Co-Feature and Shape Prior Based Saliency Analysis for Oil Tank Detection in Remote Sensing Images

The great increase in the resolution of remote sensing images comes with the problem of high computational complexity. Besides, the irregular circular shape of the tanks and the difficulty to establish the dataset make the detection task a big challenge. This paper proposes a co-feature and shape prior based saliency analysis model to extract the candidates. Two kinds of saliency maps are considered including the co-feature spatial residual map which is extracted as the common parts of different feature maps and the shape saliency map which provides the complementary information with the shape prior knowledge of circular targets. Besides, the curvature driven active contour model is used to insure the precise of the extracted contour. The quantitative evaluation of the experiments is conducted considering the detection precision and the geometric error. Results show that the proposed method is superior both in the pixel level performance and the geometric shape.