To solve the problem of detecting small infrared targets ininfrared optical systems under complex backgrounds, an information processing model based on visual feature integration was established, and a dim small target detection method based on visual feature integration was proposed. First, the difference of Gaussians model of the receptive fields of retinal ganglion cells was used for processing the primary information of infrared images and initially detecting dim small targets. Then, the features containing the dim small targets were extracted by spatial and frequency channels. In the spatial channel, the second-order differential Hessian matrix was constructed with image information, and the local extremum was determined by calculating the basis truth and determinantto extract the structural component features. In the frequency domain channel, wavelets were used for decomposing the image frequency domain to extract the features of high-frequency components containing dim small targets. Finally, the spatial channel and frequency channel were integrated to extract the dim small targets from complex backgrounds. Experimental results indicate that when the false alarm rate is 10-3, the average detection probability is 95.17%. The proposed method can basically meet the requirements of stability, reliability, and high accuracy.