Title :
Ship recognition in high resolution SAR imagery based on feature selection
Author :
Chen Wen-ting ; Ji Ke-feng ; Xing Xiang-wei ; Zou Huan-xin ; Sun Hao
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
Ship detection and recognition are crucial components of SAR ocean monitoring applications. In the literature, various features have been proposed for ship pattern analysis. However, operators often face the dilemma that they have little knowledge on feature selection. In this paper, we first propose a novel RCS density encoding feature for ship description. A novel two-stage feature selection approach is then presented. Finally, ship recognition experiment conducted with high resolution SAR imagery reveals a percent of correct classification as high as 91.54%.
Keywords :
image coding; image recognition; marine engineering; radar cross-sections; radar imaging; radar resolution; ships; SAR imagery; SAR ocean monitoring application; feature selection; radar cross section density encoding feature; ship description; ship detection; ship pattern analysis; ship recognition; Correlation; Image recognition; Marine vehicles; RCS density encoding; feature selection; high resolution SAR imagery; ship recognition;
Conference_Titel :
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4673-1272-1
DOI :
10.1109/CVRS.2012.6421279