基于图像融合与处理技术的舰船目标检测

The ship detection based on image fusion and processing technology

舰船目标检测在国民经济、国家安全和环境保护等诸多方面有非常重要的地位。本文首先获取原始的光学遥感图像,进行预处理去除噪声等不良因素的干扰;其次进行目标增强,利用CRC自适应控制的结构元素尺寸,便于感兴趣的视觉焦点提取,运用自适应滤波器提取出划定的感兴趣区域的特征信息,利用图像信息融合检测出舰船目标;最后通过实验进行验证本文设计的算法,与传统舰船目标检测相比,提高了检测率,即使存在噪音等不利因素也能有效地检测出目标,并且降低了漏检率和虚警率。

Ship detection has a very important role in the national economy and national security, as well as many other aspects of environmental protection. First, this article get the original optical remote sensing image. Then pretreated to remove interference noise and other adverse factors. Secondly, the target enhancement and use of structural elements size CRC adaptive control to extract the visual focus of interest. Applying the adaptive filter to extract a region of interest delineated feature information. Using image information fusion to detect ship target. Finally, experimental verification algorithms designed in this paper compared to traditional ship detection improves the detection rate. Even the presence of noise and other negative factors can effectively detect the target, and reduce the missing rate and false alarm rate.