基于视觉注意机制和Hough变换融合的遥感影像油罐提取

Oil Tank Extraction from Remote Sensing Images Based on Visual Attention Mechanism and Hough Transform

Hough变换用于遥感影像地物提取时具有较高的精度,但其算法非常复杂,效率较低。为提高Hough变换处理效率,提出了一种融合视觉注意机制和Hough变换遥感影像提取算法,并以油罐提取为例验证其有效性。首先提取影像的视觉显著性特征图,获取油罐目标显著性区域;然后对显著性区域进行Hough变换检测,得到油罐目标。实验结果证明,该方法能大幅减少Hough变换的计算量,提高效率的同时,提取精度也较高。

Hough transform can achieve high precision in remote sensing image feature extraction, but the algorithm is very complex and inefficient. To improve the Hough transform processing effi- ciency, this paper presents a feature extraction algorithm for remote sensing images combined with visual attention mechanism and Hough transform. Test of oil tanks extraction are made to verify its validity as an example. Firstly, visual salient feature maps are extracted to get significant area of oil tank target. Then, Hough transform detection in significant area is implemented to get the tank target. The results show that the method can significantly reduce the calculation amount of Hough transform and improve efficiency and extraction accuracy.