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Contrast Enhanced Low-light Visible and Infrared Image Fusion

机译:对比增强低光可见和红外图像融合

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Multi-modal image fusion objective is to combine complementary information obtained from multiple modalities into a single representation with increased reliability and interpretation. The images obtained from low-light visible cameras containing fine details of the scene and infrared cameras with high contrast details are the two modalities considered for fusion. In this paper, the low-light images with low target contrast are enhanced by using the phenomenon of stochastic resonance prior to fusion. Entropy is used as a measure to tune iteratively the coefficients using bistable system parameters. The combined advantage of multi scale decomposition approach and principal component analysis is utilized for the fusion of enhanced low-light visible and infrared images. Experimental results were carried out on different image datasets and analysis of the proposed methods were discussed.?
机译:多模态图像融合目标是将从多个模式获得的互补信息与具有增加的可靠性和解释的单个表示组合成单个表示。从含有高对比度细节的场景和红外相机的细节的低光可见摄像机获得的图像是考虑融合的两个模态。在本文中,通过使用融合前的随机共振现象提高了具有低目标对比的低光图像。熵用作使用双稳态系统参数迭代地调谐系数的度量。多尺度分解方法和主成分分析的组合优点用于增强的低光可见和红外图像的融合。实验结果在不同的图像数据集上进行,并讨论了所提出的方法的分析。

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