Deep learning has been widely applied to ship detection in Synthetic Aperture Radar (SAR) images. Unlike optical images, the current object detection methods have the problem of weak feature representation due to the low object resolution in SAR images. In addition, disturbed by chaotic noise, ...
This paper discusses an image processing architecture and tools to address the problem of ship detection in synthetic-aperture radar images. The detection strategy relies on a tree-based representation of images, here a Maxtree, and graph signal processing tools. Radiometric as well as geometric attr...
• We achieve favorable results on different SAR image datasets, demonstrating the effectiveness and robustness of our method.摘要 •We propose an effective and stable single-stage detector in a refined manner, achieving high accuracy for small ship detection.•We design a feature pyramids fusio...
船只探测PNNCFAR合成孔径雷达In this paper,we present an improved constant false alarm rate(CFAR)algorithm for ship detection in syn-thetic aperture radar(SAR)imagery.The algorithm includes the probabilistic neural networks(PNN),CFAR tech-nique,golden section method and area growth method.The PNN is ...
实际的位置13SAR图像解译的关键信息1.SAR是一种主动传感器,量测信号的返回时间和后向散射的强弱;2.侧视几何导致了独特的图像效果,例如叠掩、透视收缩、阴影,这些是不可避免的,但是也是有用的信息;3.SAR图像的特征是由SAR系统参数和目标参数共同决定的;4.图像的统计信息和光学影像不同,因此要使用适合SAR的图像处理...
Target detection in the multiscale situation where there exit multiple ship targets with different sizes is a challenging task due to the mismatch of the s... S Chen,X Li - 《Signal Image & Video Processing》 被引量: 0发表: 2019年 Ship Detection in High-Resolution SAR Images by Clustering...
This work proposes a SAR image ship detection model SSE-Ship that combines image context to extend the detection field of view domain and effectively enhance feature extraction information to solve the problem of low detection rate in SAR images with ship combination and ship fusion scenes. ...
This highlights the need to monitor the Canal to prevent similar disturbances in the future. In this paper, we propose a CNN-based attention-guided self-learning framework for ship detection from 3m high-resolution COSMO-SkyMed SAR imagery acqui...
Ship detection on the SAR images for marine monitoring has a wide usage. SAR technology helps us to have a better monitoring over intended sections, without considering atmospheric conditions, or image shooting time. In recent years, with advancements in convolutional neural network (CNN), which is...
For the detection of marine ship objects in radar images, large-scale networks based on deep learning are difficult to be deployed on existing radar-equipped devices. This paper proposes a lightweight convolutional neural ne...