To monitor urban areas using a synthetic aperture radar (SAR) sensor, we propose a symmetric analysis-based building signature extraction method. Instead of using separated algorithms, a unified framework is proposed to extract both layover and shadow areas. Since these two primitives usually exhibit long strip patterns in very-high-resolution SAR images, symmetry axes are first delineated. After that, local features are extracted from both symmetry and range direction to better distinguish different primitives. Then, these local radiometric features are used to identify different categories (layover, shadow, and background) via an efficient multiclass logistic regression classifier. To discriminate individual primitives, geometric information is adopted via an improved Ramer Douglas Peucker algorithm, which also simplifies the parameters for describing these primitives. To further enhance accuracy, combinatory analysis is implemented to exclude some false detections, and then shadow areas are extended via a local region growing method. The proposed approach is tested on a 0.75-m resolution airborne C band SAR image. The experiments are carried out under both small- and large-scale scenes, and the comparative results show our method has some advantages in low-contrast target detection and false-alarm elimination.
KEYWORDS: Image processing, Synthetic aperture radar, Image segmentation, Image compression, Real time imaging, Signal processing, Digital signal processing, Electronics, Parallel computing, Doppler effect
Real-time imaging processor can provide Synthetic Aperture Radar (SAR) image in real-time mode, which is necessary for airborne SAR applications such as real-time monitoring and battle reconnaissance. This paper describes the development of high-resolution real-time imaging processor in Institute of Electronic, Chinese Academy of Sciences (IECAS). The processor uses parallel multiple channels to implement large-volume calculation needed for SAR real-time imaging. A sub-aperture method is utilized to divide azimuth Doppler spectrum into two parts, which correspond two looks. With sub-aperture method, high processing efficiency, less range migration effect and reduced memory volume can be achieved. The imaging swath is also divided into two segments, which are processed in a parallel way. Range-Doppler algorithm, which consists of range migration correction and azimuth compression, is implemented in the processor. Elaborate software programming ensures a high efficient utilization of hardware. Experimental simulation and field flight indicate this system is successful. The principles, architecture, hardware implementation of the processor are presented in this paper in details.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.