palette sensor performance monitoring (spm)
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Palette /Sensor Performance Monitoring (SPM)
Bad Pixel Identification and MappingIdentifies bad pixels according to type of defect Saturated Non-Responsive Over-Responsive
Replaces bad pixels according to a user selected algorithm Nearest Neighbor Mean Minimum/Maximum
Palette is an integrated suite of tools for processing & exploiting data from all OPIR sensors. Palette is built on Opticks, an open-source remote sensing analysis tool for GEOINT, and ArcGIS for geospatial analysis. In addition to OPIR, Opticks also supports the processing and exploitation of Imagery, Hyper-Spectral, Multi-Spectral, Thermal Infra-Red (TIR), and Synthetic Aperture Radar (SAR) data. Operates in both connected mode (interfacing with IOTS services) and stand-alone mode
(read/write from file system) Provides event and scene-based processing capabilities DoDIIS Certified – Oct 2011 Deployed at more than 25 organizations world-wide,
including: NGA, NASIC, OPIR ground sites, ARSTRAT, NGIC, other intelligence agencies, multiple partner locations When coupled with ESD, OPIR users can search, download,
and process OPIR data and publish OPIR products Selected by NGA to provide OPIR scene based analysis for
the entire OPIR enterprise comprised of both GEOCOMPASS (GC) and IOTS. Palette will be integrated into GC during GC Increment 6
Temporal Mean Image of a Series of Point Source Frames
Palette Workbench with Raw and Drizzled Images Displayed
Measured EnsquaredEnergy Per-Frame for a
Point Source Image Sequence
Plot of Per-Frame Width vs. Height Full Width and Half Max
Measurements
3D Difference Surface Between the Fitted and Raw PSF Images
The Sensor Performance Monitoring (SPM) utility is a suite of tools integrated into Palette that perform a host of sensor characterization and calibration activities such as: Stellar Radiometric Calibration Point Spread Function (PSF) Determination Bad Pixel Identification and mapping Sensor Noise Analysis Sensor Configuration Analysis Simple Background Suppression Algorithms
Bias Frame Generation and ApplicationFacilitates creation of temporal bias frames Mean Median Minimum
Allows easy application (subtraction) of bias frames from input datasets Cleans up fixed pattern noise, sensor bias and stray light artifacts
Provides tools for viewing and inspecting bias frames
Sensor AnalysisTools are available to create: Temporal Standard Deviation Frames Flat field frames from two temperature black
body data Per-frame statistical plots to help spot trends Row and column line plots to visualize slices
through your data
Bias Frame Generation Per-frame Statistical Analysis Jitter Analysis High Resolution PSF Analysis using the
Drizzle Algorithm
Noisy User-Defined
Mean/Median Zero
Point Spread Function Analysis:Fits a Gaussian surface to each point sourceProvides Full width at half max measurements
Measures Ensquared energy and total counts
Creates high resolution PSF images by applying the Fruchter and Hook “Drizzle” algorithm. Facilitates extraction and analysis of stellar sources Identifies the star and locates associated spectraApplies sensor relative spectral response curves and
generates calibration factorsWorks on star fields to process multiple targets
simultaneously
3D Surface of the Gaussian Fit PSF Image
SPM PSF Drizzle Application Panel
High Resolution Image Created Using the Fruchter and Hook “Drizzle” Algorithm
SPM PSF Panel Showing Various PSF Processing Options
PSF Plot of Pixel Max Value Per-Frame
PSF Plot of Total Energy Per-Frame
Palette Workbench with a PSF Fitted Image, Difference Image, Energy
Mask and Drizzled Image Displayed
Palette Workbench Displaying the Cross-Section Plot of a Difference
Image
Palette Workbench with Per-Frame Statistical Results Plotted
SPM Bias Creation Panel Showing Available Algorithms
SPM Mask Creation Panel Showing Bad Pixel Identification Algorithms