Region-based enhancement and analysis of SAR images

Segmentation plays a key role in many image processing applications, including SAR image analysis. Given a high quality segmentation, important tasks such as adaptive noise filtering and classification can be greatly simplified. However, the presence of a strong, multiplicative noise known as speckl...

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Bibliographic Details
Main Authors: Fjortoft, R., Marthon, P., Lopes, A., Sery, F., Ducrot-Gambart, D., Cubero-Castan, E.
Format: Conference Proceeding
Language:English
Subjects:
Filters
Image analysis
Image edge detection
Image segmentation
Infrared image sensors
Lubricating oils
Reflectivity
Remote monitoring
Speckle
Synthetic aperture radar
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Summary:Segmentation plays a key role in many image processing applications, including SAR image analysis. Given a high quality segmentation, important tasks such as adaptive noise filtering and classification can be greatly simplified. However, the presence of a strong, multiplicative noise known as speckle makes edge detection in SAR images very difficult. A new, hybrid segmentation technique has permitted us to obtain segmentations of relatively good quality prior to filtering. This has led us to develop a region-based version of the LMMSE speckle filter. The segmentations may further be used for the classification of raw or filtered images. In this paper we give an overview of the entire scheme, which segments, filters and classifies SAR images. The study is limited to agricultural scenes composed of distinct parcels of relatively homogeneous reflectivity.
DOI:10.1109/ICIP.1996.560916