An algorithm on fast detection and tracking of weak infrared targets from comple x background is proposed based on noise variance estimation.Firstly,the backgro und noise is suppressed by the improved morphological filtering,and the target pixel is hig hlighted preliminarily by the variance estimation of the processed multi-frame image,th en the signal-to-noise natio (SNR) is estimated to get the whole image sequence pixel score.The pixels with high scor es are marked as the target pixels,and the marked image is divided and analyzed.Finally,th e target pixels in the continuous image sequence are extracted accurately.The target pixels are de tected as the input of the target tracking algorithm of the Hough transform,and the double-th reshold is set to achieve the effective tracking of the target.The experimental results show t hat the target detection based on the noise variance estimation has a high detection probabilit y and a low false alarm probability in the infrared small target extraction under complex backgrou nd,and the target pixels obtained as the input of the Hough transform can not only effectiv ely track the target,but also simplify the complexity of the algorithm to achieve rapid extra ction and tracking of targets.