研究目的
To enhance the autonomous ability of USV on the ocean surface, successfully completing the detection and identification of marine targets is necessary.
研究成果
The weighted averaging fusion method has been addressed. The effectiveness and practicability of the algorithm are evaluated from a computer simulation point of view. By comparing the images obtained by fusion, the intended purpose can be achieved, so that the USV can overcome unfavourable factors caused by weather, night and the like on the sea surface.
研究不足
In the process of image processing, there are also some problems difficult to overcome, such as that texture details did not reach the expected value under current technology.
1：Experimental Design and Method Selection:
The algorithm for weighted averaging fusion of visible/infrared images is proposed.
2：Sample Selection and Data Sources:
The pictures used are derived from the Caltech-101 image library.
3：List of Experimental Equipment and Materials:
MATLAB R2015a environment with a personal computer.
4：Experimental Procedures and Operational Workflow:
Firstly, the visible light/infrared devices collect the target surrounding information, perform feature analysis, and complete the anti-fog and de-noising preprocessing. Secondly, feature extractions of the visible and infrared target images are performed, respectively, and the recognition of the target image is further completed. Finally, image fusion is performed by weighted averaging of the targets detected by visible light and infrared images.
5：Data Analysis Methods:
The sharpness of the visible, infrared, and fused images are calculated, respectively.
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