CN111679287B - Active video three-dimensional hyperspectral imaging method - Google Patents
Active video three-dimensional hyperspectral imaging method Download PDFInfo
- Publication number
- CN111679287B CN111679287B CN202010507729.3A CN202010507729A CN111679287B CN 111679287 B CN111679287 B CN 111679287B CN 202010507729 A CN202010507729 A CN 202010507729A CN 111679287 B CN111679287 B CN 111679287B
- Authority
- CN
- China
- Prior art keywords
- frequency
- target scene
- light
- spectral
- laser
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000000701 chemical imaging Methods 0.000 title claims abstract description 20
- 238000001228 spectrum Methods 0.000 claims abstract description 19
- 230000035559 beat frequency Effects 0.000 claims abstract description 14
- 230000003595 spectral effect Effects 0.000 claims description 25
- 238000005259 measurement Methods 0.000 claims description 15
- 238000001514 detection method Methods 0.000 claims description 11
- 239000000126 substance Substances 0.000 claims description 4
- 230000007547 defect Effects 0.000 abstract description 3
- 230000001678 irradiating effect Effects 0.000 abstract 1
- 238000003384 imaging method Methods 0.000 description 8
- 230000003287 optical effect Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 4
- 230000008447 perception Effects 0.000 description 3
- 239000000463 material Substances 0.000 description 2
- 229920000742 Cotton Polymers 0.000 description 1
- 238000002591 computed tomography Methods 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 238000001307 laser spectroscopy Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 239000004033 plastic Substances 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- -1 snow Polymers 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002023 wood Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J3/2823—Imaging spectrometer
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/08—Systems determining position data of a target for measuring distance only
- G01S17/32—Systems determining position data of a target for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated
- G01S17/34—Systems determining position data of a target for measuring distance only using transmission of continuous waves, whether amplitude-, frequency-, or phase-modulated, or unmodulated using transmission of continuous, frequency-modulated waves while heterodyning the received signal, or a signal derived therefrom, with a locally-generated signal related to the contemporaneously transmitted signal
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/481—Constructional features, e.g. arrangements of optical elements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/491—Details of non-pulse systems
- G01S7/4912—Receivers
- G01S7/4913—Circuits for detection, sampling, integration or read-out
- G01S7/4914—Circuits for detection, sampling, integration or read-out of detector arrays, e.g. charge-transfer gates
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Electromagnetism (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses an active video stereo hyperspectral imaging method, which comprises the steps of firstly, irradiating a target scene by using monochromatic beam-expanded laser with the frequency of f as a light source; a beam with the frequency of f + delta f is used as reference light at a receiving end through a frequency shift device, and the reference light and light reflected by the target scene are subjected to vector superposition on a detector; adjusting the frequency of the irradiated light in the step 1, and keeping the frequency of the reference light unchanged or the frequency beat frequency changed to enable the beat frequency delta f to be changed in an exponential law; and comparing the gray level sequence measured by each pixel of the target scene with the gray level sequence of the reference point to obtain the depth information of each point of the target scene relative to the reference point, and further obtaining the spectrum cube data of the target scene. The method can overcome the defects of low spatial resolution, few spectrum wave bands and no video image of the common spectrum scanning laser radar instrument.
Description
Technical Field
The invention relates to the technical field of spectral imaging, in particular to an active video three-dimensional hyperspectral imaging method.
Background
The imaging spectrometer can simultaneously acquire a two-dimensional space image and one-dimensional spectral information of a target, can visually reflect the geometric morphology of the target to be detected, can provide the physicochemical properties of the target, and is a detection means combined with a map. The hyperspectral imaging technology can realize the identification of an interested target, if the target is accurately identified and understood, more accurate information of an interested target area, such as the terrain and the landform of the target area, the accurate three-dimensional space position of the target and the like, especially the three-dimensional coordinate information of the target can directly influence the hitting precision, and meanwhile, the three-dimensional space information/depth information and spectral information of the target are obtained, and the problems can be solved by the stereo hyperspectral imaging technology.
The hyperspectral imaging technology is divided in principle and mainly comprises a dispersive type, an interference type, a computed tomography type, a diffractive optical element type and the like. In order to simultaneously acquire three-dimensional spatial information/depth information and spectral information of a target, in recent years, data acquisition and fusion by using various multi-sensor cooperation, for example, a laser radar imaging system and a visible/infrared camera cooperation mode, gradually appears. However, due to the differences of the imaging mechanism and the data acquisition continuity (lidar), the imaging lidar has the disadvantages as a detection means, for example, compared with passive camera imaging, the imaging lidar has the characteristics of low transverse resolution, lack of texture information of a target and insufficient flight stability of a vehicle-mounted/airborne platform, increases the registration difficulty of data acquired by different platforms, and greatly restricts the multidimensional data fusion processing precision and the information extraction efficiency, so that a scheme for integrally acquiring stereo imaging and hyperspectral imaging data is urgently needed from a data acquisition source.
Disclosure of Invention
The invention aims to provide an active video three-dimensional hyperspectral imaging method, which can overcome the defects of low spatial resolution, few spectral bands and no video image of a common spectral scanning laser radar instrument and is suitable for environment detection requirements needed in civil fields such as information industry, remote sensing perception and the like.
The purpose of the invention is realized by the following technical scheme:
an active video stereoscopic hyperspectral imaging method, the method comprising:
step 1, using monochromatic beam-expanded laser with frequency f as a light source to irradiate a target scene;
According to the technical scheme provided by the invention, the method can overcome the defects of low spatial resolution, few spectrum wave bands and no video image of a common spectrum scanning laser radar instrument, and is suitable for environment detection requirements needed in civil fields such as information industry, remote sensing perception and the like.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an active video stereoscopic hyperspectral imaging method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an optical path of active video stereoscopic hyperspectral imaging according to an embodiment of the invention;
fig. 3 is a schematic optical path diagram of a spectrum measurement mode according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The following will describe the embodiments of the present invention in further detail with reference to the accompanying drawings, and as shown in fig. 1, a schematic flow chart of an active video stereoscopic hyperspectral imaging method provided by the embodiments of the present invention is shown, where the method includes:
step 1, using monochromatic beam expanding laser with frequency f as a light source to irradiate a target scene;
fig. 2 is a schematic diagram of an optical path of active video stereoscopic hyperspectral imaging according to an embodiment of the invention, and a laser light source irradiates a target scene through an optical component.
as shown in fig. 2, reference light with a frequency of f + Δ f is obtained through a frequency shift device and a beam splitter, and vector-superposed with light reflected by the target scene on an area array detector. And delta f is beat frequency, the gray scale of each pixel of the target scene can change in brightness and darkness due to different depths of corresponding object points, and the depth difference range corresponding to one brightness and darkness period is inversely proportional to the beat frequency delta f.
wherein the reference point is chosen near the center of the target scene.
In this step, in the process of acquiring the spectral cube data, the depth measurement accuracy and the unambiguous measurement range are respectively determined by the maximum Δ f and the minimum Δ f;
to achieve a measurement accuracy of 0.1 meter and a 500 meter unambiguous measurement range, a maximum Δ f and a minimum Δ f require 1.5Ghz and 500kHz, respectively.
In a specific implementation, the method further includes a spectral measurement mode, as shown in fig. 3, a schematic light path diagram of the spectral measurement mode according to the embodiment of the present invention, and the specific process includes:
when monochromatic beam expanding laser is used as a light source to irradiate a target scene, the reference light is closed, a scene image of a spectral line is obtained on a detector, and the spectral resolution is determined by the monochromaticity of the irradiated light;
the wide-spectrum laser source covering visible light and near infrared is used as irradiation light, and the characteristic spectral line of a specific substance in the target scene is selected for irradiation, so that key spectral characteristic information of the target scene is obtained efficiently. Here, the number of spectral bands for direct detection of the spectrum can also be changed by changing the laser wavelength of the monochromatic expanded beam laser.
In a specific implementation, the specific substance may be a substance such as an obstacle that may be encountered in the field of unmanned driving, for example, skin, cotton, snow, plastic, metal, wood, and the like.
According to the spectrum measurement mode, the spectrum cube of a target scene is directly detected and obtained through the light source, the laser frequency modulation timeliness is fully utilized, a plurality of parameters of multidimensional information are analyzed in real time in the detection process according to the self-adaptive sampling principle, the high spectrum compressed sensing sparse reconstruction technology of multidimensional data is matched, the redundancy of detection data is reduced, and a foundation is laid for realizing the high spectrum rapid active obtaining technology of extremely high spectrum band number (spectrum band number > 300).
In addition, in the specific implementation, the frequency modulation frequency and the frequency difference can be adjusted by changing the laser wavelength of the laser light source, so that the distance depth extreme value which can be directly detected by laser ranging is changed.
It is noted that those skilled in the art will be familiar with the art to which this invention relates. For example, the number of optical beam expanders in the imaging system and related parameters, including the aperture size and thickness of the converging lens and the optical materials used, can be adjusted as required.
In summary, the method according to the embodiment of the present invention utilizes a high-precision laser difference frequency technique and a phase depth inversion technique to achieve distance measurement and laser spectroscopy to achieve material property detection on the basis of broadband continuous frequency modulation laser light source research, thereby providing possibility for a spectrum/depth/image information integrated active acquisition technique.
The method can expand the civilized application range of the integrated detection technology of the three-dimensional depth information/spectral information in the intelligent unmanned vehicle, reduce the industrial engineering complexity, improve the spatial resolution, the spectral quality and the number of spectral bands of a recovered image, give smooth perception experience of the video environment, enhance the detection performance of the intelligent unmanned vehicle technology on the complex environment and the target, effectively improve the multi-target early warning, reconnaissance, tracking and identification capabilities, and enable the unmanned vehicle to autonomously make judgment of 'directly passing through a vs detour' when facing an obstacle, thereby enhancing the intelligent driving efficiency in the complex and variable environment.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. An active video stereo hyperspectral imaging method, the method comprising:
step 1, using monochromatic beam-expanded laser with frequency f as a light source to irradiate a target scene;
step 2, using a light beam with the frequency of f + delta f as reference light at a receiving end through a frequency shift device, and carrying out vector superposition on the reference light and light reflected by the target scene on a detector; wherein, Δ f is beat frequency, gray scale can change in brightness and darkness due to different depths of corresponding object points of each pixel of the target scene, and a depth difference range corresponding to a brightness and darkness period is inversely proportional to the beat frequency Δ f;
step 3, adjusting the frequency of the irradiated light in the step 1, but keeping the frequency of the reference light unchanged or the frequency beat frequency change, so that the beat frequency delta f is changed in an exponential law;
step 4, comparing the gray level sequence measured by each pixel of the target scene with the gray level sequence of a reference point to obtain depth information of each point of the target scene relative to the reference point, and further obtaining spectrum cube data of the target scene; wherein the reference point is chosen near the center of the target scene.
2. The active video stereo hyperspectral imaging method according to claim 1, further comprising a spectral measurement mode, wherein the specific process is as follows:
when monochromatic beam expanding laser is used as a light source to irradiate a target scene, the reference light is closed, a scene image of a spectral line is obtained on a detector, and the spectral resolution is determined by the monochromaticity of the irradiated light;
the wide-spectrum laser source covering visible light and near infrared is used as irradiation light, and the characteristic spectral line of a specific substance in the target scene is selected for irradiation, so that the key spectral characteristic information of the target scene is obtained at high efficiency.
3. The active video stereo hyperspectral imaging method according to claim 1,
the frequency modulation frequency and the frequency difference are adjusted by changing the laser wavelength of the laser light source, so that the distance depth extreme value which can be directly detected by laser ranging is changed.
4. The active video stereo hyperspectral imaging method according to claim 1,
in the spectral measurement mode, the number of spectral bands of the spectral direct detection is changed by changing the laser wavelength of the monochromatic expanded beam laser.
5. The active video stereoscopic hyperspectral imaging method according to claim 1, wherein in step 4, in the process of acquiring the spectral cube data, the depth measurement accuracy and the unambiguous measurement range are respectively determined by a maximum Δ f and a minimum Δ f;
to achieve a measurement accuracy of 0.1 meter and a 500 meter unambiguous measurement range, a maximum Δ f and a minimum Δ f would require 1Ghz and 500kHz, respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010507729.3A CN111679287B (en) | 2020-06-05 | 2020-06-05 | Active video three-dimensional hyperspectral imaging method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010507729.3A CN111679287B (en) | 2020-06-05 | 2020-06-05 | Active video three-dimensional hyperspectral imaging method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111679287A CN111679287A (en) | 2020-09-18 |
| CN111679287B true CN111679287B (en) | 2023-01-17 |
Family
ID=72435197
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010507729.3A Active CN111679287B (en) | 2020-06-05 | 2020-06-05 | Active video three-dimensional hyperspectral imaging method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111679287B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115615548B (en) * | 2022-10-13 | 2024-05-28 | 哈尔滨工业大学 | Multi-angle multi-spectrum three-dimensional imaging module and module design method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102349205A (en) * | 2009-03-06 | 2012-02-08 | Imra美国公司 | Optical scanning and imaging systems based on dual pulsed laser systems |
| CN105571716A (en) * | 2015-12-22 | 2016-05-11 | 哈尔滨工业大学 | Traveling line sampling high spectral data object detection method based on difference and convolution kernel |
| CN106056591A (en) * | 2016-05-25 | 2016-10-26 | 哈尔滨工业大学 | Method for estimating urban density through fusion of optical spectrum image and laser radar data |
| CN106644077A (en) * | 2016-12-22 | 2017-05-10 | 中国科学院西安光学精密机械研究所 | Active and passive stereo spectral imaging device with high-precision field matching and detection method thereof |
| CN110553992A (en) * | 2019-08-12 | 2019-12-10 | 中电科仪器仪表有限公司 | Infrared spectrum high-speed measurement system and method |
| CN110869695A (en) * | 2017-04-19 | 2020-03-06 | Drs网络和成像系统公司 | Active hyperspectral imaging equipment |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9818193B2 (en) * | 2012-01-30 | 2017-11-14 | Scanadu, Inc. | Spatial resolution enhancement in hyperspectral imaging |
| WO2020041307A1 (en) * | 2018-08-21 | 2020-02-27 | Battelle Memorial Institute | Active hyperspectral imaging with a laser illuminator and without dispersion |
-
2020
- 2020-06-05 CN CN202010507729.3A patent/CN111679287B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102349205A (en) * | 2009-03-06 | 2012-02-08 | Imra美国公司 | Optical scanning and imaging systems based on dual pulsed laser systems |
| CN105571716A (en) * | 2015-12-22 | 2016-05-11 | 哈尔滨工业大学 | Traveling line sampling high spectral data object detection method based on difference and convolution kernel |
| CN106056591A (en) * | 2016-05-25 | 2016-10-26 | 哈尔滨工业大学 | Method for estimating urban density through fusion of optical spectrum image and laser radar data |
| CN106644077A (en) * | 2016-12-22 | 2017-05-10 | 中国科学院西安光学精密机械研究所 | Active and passive stereo spectral imaging device with high-precision field matching and detection method thereof |
| CN110869695A (en) * | 2017-04-19 | 2020-03-06 | Drs网络和成像系统公司 | Active hyperspectral imaging equipment |
| CN110553992A (en) * | 2019-08-12 | 2019-12-10 | 中电科仪器仪表有限公司 | Infrared spectrum high-speed measurement system and method |
Non-Patent Citations (5)
| Title |
|---|
| Generation of Carrier-Envelope Phase Stabilized Laser from;Liu Yangyang等;《2017 Conference on Lasers and Electro-Optics (CLEO)》;20171231 * |
| 大气遥感高光谱分辨率激光雷达研究进展;刘东等;《红外与激光工程》;20150925;第44卷(第09期);2535-2546 * |
| 紧凑型图像复分光谱成像系统光学设计及优化;马培培等;《光子学报》;20160731;第45卷(第07期);0722004-1-0722004-6 * |
| 连续推扫计算光谱成像技术;相里斌等;《光谱学与光谱分析》;20180430;第38卷(第04期);1256-1261 * |
| 高光谱-激光共光路联测设计与试验;付成群等;《兵工学报》;20161115;第37卷(第11期);2002-2009 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111679287A (en) | 2020-09-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6928414B2 (en) | Methods and systems for classifying objects within point cloud datasets | |
| JP7297017B2 (en) | Method and apparatus for calibrating external parameters of on-board sensors and related vehicles | |
| US10921245B2 (en) | Method and systems for remote emission detection and rate determination | |
| Palm et al. | Radargrammetric DEM extraction over urban area using circular SAR imagery | |
| Ni et al. | Features of point clouds synthesized from multi-view ALOS/PRISM data and comparisons with LiDAR data in forested areas | |
| Oliveira et al. | Generating a hyperspectral digital surface model using a hyperspectral 2D frame camera | |
| Samczynski | Superconvergent velocity estimator for an autofocus coherent mapdrift technique | |
| JP2590689B2 (en) | Interferometric synthetic aperture radar system and terrain change observation method | |
| Bimber et al. | Synthetic aperture imaging with drones | |
| Nguyen et al. | Structure overview of vegetation detection. A novel approach for efficient vegetation detection using an active lighting system | |
| Holmgren et al. | Estimation of tree position and stem diameter using simultaneous localization and mapping with data from a backpack-mounted laser scanner | |
| CN111679287B (en) | Active video three-dimensional hyperspectral imaging method | |
| Portugal-Zambrano et al. | Robust range finder through a laser pointer and a webcam | |
| Teizer et al. | Range imaging as emerging optical three-dimension measurement technology | |
| Rouveure et al. | Description and experimental results of a panoramic k‐band radar dedicated to perception in mobile robotics applications | |
| Rouveure et al. | Distance and angular resolutions improvement for a ground-based radar imager | |
| Grebner et al. | Simultaneous localization and mapping (SLAM) for synthetic aperture radar (SAR) processing in the field of autonomous driving | |
| Powers et al. | Spectral LADAR: towards active 3D multispectral imaging | |
| Assou et al. | Synthetic photoconductive antenna array for terahertz 3-D imaging and spectroscopy | |
| Markelin et al. | Geometric processing workflow for vertical and oblique hyperspectral frame images collected using UAV | |
| RU2672092C1 (en) | Method of measuring the angular position of terrestrial fixed radio-contrast objects | |
| US10495515B2 (en) | Adaptive, very high resolution imaging spectrometer | |
| CN109903307A (en) | A kind of moving target detecting method based on SAIR | |
| Zhao et al. | High throughput system for plant height and hyperspectral measurement | |
| Altuntas | Pile volume measurement by range imaging camera in indoor environment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |