Geospatial Contextual Attention Mechanism for Automatic and Fast Airport Detection in SAR Imagery

The automatic extraction of airport runway areas from high-resolution Synthetic Aperture Radar (SAR) images is of great research significance in the military and civilian fields. However, it is still challenging to distinguish the airport from surrounding objects in SAR images. In this article, a new framework is proposed to extract airport runway areas (runways, taxiways, packing lots, and aircrafts) in a fast and automatic manner. The framework is based on the Geospatial Contextual Attention Mechanism (GCAM) for geospatial feature learning and classification, which is employed together with the down-sampling and coordinate mapping modules. To evaluate the performance of the proposed framework, three large-scale Gaofen-3 SAR images with 1m resolution are utilized in the experiment. According to the results, Mean Pixels Accuracy (MPA) and Mean Intersection Over Union (MIOU) of the GCAM are 0.9850 and 0.9536, respectively, which outperform RefineNet, DeepLabV3+, and MDDA. The training time of GCAM for the dataset is 2.25h, and the average testing time for the five SAR images is only 18.15s. Therefore, GCAM can offer rapid and automatic airport detection from high-resolution SAR images with high accuracy, which can further be employed to mark the airport to greatly improve the detection accuracy of the aircrafts.

[1]  Hujun Bao,et al.  Deep Snake for Real-Time Instance Segmentation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Shiping Ma,et al.  Remote Sensing Airport Detection Based on End-to-End Deep Transferable Convolutional Neural Networks , 2019, IEEE Geoscience and Remote Sensing Letters.

[3]  Liming Zhang,et al.  Airport Target Detection in Remote Sensing Images: A New Method Based on Two-Way Saliency , 2015, IEEE Geoscience and Remote Sensing Letters.

[4]  Jongyoul Park,et al.  CenterMask: Real-Time Anchor-Free Instance Segmentation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Thomas A. Funkhouser,et al.  Dilated Residual Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Enhua Wu,et al.  Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Yue Liu,et al.  Airport Extraction via Complementary Saliency Analysis and Saliency-Oriented Active Contour Model , 2018, IEEE Geoscience and Remote Sensing Letters.

[8]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[9]  Qi Li,et al.  Dense Attention Pyramid Networks for Multi-Scale Ship Detection in SAR Images , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Yueguan Lin,et al.  Research Development of High Precision Real-time Airborne InSAR System , 2014, J. Comput..

[11]  Ian D. Reid,et al.  RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Jin Xing,et al.  Automatic Extraction of Water and Shadow from SAR Images Based on a Multi-Resolution Dense Encoder and Decoder Network , 2019, Sensors.

[13]  Wei Xiong,et al.  Automatic recognition of airfield runways based on Radon transform and hypothesis testing in SAR images , 2012, Proceedings of 2012 5th Global Symposium on Millimeter-Waves.

[14]  Peng Zhang,et al.  A New Framework for Automatic Airports Extraction from SAR Images Using Multi-Level Dual Attention Mechanism , 2020, Remote. Sens..

[15]  Weiwei Jiang,et al.  Simultaneous Ship Detection and Orientation Estimation in SAR Images Based on Attention Module and Angle Regression , 2018, Sensors.

[16]  Liu Liu,et al.  Airport detection based on Line Segment Detector , 2012, 2012 International Conference on Computer Vision in Remote Sensing.

[17]  Iasonas Kokkinos,et al.  Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.

[18]  Ping Han,et al.  A Runway Detection Method Based on Classification Using Optimized Polarimetric Features and HOG Features for PolSAR Images , 2020, IEEE Access.

[19]  George Papandreou,et al.  Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.

[20]  Hao Chen,et al.  BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Peng Zhang,et al.  A New Deep Learning Network for Automatic Bridge Detection from SAR Images Based on Balanced and Attention Mechanism , 2020, Remote. Sens..

[22]  Zhang Ning,et al.  Airport detection using convolutional neural network and salient feature , 2019 .

[23]  George Papandreou,et al.  Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation , 2018, ECCV.

[24]  Jiashi Feng,et al.  Strip Pooling: Rethinking Spatial Pooling for Scene Parsing , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[25]  Phil Blunsom,et al.  A Convolutional Neural Network for Modelling Sentences , 2014, ACL.

[26]  Xiangyu Zhang,et al.  Large Kernel Matters — Improve Semantic Segmentation by Global Convolutional Network , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[27]  Qiang Chen,et al.  Network In Network , 2013, ICLR.

[28]  Jin Xing,et al.  A New Deep Learning Algorithm for SAR Scene Classification Based on Spatial Statistical Modeling and Features Re-Calibration , 2019, Sensors.

[29]  Yang Long,et al.  Airport Detection Based on a Multiscale Fusion Feature for Optical Remote Sensing Images , 2017, IEEE Geoscience and Remote Sensing Letters.

[30]  Ning Li,et al.  A Hierarchical Airport Detection Method Using Spatial Analysis and Deep Learning , 2019, Remote. Sens..

[31]  Yiming Pi,et al.  Airport Detection in Large-Scale SAR Images via Line Segment Grouping and Saliency Analysis , 2018, IEEE Geoscience and Remote Sensing Letters.

[32]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Yue Liu,et al.  Integrating Sparse Reconstruction Saliency and Target-Aware Active Contour Model for Airport Extraction , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[34]  Iasonas Kokkinos,et al.  DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Li Ying,et al.  Fast parallel method of airport target extraction in high resolution remote sensing image , 2012 .