红外技术2025，Vol.47Issue(2)：201-210,10.
基于改进的二维Kaniadakis熵与快速引导滤波的图像融合
Image Fusion Based on Simplified Two-Dimensional Kaniadakis Entropy Segmentation Algorithm and Fast Guided Filtering
摘要
Abstract
In the field of infrared technology,the fusion of infrared and visible images is important.To obtain infrared and visible fusion images with clear targets and rich details,this paper proposes an infrared and visible image fusion method based on an improved two-dimensional Kaniadakis entropy segmentation method and fast guided filtering.First,a simplified two-dimensional Kaniadakis entropy segmentation algorithm(S2DKan)is used to fully extract the target from the infrared image.Then,the non-subsampled shearlet transform(NSST)is performed on the infrared and visible images to obtain the low-and high-frequency sub-bands,and fast guided filtering is applied to the obtained high-frequency components to retain rich visible image details.The low-frequency fusion coefficient is obtained from the extracted target image and the infrared and visible low-frequency components using the low-frequency fusion rule.The high-frequency fusion coefficient is obtained from the enhanced high-frequency sub-band components using the dual-channel spiking cortical model(DCSCM).Finally,the fused image is obtained using the inverse NSST transform.Experimental results show that the fusion image obtained by the proposed algorithm has clear targets and background information and that the algorithm's effect is stable.关键词
图像融合/二维Kaniadakis熵/快速引导滤波/双通道脉冲发放皮层模型Key words
image fusion/two-dimensional Kaniadakis entropy/fast guided filtering/dual channel spiking cortical model分类
信息技术与安全科学引用本文复制引用
巩稼民,张磊,刘尚辉,蒋杰伟,金库..基于改进的二维Kaniadakis熵与快速引导滤波的图像融合[J].红外技术,2025,47(2):201-210,10.基金项目
国家自然科学基金(61775180,62276210),陕西省自然科学基础研究计划资助项目(2022JM-380). （61775180,62276210）
