基于区域能量和标准差的图像融合

Xi Su-xia, Chen Tian-hua, Li Jing-xian
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引用次数: 10

摘要

红外与可见光图像融合技术可以增强驾驶员在低能见度环境下的视觉效果,降低交通事故的发生概率。针对小波变换在图像融合中的应用,提出了一种基于区域能量和标准差的红外和可见光图像融合方法。该方法利用区域能量加权融合规则获得小波变换的低频近似分量,利用区域标准差加权融合规则合成3个高频细节分量。通过两组红外和可见光图像融合实验表明:与简单方法相比,该方法产生的图像的标准差分别提高了41.8%和67.2%,平均亮度分别从34.6%提高到55.1%。
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Image fusion based on regional energy and standard deviation
Image fusion technology of infrared and visible light could enhance the driver's visual effects in low visibility circumstance, and reduce the probability of the traffic accidents. Focused on the application of wavelet transform in image fusion, a image fusion method was proposed based on a regional energy and standard deviation for the infrared and visual light images. In this method, low-frequency approximation component of wavelet transform were obtained by a regional energy-weighted fusion rule, and three high-frequency details components were composed by utilizing the regional standard deviation-weighted fusion rule. Through the two groups of infrared and visual light image fusion experiments show that: the standard deviation of the image produced by the method increased 41.8% and 67.2% and the average brightness increased from 34.6% to 55.1% compared with simple method, respectively.
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