[go: up one dir, main page]

Livens et al., 2016 - Google Patents

Radiometric calibration of the COSI hyperspectral RPAS camera

Livens et al., 2016

View PDF
Document ID
16236109137243595653
Author
Livens S
Blommaert J
Nuyts D
Sima A
Baeck P
Delauré B
Publication year
Publication venue
2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

External Links

Snippet

The COSI hyperspectral imaging system, suitable for small RPAS, is able to produce high resolution hyperspectral data products. By extensive inflight testing, we have identified the main challenges for achieving reliable high quality results. Based on these insights, we …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colour
    • G01J3/28—Investigating the spectrum
    • G01J3/30—Measuring the intensity of spectral line directly on the spectrum itself
    • G01J3/36—Investigating two or more bands of a spectrum by separate detectors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colour
    • G01J3/28—Investigating the spectrum
    • G01J3/2823—Imaging spectrometer
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/30—Transforming light or analogous information into electric information
    • H04N5/33—Transforming infra-red radiation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, TV cameras, video cameras, camcorders, webcams, camera modules for embedding in other devices, e.g. mobile phones, computers or vehicles
    • H04N5/225—Television cameras; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, video cameras, camcorders, webcams, camera modules for embedding in other devices, e.g. mobile phones, computers or vehicles
    • H04N5/232—Devices for controlling television cameras, e.g. remote control; Control of cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, TV cameras, video cameras, camcorders, webcams, camera modules for embedding in, e.g. mobile phones, computers or vehicles
    • H04N5/23238—Control of image capture or reproduction to achieve a very large field of view, e.g. panorama

Similar Documents

Publication Publication Date Title
Honkavaara et al. Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small unmanned airborne vehicle (UAV)
Aasen et al. Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers–From theory to application
Tu et al. Optimising drone flight planning for measuring horticultural tree crop structure
Aasen et al. Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance
Honkavaara et al. Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system
Yang A high-resolution airborne four-camera imaging system for agricultural remote sensing
Wang et al. Unmanned Aerial System multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition
Mäkynen et al. Unmanned aerial vehicle (UAV) operated megapixel spectral camera
CN108346143A (en) A kind of crop disease monitoring method and system based on the fusion of unmanned plane multi-source image
Chander et al. Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study
Cubero-Castan et al. Assessment of the radiometric accuracy in a target less work flow using Pix4D software
Nocerino et al. Geometric calibration and radiometric correction of the maia multispectral camera
Clemens Procedures for correcting Digital Camera Imagery Acquired by the AggieAir remote sensing platform
Köppl et al. Hyperspectral reflectance measurements from UAS under intermittent clouds: Correcting irradiance measurements for sensor tilt
Kurihara et al. Unmanned aerial vehicle (UAV)-based hyperspectral imaging system for precision agriculture and forest management
Ahamed et al. Tower remote-sensing system for monitoring energy crops; image acquisition and geometric corrections
Gautam et al. Footprint determination of a spectroradiometer mounted on an unmanned aircraft system
Näsi et al. UAS based tree species identification using the novel FPI based hyperspectral cameras in visible, NIR and SWIR spectral ranges
WO2019148122A1 (en) Multispectral filters
Crusiol et al. Reflectance calibration of UAV-based visible and near-infrared digital images acquired under variant altitude and illumination conditions
WO2017017929A1 (en) Vegetation index calculation method and vegetation index calculation device
Proctor et al. Workflow for building a hyperspectral UAV: Challenges and opportunities
Fawcett et al. Investigating impacts of calibration methodology and irradiance variations on lightweight drone-based sensor derived surface reflectance products
Sima et al. Compact hyperspectral imaging system (COSI) for small remotely piloted aircraft systems (RPAS)–system overview and first performance evaluation results
Sankararao et al. Workflow and calibration of airborne hyperspectral imaging system