Title :
Finding curves in SAR CCD images
Author :
Cha, Miriam ; Phillips, Rhonda ; Yee, Michael
Author_Institution :
MIT Lincoln Lab., Lexington, MA, USA
Abstract :
This paper introduces a pattern recognition and computer vision approach to mitigating false alarms in synthetic aperture radar (SAR) coherence change detection (CCD) images. In this paper, we perform an automatic detection of roads in SAR CCD images. The approach is based on a curve tracing algorithm originally proposed by Steger with modifications to better suit the goal of curve detection in SAR CCD images. In our technique, the traditional Steger´s method is used to detect curve points, and cubic splines are used to approximate the original curve. To detect roads more accurately, preprocessing and outlier removal techniques are performed along with the curve detection.
Keywords :
computer vision; image recognition; radar detection; radar imaging; splines (mathematics); synthetic aperture radar; SAR CCD images; Steger method; coherence change detection images; computer vision approach; cubic splines; curve point detection; curve tracing algorithm; pattern recognition; road automatic detection; synthetic aperture radar; Charge coupled devices; Coherence; Pixel; Roads; Spline; Synthetic aperture radar; CCD; SAR; change detection; curve detection; regression splines;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2011.5946909