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A novel night vision image color fusion method based on scene recognition

机译:基于场景识别的新型夜视图像色彩融合方法

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摘要

Infrared and low light level image color fusion can make target detection and recognition more precise. Different from the existing color transfer fusion method using fixed reference image, this paper presents a color fusion method based on a combination of scene classification, fusion quality measure and color transfer. We introduce the scene classification method into the color fusion algorithm, which is based on the Gist descriptor and SVM classifier. Afterwards we use the proposed color fusion quality measure structure to find out the best matched reference image for each classified input image. Meanwhile, we get the high quality color fusion image using color transfer method. This method is verified in both linear and non-linear color space. Results show that this method can effectively improve the color fusion effect. More importantly, it can be used in the condition with few prior information.
机译:红外和弱光图像颜色融合可以使目标检测和识别更加精确。与现有的使用固定参考图像的颜色转移融合方法不同,本文提出了一种基于场景分类,融合质量度量和颜色转移的颜色融合方法。我们将场景分类方法引入到基于Gist描述符和SVM分类器的颜色融合算法中。然后,我们使用提出的颜色融合质量度量结构来为每个分类的输入图像找出最佳匹配的参考图像。同时,我们使用颜色转移方法获得了高质量的颜色融合图像。该方法已在线性和非线性色彩空间中得到验证。结果表明,该方法可以有效提高色彩融合效果。更重要的是,它可以在几乎没有先验信息的情况下使用。

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