integration of colorized single-pol sar data into optical image mosaics.ppt
TRANSCRIPT
Oliver LangParivash Lumsdon
Astrium GEO-Information Services
Integration of Colorized Single-Pol SAR Data Into Optical Image Mosaics
IGARSS 2011, Vancouver
IGARSS Vancouver – 27 July 20112
Motivation Thematic mapping in Cloud Belt using single-
pol SAR
Cost effective approach: single coverage, full resolution + swath width
Mosaic electro-optical image mosaics with seamless SAR mosaics, colorized in meaningful way
Commercial TerraSAR-X data distribution by Astrium: Colored quick looks come with TSX data since 2010
BUT: varying colors, not intuitive
Development of new add-on product: Color Composite
IGARSS Vancouver – 27 July 20113
Single-Pol SAR Colorization Known: Basic „classification“ based on
Speckle variations
Coeff. of Variation as measure for local speckle noise
Link to main surface types: Large CoV: heterogenious (urban) Small CoV: homogenious (water, grassland)
New: combination of multiple texture filters Colorization according to reference image
µσ /=CoVSTD
mean
S. Kuntz and F. Siegert, “Monitoring of deforestation and land use in Indonesia with multitemporal ERS data.” International Journal of Remote Sensing 20: 2835-2853, 1999
M. Thiel., T. Esch, and S. Dech, “Object-oriented detection of settlement areas from TerraSAR-X data” Proceedings of the EARSeL Joint Workshop: Remote Sensing: New Challenges of high resolution. (Eds.,Carsten Jürgens), 2008
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General Approach
Apply multiscale texture filters
Classification based on filter layers
Colorization of „classes“ with given LUTs
SAR-image
Speckle filter
SAR-Image SNR
Noise, Speckle and
Texture Estimation
ClassificationThresh-holds
HSV Image
HSV to RGBColorized
SAR-image
4 Color Tables
De-speckled
SAR-image
Optical reference
Color table derivation
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Generation of filter layers
Derivation of multi-scale texture components Mean Standard Deviation Variance Skewness Coeff of Variation
Spectral high-pass
Noise components:
Multiplicative Noise S: apply Gaussian filter Additive Noise N = apply directional Lee filtered
( ) ( ) ( )SNIR logloglog ++=
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Classification Hierarchical unsupervised
classification based on filter layers
Min-distance based on empirical thresholds
Backscatter & speckle characteristics allows reliable separaton of (calm) Water / Urban
Third class is separated into hetero- and honogenious sub-class (e.g. Forest / Grassland)
Decider: local Variance
Urban
Forest
Water
0 50 100 150 200 250
Histogram
value
mean
STD
IGARSS Vancouver – 27 July 20117
Selection of Colors
2 methods: Predefined standard color tables (optical) reference image
Manual or automatic selection of samples for each class
Derivation of Hue values from samples and quantization of colors to a desired number of colors 4 LUTs
HSV RGB Transformation
Example: selection of sample areasBackground image: Google Earth
mean
STD
huehueSaturationSaturation
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2 Examples
Overlay: Spot 4 and TerraSAR-X Stripmap
Overlay: TerraSAR-X Spotlight in Google Earth
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10 km
TerraSAR-X:Date: 29 Jul 2010 StripMap, 3 m res HH polarization
SPOT4: date: 8 Jan 201120 m resolution, Layers 4, 1, 2
Example: Cameroon
IGARSS Vancouver – 27 July 201110
Color tables derived from overlapping optical scene
Nr. of quantized colors: 16
TerraSAR-X:Date: 29 Jul 2010 StripMap, 3 m res HH polarization
SPOT4: date: 8 Jan 20120 m resolution, Layers 4, 1, 2
Example: Cameroon
Water Agriculture Forest Urban
10 km
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Example: Germany
Quantization: 256 colors / class
urbanforest
agriculture
water
Germany: TerraSAR-X HS
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Example: Germany
Background image: Google Earth
urbanforest
agriculture
water
Germany: TerraSAR-X HS
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Discussion Sensor and SAR-mode independent
qualitative approach
Supports thematic mapping as additional information layer, e.g. in cloud belt
Intuitive visualization and interactive interpretation
SAR specific backscatter characteristics remain
Inherently, differences regarding surface representation between optical and SAR remain
Further improvements expected by optimized classification procedure & automatic LUT derivation
0% 100%Clouds
IGARSS Vancouver – 27 July 201114
Thank You
Astana, KasachstanTerraSAR-X StripMap ColorSAR
IGARSS Vancouver – 27 July 201115
Contact
Dr. Oliver Lang
Senior Application Development Manager
Development & Engineering | Infoterra GmbH
GEO-Information Services
Astrium GmbH - ServicesClaude-Dornier-Str. | 88090 Immenstaad | GermanyTel +49 7545 8 5520 | Fax +49 7545 8 1337 | Mob +49 151 1822 [email protected] | www.infoterra.de