GB2621668A - System and method for acquiring hyperspectral image on the basis of inertial navigation system data - Google Patents

System and method for acquiring hyperspectral image on the basis of inertial navigation system data Download PDF

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Publication number
GB2621668A
GB2621668A GB2308276.1A GB202308276A GB2621668A GB 2621668 A GB2621668 A GB 2621668A GB 202308276 A GB202308276 A GB 202308276A GB 2621668 A GB2621668 A GB 2621668A
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United Kingdom
Prior art keywords
hyperspectral
inertial navigation
navigation system
images
time values
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GB2308276.1A
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GB202308276D0 (en
Inventor
He Yong
Yang Ningyuan
Bai Tiecheng
He Liwen
Nie Pengcheng
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Zhejiang University ZJU
Tarim University
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Zhejiang University ZJU
Tarim University
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Publication of GB202308276D0 publication Critical patent/GB202308276D0/en
Publication of GB2621668A publication Critical patent/GB2621668A/en
Pending legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G01C21/1656—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with passive imaging devices, e.g. cameras
    • 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
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • 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
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/16—Image acquisition using multiple overlapping images; Image stitching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/58—Extraction of image or video features relating to hyperspectral data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/17—Terrestrial scenes taken from planes or by drones
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/194—Terrestrial scenes using hyperspectral data, i.e. more or other wavelengths than RGB
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/32—Indexing scheme for image data processing or generation, in general involving image mosaicing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Automation & Control Theory (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)
  • Navigation (AREA)

Abstract

A system and method for splicing hyperspectral images on the basis of inertial navigation system data includes an autonomous mobile platform 3, a global navigation satellite system receiver 2, an inertial navigation system 4, a hyperspectral camera 5 and a controller. The global navigation satellite system (GNSS) receiver is configured to receive a GNSS signal, the controller carries out unified time service on the inertial navigation system and the hyperspectral camera according to the GNSS signal. The hyperspectral camera is configured to collect hyperspectral array images and collection time values whilst the inertial navigation system collects relative position information of centre points of the hyperspectral images. Using the time and position data all frames of the hyperspectral array images are spliced. Frames are placed in a rectangular plane coordinate system and the platform may be a ground robot or unmanned aerial vehicle.

Description

SYSTEM AND METHOD FOR ACQUIRING HYPERSPECTRAL IMAGE ON THE
BASIS OF INERTIAL NAVIGATION SYSTEM DATA
TECHNICAL FIELD
[0001] The present disclosure relates to the field of image processing, and particularly to a system and method for acquiring hyperspectral images on the basis of inertial navigation system data.
BACKGROUND
[0002] Generally, inertial navigation systems are carried on autonomous mobile platforms such as ground robots and unmanned aerial vehicles. With the aid of the inertial navigation system, information about a velocity, a yaw angle and a relative position in a navigation coordinate system can be acquired by measuring acceleration of a carrier in an inertial reference system and integrating it with time. Since the inertial navigation system neither relies on external information nor radiates energy outwards, and has a remarkable anti-external-interference ability, it can complete navigation tasks autonomously merely with an airborne apparatus. The inertial navigation system can work in the air, on the ground or even underwater. Due to an optical splitter, a hyperspectral primary image is composed of a number of lines arranged in a space, and each line has spectral information of a certain specific waveband, that is, one line corresponds to one spectral plane and is composed of a number of wavebands arranged together. In order to acquire two-dimensional information, it is required to repeatedly take photographs through an external or internal push-broom method, splice these linear arrays together to form a complete planar image, and collect spectral data.
100031 Although the hyperspectral technology has been widely used currently and has a bright prospect, data information derived from each hyperspectral scanning is scarce and has to be spliced. A current splicing method is an image processing algorithm such as a feature point matching algorithm and an overlapping region obtaining algorithm, which involves long post-processing time, enormous difficulty and poor adaptability.
SUMMARY
100041 An objective of the present disclosure is to provide a system and method for acquiring hyperspectral images on the basis of inertial navigation system data which improves splicing efficiency of the hyperspectral images.
[0005] In order to realize the above objective, the present disclosure provides a solution as follows.
100061 A system for acquiring hyperspectral images on the basis of inertial navigation system data includes an autonomous mobile platform, where the autonomous mobile platform is provided with a global navigation satellite system receiver, an inertial navigation system, a hyperspectral camera and a controller; the global navigation satellite system receiver is configured to receive a global navigation satellite system (GNSS) signal; the controller is configured to carry out unified time service on the inertial navigation system and the hyperspectral camera according to the GNSS signal; the hyperspectral camera is configured to collect hyperspectral array images and collection time values, and the inertial navigation system is configured to collect relative position information of center points of the hyperspectral array images and the collection time values; and the controller is further configured to splice all frames of the hyperspectral array images according to relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image.
[0007] Alternatively, the controller is further configured to acquire, with a starting point where the inertial navigation system starts to collect information as an origin and according to all the collection time values, relative position information corresponding to the center points of the hyperspectral array images from the inertial navigation system, and place all frames of the hyperspectral array images in a rectangular plane coordinate system according to the relative position information of the center points, so as to obtain the spliced hyperspectral image.
[0008] Alternatively, the autonomous mobile platform includes a ground mobile robot and an unmanned aerial vehicle.
[0009] The present disclosure discloses a method for acquiring hyperspectral images on the basis of inertial navigation system data. The method includes: [0010] receiving a GNSS signal by a global navigation satellite system receiver; [0011] carrying out unified time service on the inertial navigation system and the hyperspectral camera on an autonomous mobile platform according to the GNSS signal; 100121 collecting hyperspectral array images and collection time values by the hyperspectral camera, and collecting relative position information of center points of the hyperspectral array images and collection time values by the inertial navigation system; and 100131 splicing all frames of the hyperspectral array images according to the relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image.
100141 Alternatively, the splicing all frames of the hyperspectral array images according to the relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image specifically includes: [0015] acquiring, with a starting point where the inertial navigation system starts to collect information as an origin and according to all the collection time values, relative position information corresponding to the center points of the hyperspectral array images from the inertial navigation system, and placing all frames of the hyperspectral array images in a rectangular plane coordinate system according to the relative position information of the center points, so as to obtain the spliced hyperspectral image.
[0016] Alternatively, the autonomous mobile platform includes a ground mobile robot and an unmanned aerial vehicle.
100171 According to particular embodiments provided by the present disclosure, the present disclosure provides technical effects as follows: [0018] the present disclosure discloses a system and method for acquiring hyperspectral images on the basis of inertial navigation system data, the hyperspectral images are spliced on the basis of an inertial navigation system, it is not required to use a complex image processing algorithms such as a feature point matching algorithm, a speed is high, simplicity and practicability are achieved, splicing can be realized only by means of position information, and splicing efficiency of the hyperspectral images is improved. Moreover, the present disclosure is not limited to an image splicing direction, that is, horizontal, vertical and oblique splicing can be implemented by means of position information. Therefore, a moving direction of the autonomous mobile platform is not limited, and the system and method is more suitable for an outdoor scientific research environment.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to describe the technical solutions in embodiments of the present disclosure or in the prior art more clearly, accompanying drawings required to be used in the embodiments are briefly described below. Apparently, the accompanying drawings in the following descriptions show merely some embodiments of the present disclosure, and those of ordinary skill in the art can still derive other accompanying drawings from these accompanying drawings without making inventive efforts.
[0020] FIG. I is a schematic structural diagram of a system for acquiring hyperspectral images on the basis of inertial navigation system data according to the present disclosure; and 100211 FIG. 2 is a schematic flow diagram of a method for acquiring hyperspectral images on the basis of inertial navigation system data according to the present disclosure. [0022] Description of reference numerals: [0023] 1-global navigation satellite system, 2-global navigation satellite system receiver, 3-autonomous mobile platform, 4-inertial navigation system, and 5-hyperspectral camera.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0024] The technical solutions of embodiments of the present disclosure are clearly and completely described below in combination with accompanying drawings in the present disclosure. Apparently, the described embodiments are merely some embodiments rather than all embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art on the basis of the embodiments of the present disclosure without making creative efforts shall fall within the scope of protection of the present disclosure.
[0025] An objective of the present disclosure is to provide a system and method for acquiring hyperspectral images on the basis of inertial navigation system data, which improves splicing efficiency of the hyperspectral images.
[0026] In order to make the above objectives, features, and advantages of the present disclosure clearer and more comprehensible, the present disclosure will be further described in detail below in combination with accompanying drawings and particular embodiments.
[0027] FIG. I is a schematic structural diagram of a system for acquiring hyperspectral images on the basis of inertial navigation system data according to the present disclosure. As shown in FIG. 1, a system for acquiring hyperspectral images on the basis of inertial navigation system data includes an autonomous mobile platform 3, and the autonomous mobile platform 3 is provided with a global navigation satellite system receiver 2, an inertial navigation system 4, a hyperspectral camera 5 and a controller; the global navigation satellite system receiver 2 is configured to receive a global navigation satellite system (GNSS) signal 1; the controller is configured to carry out unified time service on the inertial navigation system 4 and the hyperspectral camera 5 according to the GNSS signal; the hyperspectral camera 5 is configured to collect hyperspectral array images and collection time values, and the inertial navigation system 4 is configured to collect relative position information of center points of the hyperspectral array images and the collection time values; and the controller is further configured to splice all frames of the hyperspectral array images according to relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera 5 and the collection time values acquired by the inertial navigation system 4, so as to obtain a spliced hyperspectral image.
[0028] The controller is further configured to acquire, with a starting point where the inertial navigation system 4 starts to collect information as an origin and according to all the collection time values, relative position information corresponding to the center points of the hyperspectral array images from the inertial navigation system 4, and place all frames of the hyperspectral array images in a rectangular plane coordinate system according to the relative position information of the center points, so as to obtain the spliced hyperspectral image.
100291 The hyperspectral camera 5 and the inertial navigation system are fixed on the autonomous mobile platform 3.
100301 Global navigation satellite system positioning is to use pseudoranges, ephemerises, satellite launch time and other observations of one group of satellites, and moreover, a user clock difference has to be known. A global navigation satellite system is a space-based radio navigation and positioning system that can provide users with all-weather three-dimensional coordinates and velocity and time information at any location on the earth surface or near-earth space.
[0031] The principle of using a GNSS satellite signal for time service is to take 1_ pulse per second (PPS) output by the GNSS as a reference second pulse of a post-stage time service link. [0032] The global navigation satellite system receiver 2 is specifically a GNSS-based time service receiver, and time service, that is, time synchronization is directly carried out on the inertial navigation system 4 and the hyperspectral camera 5 by the GNSS-based time service receive 100331 A working process of a system for acquiring hyperspectral images on the basis of inertial navigation system data includes: [0034] after the autonomous mobile platform 3 starts to work, the hyperspectral camera 5 and the inertial navigation system 4 start to collect data at the same time, and in a collection process, the hyperspectral camera 5 and the inertial navigation system do not interfere with each other, and information is independently collected. In the unified time service of the hyperspectral camera 5 and the inertial navigation system realized through control, information collected by the hyperspectral camera 5 is a linear array image (hyperspectral array image) at a current moment, and the data collected by the inertial navigation system is the relative position information of the center point of the hyperspectral array image and the current moment value. [0035] After the hyperspectral camera 5 completes latest collection, by corresponding the hyperspectral camera 5 to the collection time values in the inertial navigation system one by one, the center points of the linear array images of all frames of the hyperspectral images match the relative position information of the center points, that is, the relative position information of the center point is acquired.
100361 With the starting point from which the hyperspectral camera 5 and the inertial navigation system start to collect information as the origin, all frames of the hyperspectral array images collected by the hyperspectral camera 5 are placed in a rectangular plane coordinate system one by one according to the relative coordinate position information of the center points, and finally are spliced.
[0037] The autonomous mobile platform 3 includes a ground mobile robot, a remotely piloted vehicle and an unmanned aerial vehicle.
[0038] According to the present disclosure, the hyperspectral images are spliced on the basis of an inertial navigation system, it is not required to use a complex image processing algorithm such as a feature point matching algorithm, a speed is high, simplicity and practicability are achieved, splicing can be realized only by means of position information.
[0039] The present disclosure is not limited to an image splicing direction, that is, horizontal, vertical and oblique splicing can be realized by means of position information. Therefore, a moving direction of the autonomous mobile platform is not limited, and the system and method is more suitable for an outdoor scientific research environment.
[0040] FIG. 2 is a schematic flow diagram of a method for acquiring hyperspectral images on the basis of inertial navigation system data according to the present disclosure. As shown in FIG. 2, a method for acquiring hyperspectral images on the basis of inertial navigation system data includes: [0041] Step 101: receive a GNSS signal by a global navigation satellite system receiver; [0042] Step 102: carry out unified time service on the inertial navigation system and the hyperspectral camera on an autonomous mobile platform according to the GNSS signal; [0043] Step 103: collect hyperspectral array images and collection time values by the hyperspectral camera, and collect relative position information of center points of the hyperspectral array images and collection time values by the inertial navigation system; and [0044] Step 104: splice all frames of the hyperspectral array images according to relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image. [0045] The step 104 specifically includes: [0046] acquire, with a starting point where the inertial navigation system starts to collect information as an origin and according to all the collection time values, relative position information corresponding to the center points of the hyperspectral array images from the inertial navigation system, and place all frames of the hyperspectral array images in a rectangular plane coordinate system according to the relative position information of the center points, so as to obtain the spliced hyperspectral image.
[0047] The autonomous mobile platform includes a ground mobile robot and an unmanned aerial vehicle.
[0048] Each embodiment in the description is described in a progressive manner, each embodiment focuses on differences from other embodiments, and references can be made to each other for the same and similar parts between embodiments. Since the system disclosed in an embodiment corresponds to the method disclosed in another embodiment, the description is relatively simple, and reference can be made to the description of the method.
[0049] In the description, principles and implementation modes of the present disclosure are illustrated through particular embodiments, and the description of the above embodiments is only used for helping understand the method in the present disclosure and its core ideas. Moreover, those of ordinary skill in the art can make various changes in terms of particular implementation modes and the scope of application in accordance with the ideas of the present disclosure. In conclusion, the content of the description shall not be construed as limitations to the present disclosure.

Claims (6)

  1. WHAT IS CLAIMED IS: 1. A system for acquiring hyperspectral images on the basis of inertial navigation system data, comprising an autonomous mobile platform, wherein the autonomous mobile platform is provided with a global navigation satellite system receiver, an inertial navigation system, a hyperspectral camera and a controller; the global navigation satellite system receiver is configured to receive a global navigation satellite system (GNSS) signal; the controller is configured to carry out unified time service on the inertial navigation system and the hyperspectral camera according to the GNSS signal; the hyperspectral camera is configured to collect hyperspectral array images and collection time values; the inertial navigation system is configured to collect relative position information of center points of the hyperspectral array images and the collection time values; and the controller is further configured to splice all frames of the hyperspectral array images according to relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image.
  2. 2. The system for acquiring hyperspectral images on the basis of inertial navigation system data according to claim 1, wherein the controller is further configured to acquire, with a starting point where the inertial navigation system starts to collect information as an origin and according to all the collection time values, relative position information corresponding to the center points of the hyperspectral array images from the inertial navigation system, and place all frames of the hyperspectral array images in a rectangular plane coordinate system according to the relative position information of the center points, so as to obtain the spliced hyperspectral image.
  3. 3. The system for acquiring hyperspectral images on the basis of inertial navigation system data according to claim 1, wherein the autonomous mobile platform comprises a ground mobile robot and an unmanned aerial vehicle
  4. 4. A method for acquiring hyperspectral images on the basis of inertial navigation system data, comprising: receiving a GNSS signal by a global navigation satellite system receiver; carrying out unified time service on an inertial navigation system and a hyperspectral camera on an autonomous mobile platform according to the GNSS signal; collecting hyperspectral array images and collection time values by the hyperspectral camera, and collecting relative position information of center points of the hyperspectral array images and the collection time values by the inertial navigation system, and splicing all frames of the hyperspectral array images according to the relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image.
  5. 5. The method for acquiring hyperspectral images on the basis of inertial navigation system data according to claim 4, wherein the splicing all frames of the hyperspectral array images according to the relative position information of the center points of all frames of the hyperspectral array images by means of the collection time values acquired by the hyperspectral camera and the collection time values acquired by the inertial navigation system, so as to obtain a spliced hyperspectral image specifically comprises: acquiring, with a starting point where the inertial navigation system starts to collect information as an origin and according to all the collection time values, relative position information corresponding to the center points of the hyperspectral array images from the inertial navigation system, and placing all frames of the hyperspectral array images in a rectangular plane coordinate system according to the relative position information of the center points, so as to obtain the spliced hyperspectral image.
  6. 6. The method for acquiring hyperspectral images on the basis of inertial navigation system data according to claim 4, wherein the autonomous mobile platform comprises a ground mobile robot and an unmanned aerial vehicle.
GB2308276.1A 2022-06-02 2023-06-02 System and method for acquiring hyperspectral image on the basis of inertial navigation system data Pending GB2621668A (en)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106198443A (en) * 2016-06-24 2016-12-07 湖北久之洋红外系统股份有限公司 Airborne hyperspectral infrared spilled oil monitoring method and system
CN106872369A (en) * 2017-02-20 2017-06-20 交通运输部水运科学研究所 The airborne hyperspectral imaging system and method for a kind of spilled oil monitoring
US20190096033A1 (en) * 2017-09-28 2019-03-28 Eric Taipale Multiple georeferenced aerial image crop analysis and synthesis
CN113009502A (en) * 2021-03-22 2021-06-22 国网福建省电力有限公司漳州供电公司 Multispectral laser radar system and working method thereof
CN113156420A (en) * 2021-03-12 2021-07-23 中国石油大学(华东) Oil spill detection system and method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106198443A (en) * 2016-06-24 2016-12-07 湖北久之洋红外系统股份有限公司 Airborne hyperspectral infrared spilled oil monitoring method and system
CN106872369A (en) * 2017-02-20 2017-06-20 交通运输部水运科学研究所 The airborne hyperspectral imaging system and method for a kind of spilled oil monitoring
US20190096033A1 (en) * 2017-09-28 2019-03-28 Eric Taipale Multiple georeferenced aerial image crop analysis and synthesis
CN113156420A (en) * 2021-03-12 2021-07-23 中国石油大学(华东) Oil spill detection system and method
CN113009502A (en) * 2021-03-22 2021-06-22 国网福建省电力有限公司漳州供电公司 Multispectral laser radar system and working method thereof

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Pece V. Gorsevski and Paul E Gessler "The design and the development of a hyperspectral and multispectral airborne mapping system" March 2009ISPRS Journal of Photogrammetry and Remote Sensing 64(2): p184-192, DOI:10.1016/j.isprsjprs.2008.09.002 *
Pece V. Gorsevski and Paul E Gessler "The design and the development of a hyperspectral and multispectral airborne mapping system" March 2009ISPRS Journal of Photogrammetry and Remote Sensing 64(2): p184-192; *

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