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Ship detection from high-resolution imagery based on land masking and cloud filtering

High resolution satellite images play an important role in target detection application presently. This article focuses on the ship target detection from the high resolution panchromatic images. Taking advantage of geographic information such as the coastline vector data provided by NOAA Medium Resolution Coastline program, the land region is masked which is a main noise source in ship detection process. After that, the algorithm tries to deal with the cloud noise which appears frequently in the ocean satellite images, which is another reason for false alarm. Based on the analysis of cloud noise's feature in frequency domain, we introduce a windowed noise filter to get rid of the cloud noise. With the help of morphological processing algorithms adapted to target detection, we are able to acquire ship targets in fine shapes. In addition, we display the extracted information such as length and width of ship targets in a user-friendly way i.e. a KML file interpreted by Google Earth.