There are numerous problems with infrared imaging using power equipment, such as dark brightness and low contrast. To solve these problems, an enhancement algorithm using a color-model space was proposed. In this method, the contrast and brightness enhancement of the image are processed in the HSV and RGB spaces, respectively. First, the high gray levels of the image are preprocessed, and the mixed filtering method is adopted to suppress the noise in the image. An enhancement function is used to improve the brightness of the image. Finally, the enhanced image is converted into the HSV space, the H, S and V component images are extracted, the gamma transform and CLAHE algorithms are used to improve the brightness of V component, and a nonlinear saturation correction function is used to process component S to improve the image contrast. Finally, the enhanced image in the HSV space is obtained by the corresponding fusion of each processing and extraction component, and is transferred back to the RGB space to obtain the final output image. Experimental results show that the proposed algorithm can significantly improve the contrast and brightness of infrared images. The average gray mean and standard deviation of the enhanced 6 groups of images were 115.94 and 78.65, respectively, which are improvements of 81.59 and 36.17 compared with the original image.