红外轴温监测系统中的图像融合算法

针对红外轴温监测系统中可见光与红外图像分辨率相差较大时图像融合效果不理想,不利于列车热轴判定的问题,提出了一种可见光与红外伪彩图像融合的算法.该算法对红外轴温系统中的红外图像与可见光图像视场相同部分进行像素灰度复制,并对其他部分进行双线性插值,以此完成红外图像与可见光图像的像素匹配;接着对红外图像进行伪彩编码映射,在RGB三通道内对可见光与红外图像进行加权融合.实验结果表明,融合图像在色彩上更丰富,红外目标位置更准确,更便于人工辨认热轴的位置.结果满足红外轴温监测系统对红外与可见光图像的融合需求.

Image Fusion Algorithm for Infrared Hotbox Monitoring System

For an infrared hotbox monitoring system, when its visible image and infrared image have a large difference in resolution, the fusion of the images is not ideal. This is unfavorable for the determination of the hotboxes of a train. To solve this problem, an algorithm for fusing a visible image with a pseudo-color infrared image is proposed. In the algorithm, the gray levels of the pixels in the same part in both a visible image and an infrared image are reproduced firstly and bilinear interpolation is implemented for other parts in the images, so as to match the pixels in the visible image with those in the infrared image. Then, the infrared image is mapped by pseudo-dolor coding, and weighted fusion is implemented for the visible and infrared images in three channels (RGB). The experimental result shows that the fused image is richer in color. The location of the infrared target in the image is more accurate and is more convenient for the manual identification of the position of a hot-axis. The algorithm can meet the need for fusing infrared and visible images in an infrared hotbox monitoring system.