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An Adaptive Multisensor Image Fusion Method Based on Monogenic Features

机译:基于单体特征的自适应多传感器图像融合方法

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摘要

Each kind of sensor is designed to adapt to a specific environment and usage scope. In this paper, an adaptive multisensor image fusion method based on monogenic features is proposed. For the proposed method, the monogenic features are extracted from the source images including monogenic amplitude, monogenic phase and monogenic orientation features. The energy matching similarity measure is used to measure the monogenic amplitude feature, and the complex coefficient structure similarity measure is used to characterize the monogenic phase and the monogenic orientation feature. Analyses the monogenic features in different types of regions, different fusion strategies are adopted for different characteristic regions. By means of visible and infrared image fusion, SAR and infrared image fusion experiments, the proposed method can effectively preserve a large amount of information and significantly improve the visual quality of the fused image, which can be evaluated with objective indicators.
机译:各种传感器旨在适应特定的环境和使用范围。本文提出了一种基于单一特征的自适应多传感器图像融合方法。对于所提出的方法,从包括单一的幅度,单一的相和单一的取向特征的源图像中提取单一的细胞。能量匹配相似度测量用于测量单一的变量幅度特征,并且复杂系数结构相似度测量用于表征单晶相和单一的取向特征。分析不同类型地区的单一形单一特征,不同的融合策略被采用不同特征区域。通过可见光和红外图像融合,SAR和红外图像融合实验,所提出的方法可以有效地保持大量信息,并显着提高熔融图像的视觉质量,可以用客观指标评估。

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