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An Adaptive Multisensor Image Fusion Method Based on Monogenic Features

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.