Palette Sensor Performance Monitoring (SPM)

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