MATEC Web of Conferences
Volume 31, 20152015 7th International Conference on Mechanical and Electronics Engineering (ICMEE 2015)
|Number of page(s)||5|
|Section||Image processing and application|
|Published online||23 November 2015|
An Improved GLRT Method for Target Detection in SAR Imagery
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106 Jiangsu, China
a Corresponding author: firstname.lastname@example.org
Automatic ground vehicle detection based on SAR imagery is one of the important military applications of SAR. A region-based generalized likelihood ratio test (GLRT) method is proposed in this paper, and this method combines the GLRT detection theory and image segmentation technology. First, the SAR imagery is roughly segmented as land clutter region and potential target region through the split and merge procedure often used for processing the original images. Then, based on the segmentation results, the reasonable statistical models for the data in the two regions are built respectively. Finally, with the knowledge of statistical characteristics of clutter and target, GLRT detection method is applied to the each pixel in the potential target region to obtain more accurate detection results. Experimental results based on real SAR data show that the proposed method can effectively detect the ground vehicle targets from the land clutter with excellent accuracy and speed.
Key words: SAR Imagery / Target Detection / Image Segmentation / Statistical Model / GLRT
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.