基于分形特征和导引滤波的可见光与红外图像融合算法

Visible and Infrared Image Fusion Algorithm by Fractal Feature and Guided Filtering

为充分利用红外图像的目标指示信息,本文提出了一种基于分形特征和导引滤波的可见光与红外图像融合算法。该算法首先采用分形特征对红外图像中的人造目标进行增强,通过阈值分割得到目标分布图。待融合图像经过一层分解得到近似图像和细节图像,基于目标分布图利用导引滤波分别得到可见光与红外近似图像与细节图像的融合系数。实验结果表明,融合后图像充分结合了可见光图像的背景信息与红外图像中的目标信息,有利于后续的目标识别任务。

To make full use of object targeting information in infrared image, the algorithm based on fractal feature and guided filtering is presented to fuse visible and infrared image. The proposed algorithm adopts fractal feature to perform man-made object enhancement in infrared image first, and then gets object distribution picture through threshold segmentation. The approximation image and detail image are obtained by one-level decomposition of images to be fused, and the fusion coefficients are obtained by guided filtering based on object distribution picture. The experimental results demonstrate that, the fused image combines background information from visible image and object information from infrared image fully, and can be beneficial for object recognition tasks further.