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ASPRS Digital Imagery Guideline Update Fall 2007

ASPRS Digital Imagery Guideline Update Fall 2007. Status. ASPRS Digital Imagery Guideline is being updated with new image chips NASA SSC contractor funded through DHS University of Mississippi led grant for Hurricane Decision Support Tool Development

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ASPRS Digital Imagery Guideline Update Fall 2007

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  1. ASPRS Digital Imagery Guideline UpdateFall 2007

  2. Status • ASPRS Digital Imagery Guideline is being updated with new image chips • NASA SSC contractor funded through DHS University of Mississippi led grant for Hurricane Decision Support Tool Development • Building off ASPRS Digital Imagery Guideline concept to develop a process for defining and developing products • Web Based Decision Support Tool that generates prototype specification • Uses image chips to help select product resolution and type • Developing automated spatial resolution assessment • Coordinating with USGS and others • Looking for high resolution Digital Imagery Donation • 2-30 cm GSD • Pan, RGB, CIR • Planning to present results at Spring ASPRS meeting

  3. Background

  4. Digital Imagery Guidelines Goals • Build Imagery Markets By: • Facilitating user purchasing • Improving communication between user/supplier • Promoting standards to improve market education level • Facilitating QA/QC Processes • Promote Market-Driven Technology Innovation By: • Improving communication with supplier/manufacturer with common dialog • Bringing critical technical issues to surface

  5. Digital Imagery Request Form • Type (Panchromatic, CIR, Color) • GSD or Scale • Geolocation Accuracy • Collection Area • Collection Constraints • Post Processing Requirements • Delivery Format (datum, compression, tiling) Request begins online athttp://www.asd/image_gallery/default.htm

  6. Image Gallery Image chips are produced from features from Emerge imagery of Lakeland, Florida

  7. Image Gallery Generation • High spatial resolution imagery is systematically modified to produce a variety of image chips with varying image quality

  8. Example Simulated Image Chips 16 “ GSD Original 8 “ GSD 32 “ GSD 24 “ GSD

  9. Imagery Requirement Generation Process Intrinsic Verification & Validation Spatial Resolution, SNR, etc. Simulated Imagery Varying Spatial Resolution Data Selection Market Segment

  10. Imagery Spatial ResolutionVerification and Validation

  11. Spatial Resolution • Most spatial resolution specifications are written in terms of MTF as a function of spatial frequency • Dominant parameter is typically MTF @ Nyquist frequency • Nyquist frequency depends on GSD • Nyquist frequency = 1/(2*GSD) • MTF at Nyquist is a measure of aliasing • MTF measurements at Nyquist are difficult to estimate in-flight • Edge Response is more intuitive • RER (Relative Edge Response) • Ringing

  12. Point Spread Function Edge Spatial Domain * x Edge Response Slope ~ 1/x Steepness of edge response effects spatial resolution Edge Response

  13. 1.2 Ringing Overshoot 1 0.8 Region where mean slope is estimated Edge Response 0.6 0.4 0.2 0 Ringing Undershoot -0.2 -2.5 -2.0 -1.5 -1.0 -0.5 0 0.5 1.0 1.5 2.0 2.5 Pixels Relative Edge Response

  14. GSD 8 inch RER ~0.35 GSD 8 inch RER ~0.7 GSD 8 inch RER ~0.23 GSD 8 inch RER ~ 0.17

  15. GSD 16 inch RER ~1.0 GSD 8 inch RER ~0.7 GSD 24 inch RER ~1.0 GSD 32 inch RER ~1.0

  16. 3.7 deg 20 m 10 m 10 m 20 m Standard Method Spatial Resolution Method • Verification and validation of spatial resolution is typically performed using specially designed edge targets • Deployable: Radiometric tarp edges • Permanent: Painted conrete edge targets QuickBird Imagery Panchromatic Imagery Feb 17 2002 Tarp Edge Concrete Edge Concrete Edge QuickBird Imagery Panchromatic Imagery Nov 14 2002 These types of targets will not be available in the imagery to validate spatial resolution

  17. Urban Target Edge Response Determination

  18. Vicarious Spatial Resolution Estimation • MTF edge response estimation without dedicated targets • Exploit features in nominal imagery • Developing automated process • Edge identification • Edge spread function construction • MTF calculation • Required to properly generate array of products

  19. Vicarious Edge Response • Matlab code being developed for automated edge detection and analysis algorithms using scene data Data points across the edge to estimate edge response Simulated image with noise Edge found with Sobel method

  20. Vicarious Edge Targets Examples • Natural edge targets from within the imagery will be used for the spatial resolution analysis • Examples of probable edge targets that will be detectable using automated methods are shown below Rooflines Street center lines (pulse targets) Building Shadows

  21. A s Example Smoothed Edge Response

  22. Next Steps/Summary • Acquire high resolution imagery out of archives • Automated spatial resolution assessment and image generation • New tool for quickly estimating spatial resolution and producing image chips • Release next generation ASPRS Digital Imagery Guideline in Spring

  23. Points of Contact • Bob Ryan Stennis 228-688-1868/ reryan@nasa.gov • George Lee USGS 650-329-4255/ gylee@usgs.gov

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