1. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Sensor Modeling in DIRSIG June 10, 2004 Cindy Scigaj Dr. John Schott Scott BrownDr. Bob Kremens Dr.Carl Salvaggio Paul LeeJason Faulring Niek Sanders

2. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Overview What is DIRSIG?What is DIRSIG? Project definitionProject definition Background informationBackground information –MTF, Spectral Response (& spectral smile), Noise Lab experimentsLab experiments Field experimentsField experiments SummarySummary

3. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T DIRSIG Physics based model developed at RIT to simulated remotely sensed dataPhysics based model developed at RIT to simulated remotely sensed data Various platformsVarious platforms –Line scanner, framing array, pushbroom scanner DIRSIG Megascene Image

4. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Project Definition Historical perspective and justificationHistorical perspective and justification –Users wishing to incorporate rigorous sensor modeling to DIRSIG simulations needed to oversample the image spatially and spectrally. »Large intermediate images were required Project GoalsProject Goals –Add a flexible sensor model that allows users to incorporate sensor models during rendering. »Vary properties for each detector element (pixel) –Create and distribute pre-built sensor models for “out-of-the-box” use. »Potential systems: AVIRIS, WASP, HYDICE, SEBASS, COMPASS, NVIS »Allow users to compare results with these standardized models –Combine efforts to create sensor model “cook-book” –Benefit algorithm developers/testers and instrument designers »Long term – handle tabulated data –Overall – provide an easy way to incorporate sensor artifacts

5. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Implementation Overview Response functionResponse function –A set of one or more channel or band responses –Different types of channels »Pass-band channels have a tabulated spectral response. »Spectrometers channels have a center, width and shape. –Both have gain and bias terms per channel »“Dead” detectors introduced with zero gain values Spectral Response FunctionSpectral Response Function –Pushbroom spectrometer specific issues »“Smile” and “frown” effects can vary channel locations for each spatial detector. Point-Spread Function (MTF)Point-Spread Function (MTF) –A combination of atmosphere (turbulence), platform (jitter), optics, detector and electronics effects. –Ideally, a series of PSFs stored in a functional form to ease computation and allow for different sub-detector sampling schemes. NoiseNoise –A combination of photon arrival, detector read-out and electronics. –Store the noise covariance and use a Principle Component (PC) synthesis method to compute a unique noise spectrum for each scan/read-out of the detector elements.

6. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Pushbroom axis Spectral axis Area arrays Diffraction grating Collimator Slit Optics Ground Track Pushbroom Scanners AIS (grating)AIS (grating) HYDICE (prism)HYDICE (prism) SEBASS (prism)SEBASS (prism) Hyperion (EO-1)Hyperion (EO-1)

7. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Response Function: Spectral Smile and Frown In pushbroom spectrometers, the spectral channel locations of pixels on the edge of the focal plane are different than the ones in the center of the focal planeIn pushbroom spectrometers, the spectral channel locations of pixels on the edge of the focal plane are different than the ones in the center of the focal plane –This effect can be modeled with these enhancements. Center Pixel Edge Pixel Spatial Spectral

8. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Point-Spread Function A spectrally dependent function that introduces the blur from a variety of sources in the image formation process.A spectrally dependent function that introduces the blur from a variety of sources in the image formation process. –Atmospheric turbulence, platform jitter, optics, detector and electronics effects. –Ideally, each of these would be in a flexible, functional form. »Radially symmetric (Gaussian, Lorentzian, etc.) »X/Y separable (Gaussian, Sinc, Sinc 2, etc.) –A functional form could allow the user to change the sub-detector sampling (finer grid, N random locations, etc.) Pixel Detector PSF = PSF a (r,l) + PSF p (r) + PSF o (r) + PSF d (x,y) Cn2Cn2 jitter opticsdetector

9. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Noise: Spectral Structure We want to introduce noise for each detector element and each scanWe want to introduce noise for each detector element and each scan –Each detector can have unique noise statistics »Non-repeating noise that can be described by higher order statistics (spectral covariance/correlation) Due to focal plane design (shared electronics) the sensor noise is correlated.Due to focal plane design (shared electronics) the sensor noise is correlated. –This effect can be modeled with these enhancements. AVIRIS Noise Correlation12341 2 3 4

10. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Modeling Concept Focal Plane Many spectral samples To accurately model the radiance at this pixel detector:To accurately model the radiance at this pixel detector: –Spectrally oversample »Convolve to channel resolution using response. –Spatially oversample inside and outside the physical detector element »Convolve to detector resolution using PSF. –Add spectrally correlated noise »Pull from statistical noise model. Many spatial samples PSFContributionRegionProjectedDetectorExtent

11. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Data Flow Apply Response Apply PSF N Spatial Samples “Many” Spectral Samples Without Noise N Spatial Samples M Spectral Samples Without Noise 1 Spatial Sample M Spectral Samples Without Noise 1 Spatial Sample M Spectral Samples With Noise Apply Noise Channel Responses PSF (by channel) Noise

12. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Wildfire Airborne Sensor Program (WASP) System in development at RITSystem in development at RIT Four separate camera systemsFour separate camera systems –Terra Pix : 0.4-0.9 microns –SWIR: 0.9-1.8 microns –MWIR: 3.0-5.0 microns –LWIR: 8.0-9.2 microns CharacterizationCharacterization –equipment specifications –actual lab scenes and measurements –Bayer pattern artifacts WASP

13. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T WASP Modeling Criterion DIRSIG needs Terra Pix NIRMWIRLWIR Focal length 0.054966 m 0.025307 m 0.025014 m 0.025027 m # x pixels (Cross-track)4096640640640 # y pixels (Along-track)4096512512512 X length 0.000009 m 0.000025 m Y length 0.000009 m 0.000025 m Spectral response SpecsSpecsSpecsSpecs Gain & bias Color strips target CI blackbody PSF Plywood target CI blackbody W/ foil edge CI blackbody W/ foil edge Noise Color strips target CI blackbody

14. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Lab Experiments

15. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Field Experiments – 06/07/04 Data collected on sceneData collected on scene –GPS location –ASD radiance –ASD reflectance –D&P radiance –Temperature »Thermocouples »Exergen »Thermistors @ pier

16. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Summary Sensor modeling statusSensor modeling status –A survey of different sensors has been performed to gather information on popular imaging platforms. »This information will be used to construct distributed sensor models. »Recently became in contact with COMPASS instrument group Precal data and calibration documentationPrecal data and calibration documentation –Correlated noise has been demonstrated –Simple smile case has been demonstrated –Goal: supply significantly better default sensor models –These new features, user interfaces and pre-built sensor models will be in DIRSIG 4 Experiments statusExperiments status –WASP Lab data acquisition complete –Image analysis programs being developed »using ISO standard procedures –WASP imagery with supporting ground truth measurements have been acquired and need to be sorted, organized, and processed –Waiting for SEBASS and COMPASS data distribution ~ 30 days? »Pre-calibrated data as well

17. Digital Imaging and Remote Sensing Laboratory R.I.TR.I.TR.I.TR.I.T R.I.TR.I.TR.I.TR.I.T Contact info WASP – Terra Pix @ 3,000 ft Cindy Scigaj cls8343@cis.rit.edu