期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：3
页码：237-246
DOI：10.14257/ijsip.2014.7.3.19
出版社：SERSC
摘要：Ship detection is an important application of optical remote sensing image processing. Sea-land segmentation is the key step in ship detection. Traditional sea-land segment methods only based on the gray-level information of an image to choose a gray threshold to segment the image; however, it is very difficult to establish a self-adapting mechanism to select a suitable threshold for different images. Thus, the segmentation result is greatly influenced by the threshold chosen for sea-land segmentation. In this paper, we are integrating the LBP feature information to propose a novel sea-land segmentation algorithm. Moreover, a new ship detection method based on our sea-land segmentation algorithm is proposed for optical remote sensing images. The performance of ship detection is measured in terms of precision and false-alarm-rate. Experimental results show that, as compared to minimum error meth- od, the proposed algorithm can decrease the false-alarm-rate from 23.2% to 9.24%. And compared to Otsu method, the proposed algorithm improve the precision from 82.9% to 90.2%.
