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Overview

Area of application

Process flowsheets

Geo processor

Interferometric processor

Stereo processor

Image processing tools

Oil slicks detection processor

Ship detection processor

Sea waves analysis software tool

Polarimetric processor

Coherent change detection

Coherent co-registration

Quality estimation software tools

Detailed specifications

Examples

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Oil slicks detection processor

Oil slicks detection processor is intended for oil slicks detection against a background of homogeneous sea surface.

Input data are the radar images from spaceborne synthetic aperture presented in some extern data format (CEOS, XML and so on).

The result of the processing is raster binary image with detected slicks (mask) and set of the slicks parameters (square, geographic position). Result of the processing may be exported to some extern data format (for example, to graphic format Geo Tiff), which allows to save georeference data for output image.

Approaches and processing technologies which are realized in Oil slicks detection processor allows user to get result automatically. But in the case of complicated scenes user has possibility to take part in processing via adjustment of some processing parameters. Quality of the result may be increased by means of parameters variation.

Processing flow embodied into Processor concludes a few steps: selection of interested area from whole input scene, semiautomatic image searching and segmentation, detection of slicks via classification procedure, filtering of retrieved objects, calculating of output statistics on defined slicks. The flow chain settings of processor could be saved as the project form for possible subsequent application.

Initial data
The initial data for the processor is a SAR image, presented in the some extern format (CEOS, XML).

Processing flow

The user interface is designed according to the processing flow:

 Subset of interested region;

 Adaptive thresholding;

 Iterative classification;

 Iterative filtration.

Basic operations of the Oil slick detection Processor work flow diagram

Import and auxiliary data handling

 Reading of SAR data file.

 Reading of data files in extern format (CEOS, XML).

 Generation of parameter’s set needed for processing.

Georeferencing (for slant range data only)

 Transformation from slant range to ground range.

 Re-sampling to grid with same X and Y axises.

Pre-processing

 Subset of interested areas.

Adaptive thresholding

 Image statistics calculation.

 Threshold file creation.

 Thresholding.

Iterative classification

 Perspective pixels array creation.

 Energy function optimization and binar image transformation.

 Statistical models parameters calculation.

Iterative filtration

 Iterative filtration Binar image geometry analysis.

 Binar image filtration.

Binar raster image
   
Slick statistics calculation

 Slicks total square calculation.

An aim of adaptive thresholding is to get an initial classification. This initial classification is realizing by thresholding. The threshold value is calculated locally for each pixel of the input image and it depends on the statistical characteristics of the image inside some neibourhood of the pixel.

Iterative classification works in the feature space and with the input image simultaneously. This approach allows to get spatially coherent result of classification. Classification problem is vital for the optimization energy function problem.

An aim of the iterative filtration stage is to delete small pixel’s groups, which are gather rounded by contrary class pixels.

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Last modified: 12.11.2018© Racurs, 2004-2018