- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Effective detection by fusing visible and infrared images of targets for Unmanned Surface Vehicles
摘要： The research progress for Unmanned Surface Vehicle (USV) is of great significance to human off-shore operations. Target detection is the foundation for USV applications. Ocean wave, frog, and illumination are the most important factors that affect exactness of target detection through visible and infrared images. This paper proposes an algorithm for weighted averaging fusion of visible/infrared images. Firstly, the visible light/infrared devices are required to collect the target surrounding information, perform feature analysis, and complete the anti-fog and de-noising preprocessing. These operations aim at improving the accuracy of image segmentation. 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. The fusion uses a matching matrix to represent the similarity of the two images. When the two images are very similar, the image is fused by weighting pixels, which effectively improves the accuracy of the detection. Lots of simulations were conducted on MATLAB 2015a with a personal computer, and the results verified the success rate of target detection and recognition.
关键词： fusion,Multi-scale fractal,target detection,visible image,infrared image
更新于2025-09-09 09:28:46
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DenseFuse: A Fusion Approach to Infrared and Visible Images
摘要： In this paper, we present a novel deep learning architecture for infrared and visible images fusion problem. In contrast to conventional convolutional networks, our encoding network is combined by convolutional layers, fusion layer and dense block in which the output of each layer is connected to every other layer. We attempt to use this architecture to get more useful features from source images in encoding process. And two fusion layers(fusion strategies) are designed to fuse these features. Finally, the fused image is reconstructed by decoder. Compared with existing fusion methods, the proposed fusion method achieves state-of-the-art performance in objective and subjective assessment.
关键词： visible image,image fusion,infrared image,dense block,deep learning
更新于2025-09-04 15:30:14
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[IEEE 2018 IEEE International Conference on Mechatronics and Automation (ICMA) - Changchun (2018.8.5-2018.8.8)] 2018 IEEE International Conference on Mechatronics and Automation (ICMA) - Study on the Calculation Method of Ice Thickness Calculation and Wire Extraction Based on Infrared Image
摘要： In order to accurately measure the ice coating thickness on the ice-covered wire, the conventional ice-covering measurement method has complex operations and insufficient accuracy. This paper based on the infrared image of ice covered wire obtained by UAV and uses the image processing method to perform edge detection on the infrared image of the ice coating wire. The results show that Ratio operator detection results are superior to Canny operator and Steger operator. Then, the Hough change is performed on the image detected by the Ratio operator edge, and the exact position of the wire in the infrared image is extracted to prepare for the next calculation of the ice thickness. Finally, on the basis of the extracted infrared image, the calculation of the ice thickness on the ice-covered wire is converted into the solution of the image pixels. Then the image data is used to calculate the inclination of the overhead transmission line in the image, and the thickness of the ice coating is corrected. Finally,the results obtained by experiment show that the error between the calculation results of the ice coating thickness obtained by the pixel solution method and the thickness of the ice coating obtained by the numerical calculation is very small. Therefore, this method can accurately calculate the ice-covering thickness of the ice-covered wire and has a good application prospect in the wire ice covered field.
关键词： Hough transform,Ratio operator,Infrared image,ice coating
更新于2025-09-04 15:30:14