Design of SAR image target contour enhancement preprocessing module
In response to the issue that the every channel's data in three channels of synthetic aperture radar(SAR)images is the same which may cause channel information redundancy when deep learning-based target detection network detects the targets of SAR,a channel expansion preprocessing algorithm module based on smoothing and sharpening filtering is proposed,which is then named as ORLM(Original,Roberts,Laplace,Mean)block.The proposed algorithm in this article can be encapsulated,integrated,and applied to the data reading program of the target detection algorithm.It can extend the channel of SAR images with the same data in each channel,and ensure that the expanded channel data fully contains the contour information of the target.Through training,testing and comparative experiments of the target detection network with and without the proposed preprocessing algorithm on different ship target detection datasets,the experimental results show that the preprocessing algorithm proposed can be applied to various target detection algorithms and can improve detection accuracy without significantly reducing of the real-time detection performance.
万方数据
维普
