Abstract
In recent years, ship detection in satellite remote sensing images has become an important research topic. Most existing methods detect ships by using a rectangular bounding box but do not perform segmentation down to the pixel level. This paper proposes a ship detection and segmentation method based on an improved Mask R-CNN model. Our proposed method can accurately detect and segment ships at the pixel level. By adding a bottom-up structure to the FPN structure of Mask R-CNN, the path between the lower layers and the topmost layer is shortened, allowing the lower layer features to be more effectively utilized at the top layer. In the bottom-up structure, we use channel-wise attention to assign weights in each channel and use the spatial attention mechanism to assign a corresponding weight at each pixel in the feature maps. This allows the feature maps to respond better to the target's features. Using our method, the detection and segmentation mAPs increased from 70.6% and 62.0% to 76.1% and 65.8%, respectively.
Highlights
Nowadays, the marine transportation industry is making advances at a very fast pace
[1] used structured forest edge detection, morphological image processing and support vector machine (SVM) to detect ships from satellite images downloaded from Google Earth
We propose a ship detection and segmentation method based on an improved Mask R-CNN model
Summary
The rapid growth in the number of ships and shipping volume have caused an increase in the number of maritime violations. Automated ship detection can help to obtain ship distribution information. It plays an increasingly important role in maritime surveillance, monitoring and traffic supervision. It can help to control illegal fishing and cargo transportation. Ship detection in satellite remote sensing images has become an important research topic. Synthetic Aperture Radar (SAR), which allows imaging during both day time and night time, has attracted the attention of many researchers. There has been considerable amount of prior work in SAR image ship detection. Many ship detection methods in SAR images
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