Fusion of Spaceborne and Airborne SAR Images Using Saliency and Fuzzy Logic for Vessel Detection

Abstract

In the paper, we propose a new method based on multi-order superpixel-level saliency and fuzzy logic (MSSFL) to fuse spaceborne and airborne SAR images for vessel detection. First, we generate a new global regional contrast map (GRCM) by exploiting the multi-order superpixel-level saliency (MSS). In the generated GRCM, the vessel targets are well restored and the backgrounds are suppressed. Next, a new fuzzy logic approach is presented to fuse the MSS information provided by the GRCMs. This GRCM-based fuzzy fusion can further enhance the vessel target regions and filter out the inshore interference regions. Experimental results using Gaofen-3 satellite and unmanned aerial vehicle (UAV) SAR images show that the proposed MSSFL method yields higher target-to-cluster ratio (TCR) of fused images and improved detection performance compared with the commonly utilized image fusion approaches.