Urban Planning Image Feature Enhancement and Simulation Based on Partial Differential Equation Method

Based on the introduction of the basic ideas and related technologies of partial differential equations, as well as the method of path planning, the application of partial differential equations in solving urban path planning is studied. The path planning model of partial differential equations and the setting of obstacle boundary conditions are introduced, and adaptive. Theoretical research and experimental results show that it is feasible and effective to solve urban path planning by partial differential equations, which provides a new way for urban path planning research ideas and methods. This paper proposes an image detection algorithm based on diffusion equation. According to the logarithmic transformation, the multiplicative speckle noise in the image can be converted into additive noise. We first perform logarithmic transformation on the image and then use the denoising model of the diffusion equation to filter out the noise in the image and then use the logarithm to recognize the image. The difference image is obtained by the domain difference method, and finally, the difference image is classified by the clustering algorithm, and the change area is extracted. Experiments show that the algorithm can effectively reduce the effect of multiplicative speckle noise on the change detection results, improve the accuracy of change detection, and shorten the change detection time. This article takes the path planning problem of a two-dimensional space city as an example to discuss the application of partial differential equations. According to the principle of energy conservation, this paper uses the two-dimensional space radiant heat conduction equation as an example to model and illustrate the solution of the path planning problem.