基于形态学Top-Hat算子的小目标检测方法  

Small Target Detection Method Based on Morphology Top-Hat Operator

作　　者：叶斌[1] 彭嘉雄[1] 

机构地区：[1]华中理工大学图象识别与人工智能研究所图象信息处理与智能控制教育部重点实验室,武汉430074

出　　处：《中国图象图形学报（A辑）》2002年第7期638-642,共5页Journal of Image and Graphics

摘　　要：针对红外序列图象中运动弱小目标的检测问题 ,提出了一种基于能量累积与Top Hat算子的小目标检测方法 .该方法是首先设置一定大小的滑动窗口 ,并通过对窗口内的图象序列进行能量累积来去除图象中的随机噪声 ,以提高目标的信噪比 ;然后对能量累积后的图象采用形态学中的Top Hat算子完成候选小目标的检测工作 ;最后利用序列图象中目标运动的连续性和轨迹的一致性来筛选出真正的目标 .同时进行了该方法与传统高通滤波检测方法 ,在抗噪声性能、背景抑制性能以及抑制虚警目标性能等方面差异的比较实验 .实验结果表明 ,基于能量累积与Top Hat算子的小目标检测方法在这 3个方面都优于高通滤波法 ,它能够快速、可靠检测出低信噪比的运动小目标 .A new small target detection method based on energy accumulation and morphology top-hat operator is presented for solving detection of moving small target with low SNR in infrared image sequence. Accumulating the energy of the image sequence in the sliding window with a setting size can remove the random noise in the images in order to increase the SNR, the principle of accumulating the energy of the image sequence is given. Morphology Top-Hat operator can detect peaks and valleys in images, it can be used to detect candidate small targets. According to motion continuity and motion trajectory consistency in multi-frame successive image, the true small targets can be filtrated from candidate small targets. The algorithm of small target detection based on morphology Top-Hat is given. By means of experiments the performances of noise proof and background suppression and false target suppression are compared between our detection method and high-pass filtering detection method. The experiment results show that the method is better than the high pass filtering method in the performances of target detection and it can effectively and reliably detect the moving point target with low SNR.

关 键 词：形态学 小目标检测 能量累积 图象处理 TOP-HAT算子 滤波 图象流 红外序列图象 

分 类 号：TN911.73[电子电信—通信与信息系统]