摘要
针对现有的红外图像中目标分辨率低且边缘弱等问题,提出了一种基于区域特征分割的红外弱小目标提取算法;该算法根据灰度形态学理论,利用红外背景与目标轮廓信息来提取图像的目标信号;其中算法先根据红外图像的灰度与形状的相似度进行归属度处理,来分类出图像中的目标区与背景区;接着,根据边缘检测算法,该算法对目标区的目标的进行轮廓提取;实验结果表明,该算法能够有效的进行目标提取针对红外图像的不同性质;具有精度高,抗干扰能力强的分割优势。
Existing infrared images have some problems such as low resolution and weak edge. To solve these problems,an infrared dim target extraction algorithm based on region characteristic segmentation is proposed. The target signals are extracted through infrared background and target contour according to the theory of gray morphology. Firstly,the object area and the background area in the image are separated according to the similarity of the gray and shape in the infrared images. Then,the target contour in the target area is extracted by using the edge detection algorithm.The results show that this algorithm can effectively extract the targets in the infrared image. It has the advantages of high precision and the strong ability of anti- interference.
出处
《激光与红外》
CAS
CSCD
北大核心
2016年第3期308-312,共5页
Laser & Infrared
关键词
红外目标
区域特征
目标提取
轮廓
相似度
infrared target
regional characteristics
target extraction
contour
similarity