一种基于图像分割和归一化灰度Hough变换的SAR图像舰船尾迹CFAR检测算法
doi: 10.3724/SP.J.1146.2009.01527
A New Ship Wake CFAR Detection Algorithm in SAR Images Based on Image Segmentation and Normalized Hough Transform
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摘要: 该文提出了一种新的SAR图像舰船尾迹的恒虚警检测算法。该方法首先检测出舰船并将舰船部分用图像灰度均值代替;分别以舰船重心为中心分割出一定尾迹长度的正方形区域并以舰船重心为中心将图像分割成4个子图像,对各子图像进行归一化灰度Hough变换,分割后的尾迹在子图像中的对比度得到了提高。在各子图像变换域依概率模型进行统计建模实现了CFAR检测,最后将4个子图像的检测结果进行融合得到最终的检测结果。检测结果更好地提取出了尾迹,并且实现了尾迹的CFAR检测。仿真结果验证了算法的有效性。
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关键词:
- SAR /
- 图像分割 /
- 尾迹检测 /
- 恒虚警 /
- 归一化Hough变换
Abstract: A new ship wake CFAR detection algorithm is proposed in SAR images. The algorithm first detects all the ships and replaces the pixels gray value of the detected ship with the gray mean value; Then, with the ship barycenter as the center, a square image with a certain length is got and the image is segmented into four sub-images and to perform Normalized Hough Transform on every sub-image; The gray contrast of wake to clutter in the sub-image is enhanced. The probability model in the transform domain of each sub-image is constructed to realize CFAR detection; Finally, the detection results of the sub-images are fused to get the final detection. The detecting results are much better and can be used for CFAR detection. The simulation experiment proves the effectiveness of the algorithm.-
Key words:
- SAR /
- Image segmentation /
- Ship wake detection /
- CFAR /
- Normalized Hough transform
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