CN114219894A - Three-dimensional modeling method, device, equipment and medium based on chromatography SAR point cloud - Google Patents

Three-dimensional modeling method, device, equipment and medium based on chromatography SAR point cloud Download PDF

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CN114219894A
CN114219894A CN202111536990.7A CN202111536990A CN114219894A CN 114219894 A CN114219894 A CN 114219894A CN 202111536990 A CN202111536990 A CN 202111536990A CN 114219894 A CN114219894 A CN 114219894A
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elevation
statistical
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周良将
韩冬
焦泽坤
吴一戎
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Aerospace Information Research Institute of CAS
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Abstract

The invention discloses a three-dimensional modeling method based on a chromatography SAR point cloud, which comprises the following steps: projecting the chromatographic SAR three-dimensional point cloud of the detection target into a longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical chart and a point density statistical chart; amplitude filtering is carried out on the fusion result of the first elevation statistical chart and the point density statistical chart, a second elevation statistical chart is obtained according to the filtered non-zero value position, and the contour line of the detection target is extracted based on the second elevation statistical chart; extracting third elevation statistical graphs of a plurality of elevation layers from the second elevation statistical graphs, selecting the third elevation statistical graphs with the largest number of points, and taking elevation information of the third elevation statistical graphs as elevation information of a detection target; and constructing a three-dimensional model based on the contour line and elevation information of the detection target. The disclosure also provides a three-dimensional modeling device, equipment and medium based on the chromatography SAR point cloud. The method can effectively eliminate the influence of the stray points in the oblique height direction in the low and short feature target and the three-dimensional point cloud on the three-dimensional modeling, and realize the panoramic three-dimensional modeling of the observation target.

Description

Three-dimensional modeling method, device, equipment and medium based on chromatography SAR point cloud
Technical Field
The disclosure relates to the technical field of radar information acquisition and processing, in particular to a three-dimensional modeling method and device based on a chromatographic SAR point cloud, an electronic device and a medium.
Background
With the technical development of Synthetic Aperture Radars (SAR) and the widening of application requirements, the SAR three-dimensional imaging technology gradually plays an important role in many application fields, such as three-dimensional city map construction, forest biomass inversion, military battlefield survey and the like. The chromatographic SAR (synthetic aperture radar) originates from the last 90 th century, forms an equivalent synthetic aperture along an oblique height direction in a multi-observation mode, and has the resolution capability of a third dimension. The tomography SAR works in a low-frequency wave band, is insensitive to influence factors such as motion control of a radar carrier platform and cross-track wind, and has good non-fuzzy elevation along the oblique height direction, so that effective tomography data can be acquired on the premise of limited number of observation tracks. The three-dimensional reconstruction of the oblique direction is carried out by using a Compressed Sensing (CS) algorithm, so that the problem that the resolution of the chromatographic SAR in the oblique direction is not ideal can be solved, and the super resolution is realized theoretically.
The three-dimensional point cloud of the ground object obtained by the chromatography SAR is abstract and difficult to interpret, so that research on three-dimensional modeling technology is necessary to obtain a more intuitive three-dimensional model of the ground object. In recent years, researchers related to moral navigation have developed a series of modeling studies on tomographic SAR three-dimensional point clouds observed at a single azimuth. However, due to the existence of the shielding problem, the single-azimuth observation angle tomography SAR three-dimensional point cloud has serious ground object structure information loss, and complete three-dimensional structure information of the ground object cannot be acquired. Three-dimensional modeling is usually directed to a target with a certain elevation, and therefore, the three-dimensional point cloud of a low short feature has a serious influence on the three-dimensional modeling process. Meanwhile, due to the restriction of the heavy-rail flight capability and the heavy-rail flight times of the radar carrier platform, a plurality of stray points exist in the chromatographic SAR three-dimensional point cloud along the oblique height direction, and the three-dimensional modeling can be seriously influenced.
Disclosure of Invention
In view of the above problems, the present invention provides a three-dimensional modeling method, apparatus, electronic device and medium based on a tomographic SAR point cloud, so as to extract a three-dimensional model from a tomographic SAR panoramic point cloud.
One aspect of the disclosure provides a three-dimensional modeling method based on a tomographic SAR point cloud, comprising: projecting the chromatographic SAR three-dimensional point cloud of the detection target into a longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical chart and a point density statistical chart; performing amplitude filtering on a fusion result of the first elevation statistical chart and the point density statistical chart, obtaining a second elevation statistical chart according to a filtered non-zero value position, and extracting a contour line of the detection target based on the second elevation statistical chart; extracting third elevation statistical graphs of a plurality of elevation layers from the second elevation statistical graphs, selecting the third elevation statistical graphs with the most point quantity statistics, and taking the corresponding elevation information as the elevation information of the detection target; and constructing a three-dimensional model based on the contour line and the elevation information of the detection target.
Optionally, the projecting the chromatography SAR three-dimensional point cloud of the detection target into the longitude and latitude coordinate plane of the ground distance to obtain the first elevation statistical map and the point density statistical map includes: acquiring a chromatographic SAR three-dimensional point cloud obtained by observing the detection target at multiple azimuth angles; and after the registration operation is carried out on the chromatography SAR three-dimensional point cloud, projecting the three-dimensional point cloud into a longitude and latitude coordinate plane of the ground distance to obtain the first elevation statistical map and the point density statistical map.
Optionally, the amplitude filtering the fusion result of the first elevation statistical map and the point density statistical map, and obtaining a second elevation statistical map according to the filtered non-zero value position includes: calculating the product of the point density statistical chart and the first elevation statistical chart to obtain a first fusion statistical chart; carrying out amplitude filtering on the first fusion statistical chart to obtain a second fusion statistical chart; and calculating the product of the positions of the non-zero elements in the second fusion statistical chart and the first elevation statistical chart to obtain the second elevation statistical chart.
Optionally, before fusing the point density histogram and the first elevation histogram, the method further includes: and performing mean filtering on the point density statistical chart and the first elevation statistical chart.
Optionally, the mean filtering the point density histogram and the first elevation histogram comprises:
Figure BDA0003412701470000031
Figure BDA0003412701470000032
wherein D is1(u, v) represents the number of points projected to the longitude and latitude coordinate plane of the distance from the point density statistical chart at the position of (u, v), D2(u, v) represents D1(u, v) the corresponding value after mean filtering, H1(u, v) represents the maximum elevation of the first elevation histogram projected to (u, v) in the latitudinal and longitudinal coordinate plane of the ground distance, H2(u, v) represents H1(u, v) the corresponding value, N, after mean filteringwThe length of the mean filtering is indicated.
Optionally, the constructing a three-dimensional model based on the contour line and the elevation information of the detection target includes: constructing an initial three-dimensional model based on the contour line and the elevation information of the detection target; and attaching texture information to the initial three-dimensional model by combining the two-dimensional SAR image of the detection target to obtain a final three-dimensional model.
A second aspect of the present disclosure provides a three-dimensional modeling apparatus based on a tomographic SAR point cloud, including: the elevation map acquisition module is used for projecting the chromatographic SAR three-dimensional point cloud of the detection target into a longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical map and a point density statistical map; the amplitude filtering module is used for carrying out amplitude filtering on a fusion result of the first elevation statistical graph and the point density statistical graph, obtaining a second elevation statistical graph according to a non-zero value position after filtering, and extracting a contour line of the detection target based on the second elevation statistical graph; the elevation information acquisition module is used for extracting a third elevation statistical chart of a plurality of elevation layers from the second elevation statistical chart, selecting the third elevation statistical chart with the largest number of points, and taking the corresponding elevation information as the elevation information of the detection target; and the three-dimensional reconstruction module is used for constructing a three-dimensional model based on the contour line and the elevation information of the detection target.
Another aspect of the present disclosure provides an electronic device including: memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method for three-dimensional modeling of a tomographic SAR point cloud when executing the computer program.
Another aspect of the disclosure provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for three-dimensional modeling of a tomographic SAR point cloud.
The at least one technical scheme adopted in the embodiment of the disclosure can achieve the following beneficial effects:
the method and the device for three-dimensional modeling of the target in the embodiment of the disclosure project the registered target full-scene three-dimensional point cloud to the two-dimensional longitude and latitude plane, obtain the altitude statistical chart after amplitude filtering, and extract the contour line and the altitude information of the observed target according to the altitude statistical chart after amplitude filtering, so as to achieve three-dimensional modeling. The method can effectively eliminate the influence of the stray points in the oblique height direction in the low and short feature target and the three-dimensional point cloud on the three-dimensional modeling, and realize the panoramic three-dimensional modeling of the observation target.
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For a more complete understanding of the present disclosure and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:
fig. 1A schematically illustrates an application scenario diagram of a three-dimensional modeling method based on a tomographic SAR point cloud provided by an embodiment of the present disclosure;
fig. 1B schematically illustrates an airborne tomographic SAR flight path of an application scenario of a three-dimensional modeling method based on a tomographic SAR point cloud provided by an embodiment of the present disclosure;
fig. 2 schematically illustrates a general flowchart of a three-dimensional modeling method based on a tomographic SAR point cloud provided by an embodiment of the present disclosure;
fig. 3 schematically illustrates a detailed flowchart of a three-dimensional modeling method based on a tomographic SAR point cloud provided by an embodiment of the present disclosure;
FIG. 4 schematically illustrates a registered tomosynthesis SAR whole scene three-dimensional point cloud of an embodiment of the present disclosure;
FIG. 5A schematically illustrates a contour line of a detection target of an embodiment of the present disclosure;
FIG. 5B is a schematic illustration of a statistical variation curve of the number of points of each third high-range statistical graph in the embodiment of the present disclosure;
FIG. 6 schematically illustrates a three-dimensional model of a detected object after attachment of a texture according to an embodiment of the disclosure;
fig. 7 schematically shows a structural block diagram of a three-dimensional modeling apparatus based on a tomographic SAR point cloud provided by an embodiment of the present disclosure;
fig. 8 schematically shows a block diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Some block diagrams and/or flow diagrams are shown in the figures. It will be understood that some blocks of the block diagrams and/or flowchart illustrations, or combinations thereof, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the instructions, which execute via the processor, create means for implementing the functions/acts specified in the block diagrams and/or flowchart block or blocks.
Accordingly, the techniques of this disclosure may be implemented in hardware and/or software (including firmware, microcode, etc.). In addition, the techniques of this disclosure may take the form of a computer program product on a computer-readable medium having instructions stored thereon for use by or in connection with an instruction execution system. In the context of this disclosure, a computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the instructions. For example, the computer readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. Specific examples of the computer readable medium include: magnetic storage devices, such as magnetic tape or Hard Disk Drives (HDDs); optical storage devices, such as compact disks (CD-ROMs); a memory, such as a Random Access Memory (RAM) or a flash memory; and/or wired/wireless communication links.
Fig. 1A schematically shows an application scenario diagram of the three-dimensional modeling method for a tomographic SAR point cloud provided by the embodiment of the present disclosure, where a building is a detection target, fig. 1B schematically shows a flight path when an airborne tomographic SAR detects the detection target in fig. 1A, and the three-dimensional point cloud of the detection target is obtained through tomographic SAR observation at four different azimuth angles. In the following embodiments, the application scenarios shown in fig. 1A and 1B will be described as examples.
Fig. 2 schematically illustrates a general flowchart of a three-dimensional modeling method for a tomographic SAR point cloud according to an embodiment of the present disclosure.
As shown in fig. 2, the three-dimensional modeling method for a tomographic SAR point cloud provided by the embodiment of the present disclosure includes operations S210 to S240.
In operation S210, the tomographic SAR three-dimensional point cloud of the detection target is projected into the longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical map and a point density statistical map.
In operation S220, amplitude filtering is performed on the fusion result of the first elevation statistical map and the point density statistical map, and a second elevation statistical map is obtained according to the filtered non-zero value position, so as to extract a contour line of the probe target based on the second elevation statistical map.
In operation S230, third elevation statistical graphs of a plurality of elevation layers are extracted from the second elevation statistical graphs, the third elevation statistical graphs with the largest number of points are selected, and the elevation information corresponding to the third elevation statistical graphs is used as the elevation information of the exploration target.
In operation S240, a three-dimensional model is constructed based on the contour line and the elevation information of the probe target.
In the embodiment of the disclosure, the registered target full-scene three-dimensional point cloud is projected to a two-dimensional longitude and latitude plane, an altitude statistical map after amplitude filtering is obtained, and contour lines and altitude information of an observation target are extracted according to the altitude statistical map after amplitude filtering to realize three-dimensional modeling, so that the influence of obliquely-high stray points in a low and short feature target and the three-dimensional point cloud on the three-dimensional modeling can be effectively eliminated, and the panoramic three-dimensional modeling of the observation target is realized.
Specific embodiments of the method will be described in detail below.
Fig. 3 schematically illustrates a detailed flowchart of a three-dimensional modeling method for a tomographic SAR point cloud provided by an embodiment of the present disclosure.
As shown in fig. 3, before the method of the embodiment of the present disclosure is performed, operations S301 to S302 are included.
In operation S301, a tomographic SAR three-dimensional point cloud obtained by observing the detection target at multiple azimuth angles is obtained.
In operation S302, the tomographic SAR three-dimensional point cloud is subjected to a registration operation.
Optionally, an ICP algorithm may be adopted to perform registration on the tomographic SAR three-dimensional point cloud at different azimuth angles to obtain a full scene three-dimensional point cloud of the target. The registered tomography SAR full scene three-dimensional point cloud is shown in FIG. 4.
As shown in fig. 3, in the embodiment of the present disclosure, projecting the tomographic SAR three-dimensional point cloud of the detection target into the latitude and longitude coordinate plane, obtaining the first elevation statistical map and the point density statistical map to obtain the second elevation statistical map, and extracting the contour line of the target object therefrom, including operations S303 to S306.
In operation S303, mean filtering is performed on the point density histogram and the first elevation histogram.
The filter calculation formula is as follows:
Figure BDA0003412701470000071
Figure BDA0003412701470000072
wherein D is1(u, v) represents the number of points projected to the longitude and latitude coordinate plane of the distance from the point density statistical chart at the position of (u, v), D2(u, v) represents D1(u, v) the corresponding value after mean filtering, H1(u, v) represents the maximum elevation of the first elevation histogram projected to (u, v) in the latitudinal and longitudinal coordinate plane of the ground distance, H2(u, v) represents H1(u, v) the corresponding value, N, after mean filteringwRepresenting the size of the sliding window of the mean filtering.
In operation S304, a product of the mean-filtered point density histogram and the first elevation histogram is calculated to obtain a first fusion histogram.
By D2(u, v) and H2(u, v) obtaining a first fusion statistical graph by multiplying corresponding elements, namely:
F(u，v)＝D2(u，v)·H2(u，v)。
in operation S305, amplitude filtering is performed on the first fused statistical mapObtaining a second fusion statistical chart Fbool(u，v)。
In operation S306, a product of the second fusion statistical map and the first elevation statistical map is calculated to obtain the second elevation statistical map.
H is to be1(u, v) and FboolMultiplying corresponding elements of (u, v) to obtain a second elevation statistical chart H after amplitude filtering3，bool(u，v)。
According to the second elevation statistical chart H3，bool(u, v), extracting the contour of the target in the scene, and taking the minimum circumscribed polygon of the contour as the contour line of the three-dimensional model, as shown in fig. 5A, schematically showing the contour line of the detection target of the embodiment of the present disclosure.
In the disclosed embodiment, according to the second elevation statistical chart H3，bool(u, v) dividing a plurality of height layers with the interval of 1m from the reference imaging height 1086m to the set maximum elevation 1121m, and extracting a third height statistical chart H corresponding to each height layerpAnd counting the number of points of each third height statistical chart.
Fig. 5B schematically shows a point number statistical variation curve of each third altitude statistical chart in the embodiment of the present disclosure, and as can be seen from fig. 5B, the maximum value of the point number statistics is 1111m, and therefore 1111m is taken as the altitude of the detection target.
In the embodiment of the disclosure, an initial three-dimensional model is constructed based on the contour line and the elevation information of the detection target; and attaching texture information to the initial three-dimensional model by combining the two-dimensional SAR image of the detection target to obtain a final three-dimensional model. Fig. 6 schematically illustrates a three-dimensional model of a detected object after attachment of a texture according to an embodiment of the present disclosure.
Fig. 7 schematically shows a structural block diagram of a three-dimensional modeling device based on a tomographic SAR point cloud provided by an embodiment of the present disclosure.
As shown in fig. 7, an apparatus provided in an embodiment of the present disclosure includes: an elevation map obtaining module 710, an amplitude filtering module 720, an elevation information obtaining module 730, and a three-dimensional reconstruction module 740.
The elevation map acquisition module 710 is configured to project the tomographic SAR three-dimensional point cloud of the detection target onto the longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical map and a point density statistical map.
The amplitude filtering module 720 is configured to perform amplitude filtering on a fusion result of the first elevation statistical map and the point density statistical map, obtain a second elevation statistical map according to a filtered non-zero value position, and extract a contour line of the probe target based on the second elevation statistical map.
The elevation information obtaining module 730 is configured to extract a third elevation statistical chart of a plurality of elevation layers from the second elevation statistical chart, select the third elevation statistical chart with the largest number of points, and use the corresponding elevation information as the elevation information of the exploration target.
The three-dimensional reconstruction module 740 is configured to construct a three-dimensional model based on the contour line and elevation information of the detection target.
It is understood that the elevation map acquisition module 710, the amplitude filtering module 720, the elevation information acquisition module 730, and the three-dimensional reconstruction module 740 may be combined and implemented in one module, or any one of the modules may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present invention, at least one of the high-level diagram acquisition module 710, the amplitude filtering module 720, the elevation information acquisition module 730 and the three-dimensional reconstruction module 740 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or in a suitable combination of three implementations of software, hardware and firmware. Alternatively, at least one of the elevation map acquisition module 710, the amplitude filtering module 720, the elevation information acquisition module 730, and the three-dimensional reconstruction module 740 may be at least partially implemented as a computer program module that, when executed by a computer, may perform the functions of the respective modules.
It can be understood that the device has the same technical features as the three-dimensional modeling method based on the chromatography SAR point cloud shown in FIGS. 2 to 3, and therefore, the corresponding technical effects can be achieved, and further description is omitted here.
Fig. 8 schematically shows a block diagram of an electronic device provided in an embodiment of the present disclosure.
As shown in fig. 8, the electronic device described in this embodiment includes: electronic device 800 includes a processor 810, a computer-readable storage medium 820. The electronic device 800 may perform the method described above with reference to fig. 2 to enable detection of a particular operation.
In particular, processor 810 may include, for example, a general purpose microprocessor, an instruction set processor and/or related chip set and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), and/or the like. The processor 810 may also include on-board memory for caching purposes. Processor 810 may be a single processing unit or a plurality of processing units for performing the different actions of the method flows described with reference to fig. 2 in accordance with embodiments of the present disclosure.
Computer-readable storage medium 820 may be, for example, any medium that can contain, store, communicate, propagate, or transport the instructions. For example, a readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. Specific examples of the readable storage medium include: magnetic storage devices, such as magnetic tape or Hard Disk Drives (HDDs); optical storage devices, such as compact disks (CD-ROMs); a memory, such as a Random Access Memory (RAM) or a flash memory; and/or wired/wireless communication links.
The computer-readable storage medium 820 may include a computer program 821, which computer program 821 may include code/computer-executable instructions that, when executed by the processor 810, cause the processor 810 to perform a method flow, such as described above in connection with fig. 1, and any variations thereof.
The computer program 821 may be configured with, for example, computer program code comprising computer program modules. For example, in an example embodiment, code in computer program 821 may include one or more program modules, including for example 821A, modules 821B, … …. It should be noted that the division and number of modules are not fixed, and those skilled in the art may use suitable program modules or program module combinations according to actual situations, which when executed by the processor 810, enable the processor 810 to execute the method flows described above in connection with fig. 2-3, for example, and any variations thereof.
According to an embodiment of the present invention, at least one of the high-level-chart acquiring module 710, the amplitude filtering module 720, the elevation information acquiring module 730 and the three-dimensional reconstruction module 740 may be implemented as a computer program module described with reference to fig. 8, which, when executed by the processor 810, may implement the corresponding operations described above.
The present disclosure also provides a computer-readable medium, which may be embodied in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer readable medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
While the disclosure has been shown and described with reference to certain exemplary embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the disclosure as defined by the appended claims and their equivalents. Accordingly, the scope of the present disclosure should not be limited to the above-described embodiments, but should be defined not only by the appended claims, but also by equivalents thereof.

Claims (9)

1. A three-dimensional modeling method based on chromatography SAR point cloud is characterized by comprising the following steps:
projecting the chromatographic SAR three-dimensional point cloud of the detection target into a longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical chart and a point density statistical chart;
performing amplitude filtering on a fusion result of the first elevation statistical chart and the point density statistical chart, obtaining a second elevation statistical chart according to a filtered non-zero value position, and extracting a contour line of the detection target based on the second elevation statistical chart;
extracting third elevation statistical graphs of a plurality of elevation layers from the second elevation statistical graphs, selecting the third elevation statistical graphs with the most point quantity statistics, and taking the corresponding elevation information as the elevation information of the detection target;
and constructing a three-dimensional model based on the contour line and the elevation information of the detection target.
2. The method of claim 1, wherein the projecting the tomographic SAR three-dimensional point cloud of the detection target into the latitude and longitude coordinate plane to obtain the first elevation statistical map and the point density statistical map comprises:
acquiring a chromatographic SAR three-dimensional point cloud observed by the multi-azimuth angle of the detection target;
and after the registration operation is carried out on the chromatography SAR three-dimensional point cloud, projecting the three-dimensional point cloud into a longitude and latitude coordinate plane of the ground distance to obtain the first elevation statistical map and the point density statistical map.
3. A method according to claim 1, wherein amplitude filtering the merged results of the first elevation histogram and the point density histogram, and wherein deriving a second elevation histogram from the filtered non-zero locations comprises:
calculating the product of the point density statistical chart and the first elevation statistical chart to obtain a first fusion statistical chart;
carrying out amplitude filtering on the first fusion statistical chart to obtain a second fusion statistical chart;
and calculating the product of the positions of the non-zero elements in the second fusion statistical chart and the first elevation statistical chart to obtain the second elevation statistical chart.
4. The method according to claim 3, further comprising, prior to fusing the point density histogram and the first elevation histogram:
and performing mean filtering on the point density statistical chart and the first elevation statistical chart.
5. The method of claim 4, wherein mean filtering the point density histogram and the first elevation histogram comprises:
Figure FDA0003412701460000021
Figure FDA0003412701460000022
wherein D is1(u, v) represents the number of points projected to the longitude and latitude coordinate plane of the distance from the point density statistical chart at the position of (u, v), D2(u, v) represents D1(u, v) the corresponding value after mean filtering, H1(u, v) represents the maximum elevation of the first elevation histogram projected to (u, v) in the latitudinal and longitudinal coordinate plane of the ground distance, H2(u, v) represents H1(u, v) the corresponding value, N, after mean filteringwThe length of the mean filtering is indicated.
6. The method of claim 1, wherein constructing a three-dimensional model based on contour line and elevation information of the probe object comprises:
constructing an initial three-dimensional model based on the contour line and the elevation information of the detection target;
and attaching texture information to the initial three-dimensional model by combining the two-dimensional SAR image of the detection target to obtain a final three-dimensional model.
7. A three-dimensional modeling device based on chromatography SAR point cloud is characterized by comprising:
the elevation map acquisition module is used for projecting the chromatographic SAR three-dimensional point cloud of the detection target into a longitude and latitude coordinate plane of the ground distance to obtain a first elevation statistical map and a point density statistical map;
the amplitude filtering module is used for carrying out amplitude filtering on a fusion result of the first elevation statistical graph and the point density statistical graph, obtaining a second elevation statistical graph according to a non-zero value position after filtering, and extracting a contour line of the detection target based on the second elevation statistical graph;
the elevation information acquisition module is used for extracting a third elevation statistical chart of a plurality of elevation layers from the second elevation statistical chart, selecting the third elevation statistical chart with the largest number of point statistics, and taking the corresponding elevation information as the elevation information of the detection target;
and the three-dimensional reconstruction module is used for constructing a three-dimensional model based on the contour line and the elevation information of the detection target.
8. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of three-dimensional modeling based on tomographic SAR point cloud of any of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for tomographic SAR point cloud based three-dimensional modeling according to any one of claims 1 to 6.
CN202111536990.7A 2021-12-15 2021-12-15 Three-dimensional modeling method, device, equipment and medium based on chromatography SAR point cloud Pending CN114219894A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
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CN114677454A (en) * 2022-03-25 2022-06-28 杭州睿影科技有限公司 Image generation method and device
CN115128609A (en) * 2022-09-01 2022-09-30 中国科学院空天信息创新研究院 Satellite-borne SAR three-dimensional product generation method and device

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114677454A (en) * 2022-03-25 2022-06-28 杭州睿影科技有限公司 Image generation method and device
CN114677454B (en) * 2022-03-25 2022-10-04 杭州睿影科技有限公司 Image generation method and device
WO2023179011A1 (en) * 2022-03-25 2023-09-28 杭州睿影科技有限公司 Image generation method and device
CN115128609A (en) * 2022-09-01 2022-09-30 中国科学院空天信息创新研究院 Satellite-borne SAR three-dimensional product generation method and device

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