Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

Sensors (Basel)

School of Automation, Huazhong University of Science and Technology, Luoyu Road 1037, Hongshan District, Wuhan 430074, China.

Published: September 2015

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610472PMC
http://dx.doi.org/10.3390/s150923071DOI Listing

Publication Analysis

Top Keywords

saliency map
16
gradient textural
12
textural saliency
12
sar images
8
based gradient
8
apron area
8
candidate regions
8
aircraft detection
4
detection high-resolution
4
high-resolution sar
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!