Along with the increase of electricity consumption in society, it means that the quality of power inspection gives higher requirements. The traditional manual inspection method is difficult to ensure the stability of checking quality. Without the popularization of manned distribution stations and smart grid methods, replacing manual inspection with electric power inspection robots can improve the inspection quality and inspection efficiency to a certain extent. Along with theimage processing process which is widely used in the robot system, visual impact is not only an effective way for us to obtain information but also the key reflection of the robot system intelligence. Unmanned aircraft as an extremely important robot has long been widely used in all walks of life. Power inspection is the most common use of unmanned aircraft robot inspection. However, due to extreme criteria such as bad weather, relative motion, and shaking of imaging equipment, inspection images are obtained ambiguously. The quality of the inspection image is related to the timely understanding, analysis, and judgment of the power engineering quality inspection database. In the paper, the unmanned aircraft power inspection robot as a scientific research foothold, according to explore the key technology of anti-internet technology to clear the image ambiguity, proposed a complete disambiguation optimization calculation method. The image denoising optimization calculation method based on the directional characteristics of time-frequency analysis and edge maintenance is selected to carry out the finding of the image, which reasonably solves the image resolution bottleneck problem of GIS in unmanned aircraft robot line inspection. Meanwhile, with the emergence of nanorobots in the 21st century, the application and analysis of remote sensing image processing technology in the field of robotic power inspection in this paper will also bring new vitality and vigor to the research of nanopower inspection robots and solve the problem of unclear images existing in nanorobots.