A Two-Stage Method for Ship Detection Using PolSAR Image

Abstract

Ship detection using polarimetric SAR (PolSAR) images has recently been an active topic in the Earth observation field. There, how to detect small ships is an open and challenging issue. Within this context, we put forward a two-stage ship detection model, by which a novel ship detection method is proposed as well. Briefly, in the first stage, a suppression manipulation is adopted to suppress sea clutter, where the feature SVVS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>O</i></sub> is built on the intensity information with the orientation angle compensation (OAC). In the second stage, an enhancement manipulation is further executed to highlight ships from the suppressed sea clutter, where the features PID (polarimetric intensity difference) and NsD (nonsurface degree) are first constructed with SVVS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>O</i></sub> and a series of theoretical derivations. Then, via fusing PID and NsD together, the two-stage-based method FPAN is proposed to detect ships. To demonstrate its performance, we apply FPAN to four different L-Band PolSAR datasets. Experimental results reveal that, compared to other state-of-the-art methods, especially the DBSP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>CP</i></sub> method, FPAN is more effective in detecting small ships. On average, its figure-of-merit (FoM) and target-to-clutter ratio (TCR) values are, respectively 9.40% and 25.18% greater than those of DBSP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>CP</i></sub> , while the time consumption is just 58.67% of the latter.