qm elevation of height value=sampled point Q3 height value-sampled point Q2 height value ... end data point B
Value.
In embodiments of the present invention, in order to realize the elevation smooth effect of riverbank region point cloud data, root has been used
According to riverbank region inner boundary sub-line head and the tail data point elevational point, and then the method for assigning height value to sampled point.If being unable to get
The height value of head and the tail data point can then obtain head and the tail data point and close on range point cloud data elevation mean information, and then participate in adopting
The smooth assignment of sampling point elevation.
Step 5.3, it is determined outside the region of riverbank by the 2nd preset rules in the outside of the riverbank region inner boundary sub-line
Boundary's sub-line；For example, setting riverbank width value according to dem data precision；According to the riverbank width value, the riverbank area is determined
Overseas boundary sub-line is substantially parallel the riverbank area outer sub-line with the riverbank region inner boundary sub-line, also, institute
The distance for stating riverbank area outer sub-line to the riverbank region inner boundary sub-line is equal to the riverbank width value.
Region between the riverbank region inner boundary sub-line and the riverbank area outer sub-line is riverbank sub-district
Domain；For each data point of the point cloud in the riverbank subregion, it is denoted as data point P, closes on search matching by sampled point
Method searches the sampled point nearest apart from data point P, is denoted as sampled point R；Then, judge data point P height value whether
Less than the height value of sampled point R, if it is less, showing that data point P is the conclusion of exceptional data point, data point P is filtered out；It is no
Then, retain data point P；
It so constantly recycles, until the equal matching judgment of all data points in the subregion of riverbank is primary；Return again to step
6；
This step main cause are as follows: since usually there is hollow phenomenon in riverbank region, by the point cloud number in hollow region
According to filtering out, it is ensured that threedimensional model surface accuracy.
Step 6, filtered data point in the sampled point and riverbank subregion in riverbank region inner boundary sub-line is formed
Eventually for the point cloud data of modeling.
In practical application, there are the sundries such as polybag since the river region in the region of riverbank usually floats, and sundries can shape
At the noise data in point cloud data, therefore, it is necessary to give to remove.
Therefore, it is filtered out using following methods；According to riverbank region inner edge boundary line, corresponding river region planar number is constructed
According to；River region planar data are filtered by spatial relationship, the point cloud data in river region is filtered out.
The processing method of riverbank region provided by the invention point cloud data has the advantage that
On the basis of guarantee riverbank region elevation smooth transition, efficient filtering noise data is realized, it can be in batches to point
Cloud data carry out riverbank region elevation smoothly and abnormal elevation filtering, promotion Point Cloud Processing accuracy inhibit to be building up to
Riverbank area three-dimensional model surface noise data, improve the precision for the riverbank area three-dimensional model being building up to.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
Depending on protection scope of the present invention.
Claims (6)
1. a kind of processing method of riverbank region point cloud data, which comprises the following steps:
Step 1, the original point cloud data in target riverbank region is obtained；
Step 2, the original point cloud data is pre-processed, obtains pretreated point cloud data；
Step 3, limb recognition is carried out to the pretreated point cloud data, recognizes several marginal points；It is sequentially connected each
A marginal point obtains riverbank region inner edge boundary line；
Step 4: according to riverbank provincial characteristics, the riverbank region inner edge boundary line being divided into several segments riverbank region inner boundary
Line；
Step 5, for riverbank region inner boundary sub-line described in every section, following steps are performed both by:
Step 5.1, it navigates to initial data point A and terminates data point B, meanwhile, get the height value and knot of initial data point A
The height value of beam data point B；If the height value of initial data point A is less than the height value for terminating data point B；
Step 5.2, by the 1st preset rules, it is upsampled to m sampled point in the riverbank region inner boundary sub-line, m is nature
Number；According to the height value of initial data point A and the height value of end data point B, height value is assigned to each sampled point, is made
By from initial data point A to the direction for terminating data point B, the height value of each sampled point is gradually increased；
Step 5.3, riverbank area outer is determined in the outside of the riverbank region inner boundary sub-line by the 2nd preset rules
Line；Region between the riverbank region inner boundary sub-line and the riverbank area outer sub-line is riverbank subregion；It is right
In each data point of the point cloud in the riverbank subregion, it is denoted as data point P, closes on searching and matching method by sampled point,
The sampled point nearest apart from data point P is searched, sampled point R is denoted as；Then, judge whether the height value of data point P is less than
The height value of sampled point R filters out data point P if it is less, showing that data point P is the conclusion of exceptional data point；Otherwise,
Retain data point P；
It so constantly recycles, until the equal matching judgment of all data points in the subregion of riverbank is primary；Return again to step 6；
Step 6, filtered data point in the sampled point and riverbank subregion in riverbank region inner boundary sub-line is formed final
Point cloud data for modeling.
2. the processing method of riverbank region according to claim 1 point cloud data, which is characterized in that in step 2, to described
Original point cloud data is pre-processed, specifically:
The ground classification data for obtaining original point cloud data filters out non-riverbank region point cloud data according to ground classification data,
Obtain riverbank region point cloud data.
3. the processing method of riverbank region according to claim 1 point cloud data, which is characterized in that in step 5.2, by
1 preset rules are upsampled to m sampled point in the riverbank region inner boundary sub-line, refer to:
Sampling step length is set according to dem data plane precision, by the sampling step length, in the riverbank region inner boundary sub-line
Sample m sampled point.
4. the processing method of riverbank region according to claim 1 point cloud data, which is characterized in that in step 5.2, to every
A sampled point assigns height value, further includes:
Sampled point Q1, sampled point Q2 ... are successively denoted as by the direction apart from initial data point A from the near to the distant for m sampled point
Sampled point Qm；
Then: the height value of sampled point Q1-initial data point A height value=sampled point Q2 height value-sampled point Q1 elevation
Value=sampled point Q3 height value-sampled point Q2 height value ...=sampled point Qm height value-sampled point Qm-1 height value
Height value-sampled point Qm height value of=end data point B.
5. the processing method of riverbank region according to claim 1 point cloud data, which is characterized in that in step 5.3, by
2 preset rules determine riverbank area outer sub-line in the outside of the riverbank region inner boundary sub-line, specifically:
According to dem data precision, riverbank width value is set；According to the riverbank width value, the riverbank area outer is determined
Sub-line is substantially parallel the riverbank area outer sub-line with the riverbank region inner boundary sub-line, also, the riverbank area
The distance of overseas boundary sub-line to the riverbank region inner boundary sub-line is equal to the riverbank width value.
6. the processing method of riverbank region according to claim 1 point cloud data, which is characterized in that after step 3, also wrap
It includes:
According to riverbank region inner edge boundary line, corresponding river region planar data are constructed；
River region planar data are filtered by spatial relationship, the point cloud data in river region is filtered out.
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