A speed-up seed point otsu method for ship detection in various scenarios

The technology of specific target detection and recognition in Synthetic Aperture Radar (SAR) image is one of the most important issues especially in the area of remote sensing observation. Aiming at ship detection in complex scenario, this paper presents a universal framework and a novel method called Speed-up Seed point OTSU (SSOTSU) based on OTSU and invoked in the framework. Different from the classic OTSU method, SSOTSU obtains seed points and compute threshold in specific area around every seed point. The experiment results demonstrate that our method can be implemented to detect ships under complicated scenario of both SAR images and optical images fast and obtain high accuracy in detection.

[1]  Andrew K. C. Wong,et al.  A new method for gray-level picture thresholding using the entropy of the histogram , 1985, Comput. Vis. Graph. Image Process..

[2]  B. Eswar Reddy,et al.  Ship Detection from SAR and SO Images , 2013 .

[3]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[4]  Carlos López-Martínez,et al.  A novel algorithm for ship detection in SAR imagery based on the wavelet transform , 2005, IEEE Geoscience and Remote Sensing Letters.

[5]  Huanxin Zou,et al.  High resolution SAR imagery ship detection based on EXS-C-CFAR in Alpha-stable clutters , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[6]  P. Maragos.  3.3 – Morphological Filtering for Image Enhancement and Feature Detection , 2004 .

[7]  D. Crisp,et al.  The State-of-the-Art in Ship Detection in Synthetic Aperture Radar Imagery , 2004 .

[8]  Yanming Yang,et al.  Automatic ship detection from SAR images , 2011, Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services.

[9]  Zhang Xuelan,et al.  Study Evolution of Ship Target Detection and Recognition in SAR Imagery , 2009 .

[10]  Yu Jiming,et al.  SAR Target Recognition with Data Fusion , 2010, 2010 WASE International Conference on Information Engineering.