A Remote Sensing Ship Recognition Using Random Forest

In order to detect the marine targets reliably and timely, a novel ship recognition method by using optical remote sensing data based on random forest is presented. First, in the feature extraction part, in addition to the common features, we introduce the visual saliency features of the target.; second, an improved random forest based on mutual information (MIRF) is utilized to recognize ships in data from the optical remote sensing system; finally, we compare MIRF to classical algorithms. The MIRF has accelerated the operation speed of the algorithm and the classification accuracy remains robust. Theoretical analysis and experiment results show that the proposed method can achieve high recognition rate; therefore, this approach is feasible and efficient in the marine target recognition.