基于先验场景知识的sar目标检测虚警去除方法

Synthetic aperture radar (SAR) target detection false alarm elimination method based on priori scene knowledge

Abstract

The invention discloses a synthetic aperture radar (SAR) target detection false alarm elimination method based on priori scene knowledge, wherein the SAR target detection false alarm elimination method mainly settles a problem of large number of SAR image target detection false alarms in a complex scene. The SAR target detection false alarm elimination method comprises the following steps of (1) inputting an original SAR image, performing down-sampling twice and mean filtering on the original SAR image; (2) performing area growth on the SAR image after preprocessing, eliminating an object-sized communicating area which are not grown out, and using the rest non-grown-out communicating area as the area to be classified; (3) selecting a training sample, performing classification on the area to be classified, and obtaining an area in which an object impossibly exists; and (4) eliminating the false alarm that is detected in the area in which the object impossibly exists, and obtaining a result image. The SAR target detection false alarm elimination method can effectively reduce detection of false alarm in the complex scene and can be used for afterprocessing in detection of the SAR image target.
本发明公开了一种基于先验场景知识的SAR目标检测虚警去除方法,主要解决复杂场景下SAR图像目标检测虚警过多的问题。其实现步骤为:(1)输入原始SAR图像,对原始SAR图像进行两次下采样和均值滤波预处理;(2)对预处理后的SAR图像进行区域生长,去除未生长出的目标大小状的连通区域,剩余的未生长出的连通区域为待分类区域;(3)选取训练样本,对待分类区域进行一类分类,得到不可能存在目标的区域;(4)去除不可能存在目标区域中检测到虚警,得到结果图像。本发明能够有效的减少复杂场景下的检测虚警,可用于对SAR图像目标检测的后处理。

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