General adaptive-neighborhood technique for improving synthetic aperture radar interferometric coherence estimation

Area of Science:

• Geosciences
• Remote Sensing
• Signal Processing

Background:

• Coherence maps are crucial for analyzing interferometric synthetic aperture radar (InSAR) data.
• Existing filtering methods, like fixed multilook and Lee adaptive filters, have limitations in preserving coherence details.

Purpose of the Study:

• To introduce a new adaptive filtering method for InSAR coherence maps.
• To improve the accuracy and detail preservation of coherence estimation in InSAR data.
• To extend the method for polarimetric interferometric SAR (PolInSAR) data.

Main Methods:

• An adaptive neighborhood is defined for each pixel using region-growing based on amplitude image information.
• Complex averaging within the adaptive neighborhood, after phase compensation, filters the coherence value.
• The algorithm is extended to handle polarimetric interferometric SAR data.

Main Results:

• The proposed method was tested on European Remote Sensing (ERS) and airborne high-resolution PolInSAR data.
• Subjective and objective analyses, including coherence edge detection, demonstrated superior performance.
• The new filter outperformed standard phase-compensated fixed multilook and Lee adaptive filters.

Conclusions:

• The developed adaptive filtering technique offers significant improvements over existing methods for InSAR coherence map processing.
• The method effectively preserves coherence details and enhances edge detection.
• The extension to polarimetric data broadens its applicability in advanced SAR interferometry.