摘要
针对红外弱小目标检测需求,根据红外弱小目标图像特性及其小波分析特性,提出了一种基于小波分析的红外弱小目标检测算法。算法首先对红外弱小目标图像进行小波分解;然后置低频小波系数为零去除背景,阈值化高频小波系数滤除噪声,自适应子带增强加强目标能量;最后进行小波逆变换并进行自适应阈值分割。实验结果表明,提出的算法速度快、抑制噪声的能力强。
Aiming at the requirement of infrared dim target detection, and according to image feature and wavelet analysis character of infrared dim small target, an infrared dim small target detection algorithm based on wavelet analysis is proposed. First, the algorithm analyzes infrared dim small target image using wavelet; then sets low frequency wavelet coefficient to zero to wipe off the background, threshold for high frequency wavelet coefficient to filter noise and self-adaptive subband enhancement to enhance the energy of target; finally reverses wavelet transform and self-adapt threshold segment. The experiment results indicate that the algorithm has merits of high speed and stronger denoise ability.
出处
《安阳工学院学报》
2008年第4期41-43,128,共4页
Journal of Anyang Institute of Technology
关键词
红外图像
弱小目标
目标检测
小波分析
infrared image
small target
target detection
wavelet analysis
