运动目标检测与识别方法研究

为了解决低对比度红外序列图像中运动小目标的检测问题,提出了一种基于多级滤波的检测方法.首先,对具有一定空间分布范围(≤5×5)的小目标,可根据目标/噪声/背景的灰度分布模型具体分析其频谱特性范围.由Fourier变换定义可知,噪声能量主要集中在高频段,背景能量主要集中在低频段,而目标能量则主要分布在中频段,所以可以根据目标的大小,由门函数的Fourier变换估算出各种尺寸目标所处的频段,然后选择不同级数的滤波器将不同大小的候选目标从复杂背景中分离出来.经过多级滤波处理后,再对得到的包含候选目标的图像进行图像分割等适当的后续处理,就可以检测出真正的目标.

Research on detection and recognition method of moving targets

In order to solve the problem of detecting moving small targets in low-contrast infrared image sequences, a new detection method based on multilevel filter is proposed. First of all, for small targets which had certain space distribution scope(≤5×5), frequency characters of target, noise and background were analyzed in detail in terms of the gray distribution model of target, noise and background. Therefore, the conclusion was got. Background was relatively dominant in low frequency part, target was viewable in middle frequency part and noise was more obvious in high frequency part in the frequency domain in terms of Fourier transform. The frequency scope of various sizes of target could be estimated by the Fourier transform of GATE function. Then various sizes of candidate targets could be distinguished from complex background by different level filters. Real targets could be detected by properly processing these images which contain targets.