Liu et al., 2009 - Google Patents
Simulation of EO-1 hyperion data from ALI multispectral data based on the spectral reconstruction approachLiu et al., 2009
View HTML- Document ID
- 8787034004462490931
- Author
- Liu B
- Zhang L
- Zhang X
- Zhang B
- Tong Q
- Publication year
- Publication venue
- Sensors
External Links
Snippet
Data simulation is widely used in remote sensing to produce imagery for a new sensor in the design stage, for scale issues of some special applications, or for testing of novel algorithms. Hyperspectral data could provide more abundant information than traditional multispectral …
- 230000003595 spectral 0 title abstract description 60
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
- 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
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- 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
- 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
- G06T11/00—2D [Two Dimensional] image generation
-
- 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
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yue et al. | Estimation of winter wheat above-ground biomass using unmanned aerial vehicle-based snapshot hyperspectral sensor and crop height improved models | |
Yokoya et al. | Potential of resolution-enhanced hyperspectral data for mineral mapping using simulated EnMAP and Sentinel-2 images | |
Zhu et al. | Integration of GF2 optical, GF3 SAR, and UAV data for estimating aboveground biomass of China’s largest artificially planted mangroves | |
She et al. | Comparison of the continuity of vegetation indices derived from Landsat 8 OLI and Landsat 7 ETM+ data among different vegetation types | |
Agapiou et al. | Evaluating the potentials of Sentinel-2 for archaeological perspective | |
Garzelli et al. | Multispectral pansharpening with radiative transfer-based detail-injection modeling for preserving changes in vegetation cover | |
Franch et al. | A method for Landsat and Sentinel 2 (HLS) BRDF normalization | |
Jia et al. | A kernel-driven BRDF approach to correct airborne hyperspectral imagery over forested areas with rugged topography | |
Banskota et al. | Investigating the utility of wavelet transforms for inverting a 3-D radiative transfer model using hyperspectral data to retrieve forest LAI | |
Liu et al. | Simulation of EO-1 hyperion data from ALI multispectral data based on the spectral reconstruction approach | |
Gao et al. | Removal of thin cirrus scattering effects in Landsat 8 OLI images using the cirrus detecting channel | |
Ji et al. | Comparison of different multispectral sensors for photosynthetic and non-photosynthetic vegetation-fraction retrieval | |
Grochala et al. | A method of panchromatic image modification for satellite imagery data fusion | |
Csillik et al. | Challenges in estimating tropical forest canopy height from planet dove imagery | |
Liang et al. | Estimating crop LAI using spectral feature extraction and the hybrid inversion method | |
Zhang et al. | Computationally inexpensive Landsat 8 operational land imager (OLI) pansharpening | |
Cui et al. | Combining Linear pixel unmixing and STARFM for spatiotemporal fusion of Gaofen-1 wide field of view imagery and MODIS imagery | |
Liu et al. | Multisource remote sensing imagery fusion scheme based on bidimensional empirical mode decomposition (BEMD) and its application to the extraction of bamboo forest | |
Wang et al. | A relative radiometric calibration method based on the histogram of side-slither data for high-resolution optical satellite imagery | |
Michel et al. | Sen2venµs, a dataset for the training of sentinel-2 super-resolution algorithms | |
Wolters et al. | iCOR Atmospheric correction on Sentinel-3/OLCI over land: intercomparison with AERONET, RadCalNet, and SYN Level-2 | |
Bachmann et al. | Estimating the influence of spectral and radiometric calibration uncertainties on EnMAP data products—Examples for ground reflectance retrieval and vegetation indices | |
Hu et al. | Spatial resolution enhancement of satellite microwave radiometer data with deep residual convolutional neural network | |
Li et al. | Hyperspectral unmixing with bandwise generalized bilinear model | |
Kim et al. | A validation experiment of the reflectance products of KOMPSAT-3A based on RadCalNet data and its applicability to vegetation indexing |