Fusion of Multiple Basic PDE Models for Enhancing Road Surface Images
路面图像增强的多偏微分方程融合法

Since P-M diffusion,Shock filter,coherence enhancing diffusion and their fusing models in existence can not enhance road surface images well,a new model fused by the 3 basic PDE models is proposed.First the relationship between the diffusion strength of coherence enhancing diffusion and the degree of consistency of local directional structure is analyzed,and on the assumption that images are without noise,3 weight functions depending on the local gradients and the degree of consistency of local directional structure are designed,and the 3 basic PDE models are fused together by the 3 weight functions.Then according to the characteristics of road surface images,the new model for noised free images are generalized to process complex road surface images by improving the basic PDE models and the weight functions.Further more the major parameters of the generalized new model are discussed.Theoretic analyses and experimental results show the effectiveness of the new model in denoising,sharpening the crack edges and enhancing the flow-like structure of cracks.