Infrared and visible heterogeneous image matching based on fusion of features
current infrared and visible image registration does not consider the gray level and spatial position,and the average normalized correction retrieval rank of the matching results is high.Therefore,a fusion feature based infra-red and visible light heterogenous image matching algorithm is proposed.Analyze the gray difference characteristics of the middle rectangular area of the image to be matched,draw the Haar feature density distribution map,and implement image filtering based on this.Extracting filtered image grayscale features,pixel density features,and texture features through discrete transformation(K-L),completing the compression and fusion of multiple image features.Based on fusion features,calculate the lattice closeness between the infrared image to be matched and the visible light image,and obtain the matching results of heterogeneous images.The experimental results show that after the application of the proposed method,the average Ar value of the heterogenous image matching results is only 0.35,which better meets the image matching requirements.
NETL
NSTL
万方数据
