Sahoo et al., 2013 - Google Patents
Processing of hyperspectral remote sensing dataSahoo et al., 2013
View PDF- Document ID
- 12725569360256007899
- Author
- Sahoo R
- Pargal S
- Pradhan S
- Krishna G
- Gupta V
- Publication year
- Publication venue
- Division of Agriculture Physics, Indian Agriculture Research Institute: New Delhi, India
External Links
Snippet
Multispectral remote sensing data have been potentially explored in India for various applications. A major limitation of multispectral broadband remote sensing products is that they use average spectral information over broadband widths resulting in loss of critical …
- 230000003595 spectral 0 abstract description 217
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
- G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
-
- 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
- G01J3/02—Details
- G01J3/0205—Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows
- G01J3/024—Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows using means for illuminating a slit efficiently (e.g. entrance slit of a spectrometer or entrance face of fiber)
-
- 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
-
- 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
- G01J3/12—Generating the spectrum; Monochromators
-
- 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
- G01J5/00—Radiation pyrometry
- G01J2005/0077—Imaging
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/84—Systems specially adapted for particular applications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
- G06T3/40—Scaling the whole image or part thereof
- G06T3/4053—Super resolution, i.e. output image resolution higher than sensor resolution
- G06T3/4061—Super resolution, i.e. output image resolution higher than sensor resolution by injecting details from a different spectral band
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10832390B2 (en) | Atmospheric compensation in satellite imagery | |
| North et al. | Retrieval of land surface bidirectional reflectance and aerosol opacity from ATSR-2 multiangle imagery | |
| Dennison et al. | A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper | |
| Bernstein et al. | Validation of the QUick atmospheric correction (QUAC) algorithm for VNIR-SWIR multi-and hyperspectral imagery | |
| Harmel et al. | Estimation of the sunglint radiance field from optical satellite imagery over open ocean: Multidirectional approach and polarization aspects | |
| Harmel et al. | Influence of polarimetric satellite data measured in the visible region on aerosol detection and on the performance of atmospheric correction procedure over open ocean waters | |
| Sterckx et al. | Atmospheric correction of APEX hyperspectral data | |
| Nag et al. | Observing system simulations for small satellite formations estimating bidirectional reflectance | |
| Fawcett et al. | Advancing retrievals of surface reflectance and vegetation indices over forest ecosystems by combining imaging spectroscopy, digital object models, and 3D canopy modelling | |
| Rossi et al. | Predicting soil nutrients with PRISMA hyperspectral data at the field scale: the Handan (south of Hebei Province) test cases | |
| Kalacska et al. | Quality control assessment of the Mission Airborne Carbon 13 (mac-13) hyperspectral imagery from Costa Rica | |
| Obata et al. | Derivation of a MODIS-compatible enhanced vegetation index from visible infrared imaging radiometer suite spectral reflectances using vegetation isoline equations | |
| Galvão et al. | A hyperspectral experiment over tropical forests based on the EO-1 orbit change and PROSAIL simulation | |
| Tian et al. | Estimation of chlorophyll-a concentration in coastal waters with HJ-1A HSI data using a three-band bio-optical model and validation | |
| Wang et al. | AERONET-based surface reflectance validation network (ASRVN) data evaluation: Case study for railroad valley calibration site | |
| Sahoo et al. | Processing of hyperspectral remote sensing data | |
| Davies et al. | Synergistic angular and spectral estimation of aerosol properties using CHRIS/PROBA-1 and simulated Sentinel-3 data | |
| Lee et al. | Absolute radiometric calibration of the KOMPSAT-2 multispectral camera using a reflectance-based method and empirical comparison with IKONOS and QuickBird images | |
| Gómez-Chova et al. | Cloud detection for CHRIS/Proba hyperspectral images | |
| Coburn et al. | Temporal dynamics of sand dune bidirectional reflectance characteristics for absolute radiometric calibration of optical remote sensing data | |
| Minu et al. | Hybrid atmospheric correction algorithms and evaluation on VNIR/SWIR Hyperion satellite data for soil organic carbon prediction | |
| Lee et al. | Coordinating high-resolution hyperspectral and RGB video acquisition of dynamic natural water scenes | |
| Pieper et al. | Hyperspectral SWIR sensor parameterization for optimal methane detection | |
| Bogliolo et al. | Inspecting MIVIS capability to retrieve chemical–mineralogical information: evaluation and analysis of VNIR–SWIR data acquired on a volcanic area | |
| Moscadelli et al. | Temperature-emissivity separation assessment in a sub-urban scenario |