An algorithm combined target detection and target recognition for a scanning infrared early-warning system was proposed to realize early-warning of air threats. First, the dimension of Laplacian of Gaussian (LOG) operator was reduced to change the isotropic characteristics of classical LOG operator and to reduce its information losses. Then, an eight-neighborhood local filter was proposed to enhance targets and suppress backgrounds by setting relevant parameters. Finally, the targets were extracted from filted results and were recognized by the Support Vector Machine(SVM) algorithm. In order to simplify the recognition procedure within preciseness, the Sufficient Dimension Reduction (SDR) based on the covariance operator was used to reduce the feature dimensions of samples and targets before recognition so that to simplify the classical filter and recognition algorithm while to improve the algorithm efficiency. Experimental results indicate that the proposed method gets better results than the high-dimensional algorithm and it can satisfy the system requirements of real-time performance. The false-warning rate and the miss-warning rate are lower than 7% and 5%, respectively.