Super-resolution Image Recognition Method for Static Health of Power Dispatching Room Based on Machine Learning
Aiming at the problem that the operation situation of the power dispatching equipment room is different and the color of the terminal signal light is difficult to identify,a super-resolution image recognition method of the static health degree of the power dispatching equipment room based on machine learning is proposed.The residual threshold is set,and the fuzzy maxi-mum entropy method is used to calculate the optimal separation point between the target class and the background class of the static image of the power dispatching room.The fuzzy membership function is introduced,and the RGB maximum ratio method is used to extract and enhance the super-resolution image signal light.The optimal classification surface is constructed,the classification constraints are set,and the static health degree of the power dispatching room is identified according to the sec-ondary classifier function.The experimental results show that the method can improve the static image quality of the power dis-patching room,and the color feature recognition effect is better,which ensures the accuracy of the static health recognition of the power dispatching room.
万方数据
维普
