“ Synthesis of Multispectral Images to High ..
1 August 1994 Synthesis of imagery with high spatial and spectral resolution from multiple image sources
Conference Detail for Metamaterials - SPIE
In general, there are dozens of bands to a few ones in the wavelength range from visible to near infrared spectrum, and the spectral resolution of multispectral is 0.1λ, such as multispectral images produced PLEIADES satellite, IKONOS satellite, and QuickBird satellite. They can obtain abundant spatial and spectral information of measured objects simultaneously. Multispectral imaging technique has been widely applied in many fields, like science research, airborne and airspace remote sensing, medical devices, environment monitoring, geological survey, agricultural monitoring, military applications, and so on [, ]. Another efficient method for collecting images of an object in a series of spectral windows is hyperspectral imaging. Hyperspectral images have narrower but more number of bands. Typical applications of hyperspectral imaging approach also appeared on science research, airborne and airspace remote sensing, and military reconnaissance [, ]. In general, hyperspectral images consist of more finely divided spectral channels than multispectral images. However, hyperspectral images have lower spatial resolution than multispectral images. Multispectral images can sometimes refer to a set of images taken at vastly different parts of the electromagnetic spectrum. In this paper, we mainly research how to compress multispectral images using an algorithm having low complexity, high robust, and high performance according to characteristics of multispectral images.
The synthesis of low-resolution panchromatic (Pan) image is a critical step of ratio enhancement (RE) and component substitution (CS) pansharpening methods. The two types of methods assume a linear relation between Pan and multispectral (MS) images. However, due to the nonlinear spectral response of satellite sensors, the qualified low-resolution Pan image cannot be well approximated by a weighted summation of MS bands.
ICCV 2009 papers on the web - Papers
Image Fusion Utility: Image fusion is the process of combining High spatial resolution panchromatic data with Low spatial resolution multispectral data to get High spatial and spectral resolution fused output. For improving the spatial resolution with improved spectral resolution several fusion methods are being used based on the requirements from the user. The widely used Fusion methods like Brovey, IHS and Synthetic Variable Ratio (SVR), High pass Filtering (HPF), YIQ fusion methods are provided as fusion techniques in this utility. The tool is platform independent and implemented using JAVA and GDAL libraries to support various file formats. (1) (2)
SWIR Band synthesis utility for IRS Resourcesat-2 LISS-4 Mx Data: SWIR band finds its uses in many applications (snow and cloud detection etc.), Resourcesat Series satellites carry LISS-4 sensor which provides data at a spatial resolution of 5.8m in 4, 3, 2 bands. The SWIR band of in LISS-4 is synthesized using the spatial and spectral knowledge from LISS-3. This module generates synthesized SWIR band at a spatial resolution of LISS-4, by taking the inputs as LISS-3 (Layer stacked as B234), LISS-4 (Layer stacked as B2345) images along with their Meta files. The module accepts inputs in Geo-Tiff format and provides output in Geo-Tiff format. The S/W module has been developed using the coefficients derived from spectral transformation method to establish a relationship between B234 and B345 of LISS-3 image and applying these coefficients on B234 of LISS-4 Image to derive synthesized SWIR band. (1) (2)
AMITY SCHOOL OF ENGINEERING AND TECHNOLOGY
Accurate interpretation of high spatial resolution multispectral (MS) imagery relies on the extraction and fusion of information obtained from both spectral and spatial domains. Feature extraction from one or several fixed windows uses inaccurate description of pixel contexts and produces blurred object boundaries and low classification accuracy. In order to accurately characterize the spatial context properties of pixels, this paper presents a hierarchical-segmentation-based classification system. The system consists of two main modules: 1) hierarchical segmentation and 2) context-based classification.
Therefore, in some local areas, significant gray value difference exists between a synthetic Pan image and a high-resolution Pan image. To tackle this problem, the pixels of Pan and MSimages are divided into several classes by k-means algorithm, and then multiple regression is used to calculate summation weights on each group of pixels. Experimental results demonstrate that the proposed technique can provide significant improvements on reducing color distortion.
Ted Scambos | National Snow and Ice Data Center
Skeptic Papers 2016 (1) - P Gosselin
This paper presents a solution to the problem of enhancing the spatial resolution of multispectral images with ..
Pyramid-based image empirical mode decomposition …
Ieee Tgrs 2011 | Image Resolution | Remote Sensing
“PAN-sharpening of very high resolution multispectral images using ..
ARISTOTELES Applications and Research Involving Space Technologies Observing the Earth's Field from a Low Earth Orbiting SatelliteARL Air Resources Laboratory, Silver Spring, Maryland ()ARL Australian Radiation Laboratory (Melbourne, Victoria) Atmospheric Radiation Measurement ( program)ARMA Autoregressive moving-averageARMSAT Atmospheric Radiation Measurement SatelliteARPA Advanced Research Project AgencyARRCC Analysis of Rapid and Recent Climate Change (project)ARS Agricultural Research Service ()ARSMC Regional Specialized Meteorological CentreART Arctica ()ARTEMIS Advanced Relay and Technology Mission Satellite ()ARTEP Ariane Technology Experiment Platform (European)ARW Advanced Research WorkshopAS Anti-Spoofing on TransmissionsAS Area of SavannaASA American Statistical AssociationASA Antarctic Support AssociationASA Atmosphere Spectroscopy ApplicationsASB Area of Savanna Burned annuallyASAP Automated Shipboard Aerological ProgrammeASAR Advanced Synthetic Aperture RadarASAS Advanced Solid State Array SensorASASP Active Scattering Aerosol Spectrometer ProbeASB Association of Southeastern BiologistsASCAT advanced scatterometerASCATT advanced scatterometerASCE American Society of Civil EngineersASCEND Agenda of Science for Environment and Development into the 21st CenturyASChE American Society of Chemical EngineersASCII American Standard Code for Information InterchangeASCOT Atmospheric Studies in Complex Terrain (program)ASCS Agricultural Stabilization and Conservation ServiceASDAR Aircraft-to-Satellite Data RelayASE Air Sea ExperimentASEAMS Association of Southeast Asian Marine Scientists Association of Southeast Asian NationsASF Alaska FacilityASF Atmospheric Stablization FrameworkASHOE Airborne Southern Hemisphere Ozone ExperimentASI Agenzia Spaziale Italiana (Italian Space Agency)ASK Assisted Search for KnowledgeASL above sea levelASL atmospheric surface layerASLO American Society of Limnology and OceanographyASM Applied Simulation and Modelling ()ASME American Society of Mechanical EngineersASOEN Senior Officials on the EnvironmentASOS Automated Surface Observing SystemASPP American Society of Plant PhysiologistsASPRS American Society for Photogrammetry and Remote SensingASR aerosol solar radiationASSAS Advanced Solid State Array SensorASTER Advanced Spaceborne Thermal Emission and Reflection (radiometer) Atmosphere-Surface Turbulent Exchange Research (formerly )ASTEX Atlantic Stratocumulus Transition ExperimentASTM American Society for Testing and Materials (Philadelphia, Pennsylvania)ASU Air Separation UnitATES Alcatel Espace Systems Atmospheric Turbulence and Diffusion Division (formerly ) () Atmospheric Turbulence and Diffusion Laboratory (now )ATF atmospheric transmission factorAtlantis Research vessel ()ATLAS Atmospheric Laboratory for Applications and ScienceATLAS Airborne Turnable Laser Absorption SpectrometerATLID atmospheric lidar atmosphereATM Atmospheric Transport ModelATMOS Atmospheric Trace Molecules Observed by SpectroscopyATOVS Advanced ATP adenosine triphosphateATPEX Tropical Pacific ExperimentATS Advanced Technology SatelliteATS Antarctic Treaty SystemATS applications technology satelliteATS Advanced Turbine SystemsATSR along-track scanning radiometerAURIO Auroral Imaging ObservatoryAV acoustic velocity (geophysical logging)AVCS Advanced Vidicon Camera SystemAVD acoustic variable density (geophysical logging) advanced very high resolution radiometer ()AVHRR GAC Global Area CoverageAVHRR LAC Local Area CoverageAVIRIS airborne visible and infrared imaging spectrometerAVISCO French group for Analysis, Validation, and Investigation of Satellite OceanographyAVNIR advanced visible and near-infrared radiometeravtur aviation gas turbine fuelAWDB Adirondack Watershed Data BaseAWIPS-90 Advanced Weather Interactive Processing System for the 90sAWRA American Water Resources AssociationAWIS Association for Women in ScienceAWWA American Water Works Association (Denver)AXCTD autonomous expendable profiler
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In this paper, we propose an effective multispectral image compression method based on DSC combined with CCSDS-IDC by deep coupling way. The proposed algorithm has low complexity, high robust, and good performance, which is well suitable to application requirements of the new generation of high-resolution multispectral camera with wide field.
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