In last few years,guided image fusion algorithms become more and more popular.However,the current algorithms cannot solve the halo artifacts.We propose an image fusion algorithm based on fast weighted guided filter.Fi...In last few years,guided image fusion algorithms become more and more popular.However,the current algorithms cannot solve the halo artifacts.We propose an image fusion algorithm based on fast weighted guided filter.Firstly,the source images are separated into a series of high and low frequency components.Secondly,three visual features of the source image are extracted to construct a decision graph model.Thirdly,a fast weighted guided filter is raised to optimize the result obtained in the previous step and reduce the time complexity by considering the correlation among neighboring pixels.Finally,the image obtained in the previous step is combined with the weight map to realize the image fusion.The proposed algorithm is applied to multi-focus,visible-infrared and multi-modal image respectively and the final results show that the algorithm effectively solves the halo artifacts of the merged images with higher efficiency,and is better than the traditional method considering subjective visual consequent and objective evaluation.展开更多
基金国家自然科学基金(the National Natural Science Foundation of China under Grant No.60605021)国家高技术研究发展计划(The National High Technology Research and Development Program of China under Grant No.2006AA04Z223)
基金supported by the National Natural Science Foundation of China(61472324 61671383)+1 种基金Shaanxi Key Industry Innovation Chain Project(2018ZDCXL-G-12-2 2019ZDLGY14-02-02)
文摘In last few years,guided image fusion algorithms become more and more popular.However,the current algorithms cannot solve the halo artifacts.We propose an image fusion algorithm based on fast weighted guided filter.Firstly,the source images are separated into a series of high and low frequency components.Secondly,three visual features of the source image are extracted to construct a decision graph model.Thirdly,a fast weighted guided filter is raised to optimize the result obtained in the previous step and reduce the time complexity by considering the correlation among neighboring pixels.Finally,the image obtained in the previous step is combined with the weight map to realize the image fusion.The proposed algorithm is applied to multi-focus,visible-infrared and multi-modal image respectively and the final results show that the algorithm effectively solves the halo artifacts of the merged images with higher efficiency,and is better than the traditional method considering subjective visual consequent and objective evaluation.
