asprs digital imagery guideline update fall 2007
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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ASPRS Digital Imagery Guideline Update
Fall 2007
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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
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Background
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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
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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 at http://www.asd/image_gallery/default.htm
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Image chips are produced from features from Emerge imagery of Lakeland, Florida
Image Gallery
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Image Gallery Generation
• High spatial resolution imagery is systematically modified to produce a variety of image chips with varying image quality
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Example Simulated Image Chips
Original 8 “ GSD 16 “ GSD
24 “ GSD 32 “ GSD
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Imagery Requirement Generation Process
Market Segment
Data Selection
Intrinsic Verification &
ValidationSpatial
Resolution, SNR, etc.
Simulated Imagery
Varying Spatial Resolution
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Imagery Spatial ResolutionVerification and Validation
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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
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Edge Response
Point Spread Function
x *
Edge
Edge Response
Slope ~ 1/x
SpatialDomain
Steepness of edge response effects spatial resolution
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Relative Edge Response
-2.5 -2.0 -1.5 -1.0 -0.5 0 0.5 1.0 1.5 2.0 2.5-0.2
0
0.2
0.4
0.6
0.8
1
1.2RingingOvershoot
RingingUndershoot
Region where mean slope is estimated
Ed
ge
Res
po
nse
Pixels
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GSD 8 inch RER ~0.7 GSD 8 inch RER ~0.35
GSD 8 inch RER ~0.23 GSD 8 inch RER ~ 0.17
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GSD 8 inch RER ~0.7
GSD 32 inch RER ~1.0
GSD 16 inch RER ~1.0
GSD 24 inch RER ~1.0
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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
These types of targets will not be available in the imagery to validate spatial resolution
QuickBird Imagery Panchromatic ImageryFeb 17 2002
10 m
10 m
20 m
20 m
3.7 deg
QuickBird Imagery Panchromatic ImageryNov 14 2002
Concrete Edge
Tarp Edge
Concrete Edge
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Urban Target Edge Response Determination
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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
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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
Edge found with Sobel methodSimulated image with noise
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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
Building Shadows
RooflinesStreet center lines (pulse targets)
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Example Smoothed Edge Response
A
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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
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Points of Contact
• Bob Ryan Stennis 228-688-1868/ [email protected]• George Lee USGS 650-329-4255/ [email protected]