In view of the shortcomings of traditional local contrast algorithm in the background of strong clutter,which is easy to introduce false alarm target,an infrared small target detection algorithm with spatial weighted local contrast is proposed.Firstly,the two-dimensional Gaussian difference filter with central excitation and lateral inhibition is used to suppress most of the background clutter of the original image,so as to improve the signal-to-noise ratio of the image;secondly,the ratio of the target mean value to the median value of the neighborhood is used to measure the local contrast,and then the gray mean difference of each region of the target is used to weight the local contrast to generate the target saliency map;finally,the image is displayed the real target is detected by adaptive threshold segmentation.Experimental results show that,compared with other detection methods,the algorithm not only has a high signal to noise ratio gain and background suppression factor,but also has a high detection rate and a low false alarm rate.It is an effective infrared small target detection method.