基于小波多尺度分析及Fisher分割的红外弱小目标检测

介绍一种新的红外图像序列中的弱小目标检测方法，利用小波多分辨特性，对图像进行预处理，以抑制背景杂波；利用改进的Fisher算法，对经预处理后的图像进行分割，最终将目标从背景中分离出来；对相邻帧进行差分运算，估计目标的运动轨迹采用本文方法与类别方差自动门限法，对大量的红外弱小目标进行了检测，实验对比结果表明了该算法的有效性。

WEAK AND SMALL OBJECT DETECTION BASED ON WAVELET MULTI-SCALE ANALYSIS AND FISHER ALGORITHM

Proposing a novel method to detect weak and small targets in infrared image sequences. Preprocess is imposed on image by use of wavelet multi scale analysis to inhibiter arbitrary background. By utilizing the improved Fisher algorithm, we then threshold the preprocessed images, and separate the targets from the background. Target’s pose estimation is obtained through computing the difference of two near frames that have been threshold. Comparing the experimental results on real IR image sequence to that of automatic threshold on class variance show its effectiveness.