Fusion Detection of Closed Water in Medium-Low Resolution Remote Sensing Imagery

Yuanyong Ning, Yanan You, Jingyi Cao, Fang Liu, Qing Yan, Yue Zhang

Abstract: Aiming at the closed water detection in remote sensing imagery at medium-low resolution, this paper proposes a novel method for closed water detection based on fusion detection which conducts detection via informative fused images blended by Synthetic Aperture Radar (SAR) and optical images. Firstly, it utilizes SAR and optical image pairs containing the same closed water object to generate aligned image pairs according to latitude and longitude information. Next, generative adversarial network (GAN) is adopted to fuse two categories of images. At last, a target detection network driven by optical image samples is used to detect the closed water on the fused image. The experiment result on Sentinel-1&2 shows that the proposed method can effectively make up for the shortage of SAR image in closed water detection and improve the detection performance.