Acito et al., 2017 - Google Patents
Unsupervised atmospheric compensation of airborne hyperspectral images in the VNIR spectral rangeAcito et al., 2017
View PDF- Document ID
- 18147460014684734613
- Author
- Acito N
- Diani M
- Publication year
- Publication venue
- IEEE Transactions on Geoscience and Remote Sensing
External Links
Snippet
Atmospheric compensation (AC) is a fundamental and critical step for quantitative exploitation of hyperspectral data. It is the means by which the reflectance of an object/material is estimated from the measured at-sensor radiance. Such reflectance is the …
- 230000003595 spectral 0 title abstract description 94
Classifications
-
- 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
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- 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
- G06K9/00664—Recognising scenes such as could be captured by a camera operated by a pedestrian or robot, including objects at substantially different ranges from the camera
- G06K9/00684—Categorising the entire scene, e.g. birthday party or wedding scene
-
- 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
- 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
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- 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
- G06K9/20—Image acquisition
-
- 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
- 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
- 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
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
-
- 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 | |
| De Keukelaere et al. | Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters | |
| Dennison et al. | A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper | |
| Chen et al. | Multi-source remotely sensed data fusion for improving land cover classification | |
| Bernstein et al. | Validation of the QUick atmospheric correction (QUAC) algorithm for VNIR-SWIR multi-and hyperspectral imagery | |
| Ceamanos et al. | Intercomparison and validation of techniques for spectral unmixing of hyperspectral images: A planetary case study | |
| Manakos et al. | Comparison between atmospheric correction modules on the basis of worldview-2 imagery and in situ spectroradiometric measurements | |
| Behrangi et al. | Evaluating the utility of multispectral information in delineating the areal extent of precipitation | |
| Cubero-Castan et al. | A physics-based unmixing method to estimate subpixel temperatures on mixed pixels | |
| Acito et al. | Unsupervised atmospheric compensation of airborne hyperspectral images in the VNIR spectral range | |
| Lee et al. | A review on atmospheric correction technique using satellite remote sensing | |
| Chen et al. | Aerosol‐cloud interactions in ship tracks using Terra MODIS/MISR | |
| Ariza et al. | Empirical line model for the atmospheric correction of sentinel-2A MSI images in the Caribbean Islands | |
| Axelsson et al. | Target detection in hyperspectral imagery using forward modeling and in-scene information | |
| Li et al. | An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area, China | |
| Chen et al. | Tradeoffs among multi-source remote sensing images, spatial resolution, and accuracy for the classification of wetland plant species and surface objects based on the MRS_DeepLabV3+ model | |
| Acito et al. | CWV-Net: A deep neural network for atmospheric column water vapor retrieval from hyperspectral VNIR data | |
| Grzegorski et al. | The Heidelberg iterative cloud retrieval utilities (HICRU) and its application to GOME data | |
| Wolfe et al. | Hyperspectral analytics in ENVI: target detection and spectral mapping methods | |
| Jusoff et al. | Mapping of individual oil palm trees using airborne hyperspectral sensing: an overview | |
| Acito et al. | Atmospheric column water vapor retrieval from hyperspectral VNIR data based on low-rank subspace projection | |
| Hu et al. | Comparison of absolute and relative radiometric normalization use Landsat time series images | |
| Ientilucci et al. | Target detection in a structured background environment using an infeasibility metric in an invariant space | |
| Borde et al. | Extension of the DDV concept to retrieve aerosol properties over land from the Modular Optoelectronic Scanner (MOS) sensor | |
| Scott et al. | A preliminary evaluation of the impact of assimilating AVHRR data on sea ice concentration analyses |