Research And Implementation Of Multi-spectral And Panchromatic Image Fusion Algorithm Based On Component Replacement

In recent years,the development of remote sensing technology has also been more widely used in our real-life applications,and more attention has been paid to remote sensing image fusion,among them,multi-spectral and panchromatic image fusion in remote sensing image fusion has received more research and attention.This kind of fusion algorithm combines the advantages of the two kinds of images by fusing panchromatic images and multi-spectral images collected by sensors in the same area,high Quality Fused Image with accurate spectral retention of texture information is obtained.Firstly,the background and research status of remote sensing image fusion are introduced,and some classical fusion algorithms are analyzed in detail.In view of the fact that the existing fusion methods can not take into account both the spatial and spectral information of the image as well as the spectral distortion phenomenon in the fusion process,some improvements are proposed:1.Aiming at the problem of spectral distortion that often occurs in the fusion process of traditional IHS fusion methods,a remote sensing image fusion method of AIHS based on guided filtering is proposed.First,use guided filtering to filter the multispectral image,fully extract the edge information of the image,and use high-pass filtering to filter the multispectral image and the panchromatic image to obtain their respective high-frequency detail components;then,use adaptive AIHS algorithm to solve the adaptive coefficients and get the detail component map;finally,use guided filtering to filter the high-frequency detail components of the multi-spectral image and panchromatic image,extract the spectral information contained in their difference information,and inject it into the details In the component diagram,the fused image is obtained.The original multi-spectral image is guided and filtered,and the edge details of the image can be better maintained;due to the use of an adaptive AIHS algorithm,the detail component map can be adaptively solved,so that each component in the fusion process is more accurate and efficient processing to reduce spectral distortion.This algorithm ensures the fusion of spatial details of the image while maintaining the spectral information,so that the two are better reflected in the fusion result,which can better solve the problem of spectral distortion in the fusion process and improve the utilization of the image.2.In view of the spectral distortion caused by the IHS fusion method during the fusion process,this paper analyzes the causes of this in detail,and points out that the intensity component is not highly correlated with the panchromatic image,it is inconsistent in the spectral response range,and the information difference between the spectra the larger one is the main cause of spectral distortion and loss of information in the fused image.In view of this phenomenon,this paper proposes to equalize the intensity component and the panchromatic image to improve the correlation between the two,obtain the best gray-scale transformation relationship in the histogram matching,obtain the optimal intensity component,and obtain the component replacement fusion image.3.Although the fusion algorithm based on histogram optimization introduced in 2 has effectively improved the correlation between the intensity component and the panchromatic image and reduced the spectral distortion to a certain extent,the obtained optimal intensity component also has certain information.missing.In order to better improve the quality of the fused image and obtain a fused image with richer spatial and spectral information,based on the optimized solution of the histogram,the IHS algorithm is combined with PCA and wavelet transform to expand the number of bands that the IHS algorithm can handle.First convert the multi-spectral image using PCA,and express it with the main component containing the main information,and then the IHS transform the multi-spectral image obtained by dimensionality reduction.The I component and the panchromatic image are improved and matched in 2 to get an optimal match to get new PAN.Then wavelet decomposition of the new plan and components,fusion according to the fusion rules,and then IHS inverse transformation to get the fusion image.