多特征融合红外舰船尾流检测方法研究

摘要/Abstract

摘要： 针对舰船热尾流红外图像易受海杂波干扰、对比度偏低,传统方式无法对其进行识别的问题,提出一种基于Gabor滤波组和局部信息熵特征融合的红外舰船尾流检测算法。首先,应用灰度共生矩阵计算尾流与海面背景的对比度,判断该区域是否存在舰船尾迹,并提取出感兴趣区域以提高算法后续处理速度;其次,将多方向Gabor滤波器和局部信息熵两种纹理进行特征融合,实现舰船尾流特征增强;最后,经阈值分割、Hough变换实现红外舰船尾迹检测。实验结果表明,该方法能够有效地保留舰船尾流的纹理特征和细节,准确地提取完整的尾流边缘,从而大大提高检测率。

关键词: Gabor滤波, 灰度共生矩阵, 霍夫变换, 舰船尾流检测, 局部信息熵

Abstract: A new algorithm of infrared ship wake detection based on fusion of Gabor filter and local information entropy was proposed to solve the problem that the infrared image of ship wake is easily disturbed by the sea clutter,the contrast is low,and the image can not be identified by the traditional method.First of all,the contrast between the wake and the sea background is calculated by using the gray level co-occurrence matrix to determine whether there is a ship wake in the region,and the region of interest is extracted to improve the processing speed of the algorithm.Secondly,multi direction Gabor filter and local information entropy are used for feature fusion to realize the feature enhancement of ship wake.Finally,the infrared ship wake detection is realized by threshold segmentation and Hough transform.Experimental results show that this method can effectively preserve the texture features and details of ship wake,and accurately extract the complete wake edge,which greatly improves detection rate.

Key words: Gabor filtering, Gray level co-occurrence matrix, Hough transform, Local information entropy, Ship wake detection

中图分类号:

TP751.1

邹娜, 田金文. 多特征融合红外舰船尾流检测方法研究[J]. 计算机科学, 2018, 45(11A): 172-175. https://doi.org/

ZOU Na, TIAN Jin-wen. Research on Multi Feature Fusion Infrared Ship Wake Detection[J]. Computer Science, 2018, 45(11A): 172-175. https://doi.org/

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