A novel harbor detection method based on pattern coding algorithm

Harbor automatic detection is a scene interpretation in remote sensing image processing. Fast and accurate harbor detection can significantly improve the performance of inshore ship detection. In order to achieve harbor detection in complex remote sensing images, in this paper, a novel pattern coding algorithm is proposed. The proposed harbor detection method has three steps: First, the harbor water area is extracted by using the definition circle (DC) model. Secondly, pre-generated eight KEY patterns are multiplied with the local scenes, and the probability density function (PDF) of the multiplied local scene is recorded. Finally, the Euclidean distance between the eight patterns' PDFs and the original local scene's PDF is calculated, then compared with the threshold and coded, so as to realize the harbor area detection. Experimental results demonstrate that the novel method has outstanding performance on harbor area detection in complex broad width remote sensing images.