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机构地区:[1]云南师范大学颜色与图像视觉实验室,云南昆明650500 [2]云南师范大学信息学院,云南昆明650500
出 处:《云南师范大学学报(自然科学版)》2016年第1期30-37,共8页Journal of Yunnan Normal University:Natural Sciences Edition
基 金:云南省学术带头人后备人才培养计划资助项目(2010CI038);云南省高校颜色与光电成像技术科技创新团队计划资助项目
摘 要:针对红外与可见光图像融合中出现的对比度较低和图像模糊的问题,提出了一种边缘优化的模块化融合方法.首先,对红外图像进行局部对比度自适应增强,突出红外图像中的目标;然后分别对红外图像和可见光图像进行HSV色空间变换,在亮度分量中,对其进行边缘细节增强的模块化融合,进一步突出红外图像中的目标轮廓;最后,结合可见光图像的色调和饱和度分量,经过RGB色空间的转换,获取融合后的图像.结果表明,与简单加权平均算法和小波融合算法的融合结果相比较,该融合算法能够较好的保持原图像的细节和目标信息,图像的对比度和清晰度也有较大的提高.To deal with the problem of low contrast and image fuzzy in the fusion processing for infrared and visible image,a modular fusion method based on edge optimization infrared and visi- ble image is proposed. Firstly,the infrared image is enhanced by the local contrast adaptive meth- od,and highlighted the target of the infrared image;then,the infrared image and visible image is transformed separately by the color space of HSV,in the obtained intensity components,two of them are fused by the modular fusion rule of edge details enhancement, further highlighted the infrared image of the target profile; Finally, combining the hue and saturation of visible image, new intensity component are transformed into the RGB color space,and obtained the fusion im- age. By subjective evaluation and objective evaluation standard,experiment results show that the results of this fusion algorithm are better than the simple weighted average algorithm and wave- let fusion algorithm,which can reserve the original image details and target information,and also improve greatly the contrast and resolution of the image.
关 键 词:图像处理 图像融合 模块化 边缘优化 对比度自适应增强
分 类 号:TN911.73[电子电信—通信与信息系统]
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