基于灰度特性的海天背景小目标检测

针对复杂海天背景下的小目标检测存在海浪、云层干扰等问题，提出了先提取海天线，然后利用一维最大熵阈值分割法对出现在天空、海面或者海天线附近特定区域的目标进行检测的算法。该算法主要利用天空海面行灰度均值特性，结合梯度运算和形态学运算在海天线的潜在位置中检测边缘，进而用强鲁棒性的Hough变换直线检测法拟合海天线，实现对海天线的准确定位。实验处理分辨率为：256pixel×256pixel的位图时，定位海天线需时4．1ms，检测到目标需时5．3ms，完全满足高帧频图像处理的实时性要求。实验结果表明，该算法能够快速、准确地检测出小目标，大大降低了虚警率。

Detection of sea-sky line in complicated background based on grey characteristics

To detect precisely small and dim targets in a complicated background with ocean waves and cloud clutters, a new algorithm is presented which picks up the sea-sky line at first, then efficiently detects the targets on the special region under sky, ocean, and nearby the sea-sky line. On the basis of the line gray characteristics of sea and sky, this algorithm combines the gradient method and morphologic operation to segment the sub-band image in a potential area of sea-sky line, further to fit the sea-sky line by Hough transform to implement the precise location of the sea-sky line. The experiment result shows that this method can extract the sea-sky line from the complicated sea-sky background and can detect the small targets fast and efficiently. For a 256 pixel×256 pixel file, the sea-sky line can be located in 4.1 ms and a small target can be detected in 5.3 ms, which demonstrates that the algorithm can meet the requirements of high frame image processing in real time.