摘要
针对现有红外图像受环境与背景等因素干扰而无法对红外图像进行精确的目标提取的问题,根据物体的辐射特征,提出了一种具有高精度红外目标分离的提取算法;该算法从红外成像的角度出发,充分利用物体的辐射分布特点对目标的辐射量以及分布概率进行求取;最终转换为图像的灰度级,并结合灰度差特性实现目标的高精度分离。实验结果表明,该算法能够获得相比其他算法更精确的目标图像,并具有抗干扰能力强与耗时低的目标提取优势。
The targets cannot be accurately extracted in the existing infrared image for environmental factors and background interference.To solve this problem,an extraction algorithm with high precision infrared target separation was proposed based on the radiation characteristics of the object.The amount of radiation and the probability distribution were calculated by using radiation distribution characteristics of the object.The amount of radiation was converted to gradation gray level in the last.And combined with the characteristics of gray difference,the high-precision separation of the goal was achieved.Experimental results show that this algorithm can obtain more accurate target image compared with other algorithms.And it has the advantages of strong anti-interference ability and low time-consuming.
出处
《激光与红外》
CAS
CSCD
北大核心
2016年第5期634-638,共5页
Laser & Infrared
关键词
目标提取
辐射特征
红外弱目标
分布概率
object extraction
radiation characteristics
infrared weak target
probability distribution
