The fault location and identification method of UHV transmission lines based on laser image processing technology is studied to enhance the fault location and identification effect. Firstly, a laser image of UHV transmission line is captured by single point laser scanning imager, and the laser image of UHV transmission line is denoised by Wiener filter algorithm. Subsequently, by using the improved multi-significance integration algorithm and K-means clustering algorithm, the significant color features and structural features are extracted from the denoised laser image, and the color features and structural features are fused to obtain the significant fault region of UHV transmission lines. Next, through the morphology of multi-scale contour structure elements, the significant fault region is processed and the edge image of the fault region is obtained. Based on the statistical analysis of edge image color distribution, the color decision model is constructed to highlight the fault region and extract the edge contour of the fault region. Finally, the fault location can be accurately identified by drawing the edge outline of the fault area in the original UHV transmission line laser image. Experimental results show that this method can effectively acquire the laser image of the UHV transmission line and complete the denoising process. It also successfully extracts color and structural features and generates the edge image of the fault area, thereby completing fault location identification. This method enables accurate identification of the fault location in transmission lines, regardless of the transition resistors involved.