SAR-PC: Edge Detection in SAR Images via an Advanced Phase Congruency Model

Edge detection in Synthetic Aperture Radar (SAR) images has been a challenging task due to the speckle noise. Ratio-based edge detectors are robust operators for SAR images that provide constant false alarm rates, but they are only optimal for step edges. Edge detectors developed by the phase congru...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2017-03, Vol.9 (3), p.209
Main Authors: Xiang, Yuming, Wang, Feng, Wan, Ling, You, Hongjian
Format: Article
Language:English
Subjects:
Convolution
Detectors
Edge detection
False alarms
Filters
Image filters
local energy
Noise
Noise levels
phase congruency
Quadratures
Radar detection
Radar imaging
ratio-based edge detectors
Remote sensing
Robustness
SAR
Sensors
Synthetic aperture radar
Visual effects
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Summary:Edge detection in Synthetic Aperture Radar (SAR) images has been a challenging task due to the speckle noise. Ratio-based edge detectors are robust operators for SAR images that provide constant false alarm rates, but they are only optimal for step edges. Edge detectors developed by the phase congruency model provide the identification of different types of edge features, but they suffer from speckle noise. By combining the advantages of the two edge detectors, we propose a SAR phase congruency detector (SAR-PC). Firstly, an improved local energy model for SAR images is obtained by replacing the convolution of raw image and the quadrature filters by the ratio responses. Secondly, a new noise level is estimated for the multiplicative noise. Substituting the SAR local energy and the new noise level into the phase congruency model, SAR-PC is derived. Edge response corresponds to the max moment of SAR-PC. We compare the proposed detector with the ratio-based edge detectors and the phase congruency edge detectors. Receiver Operating Characteristic (ROC) curves and visual effects are used to evaluate the performance. Experimental results of simulated images and real-world images show that the proposed edge detector is robust to speckle noise and it provides a consecutive edge response.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs9030209