针对红外图像对比度低、细节较差，且一般是黑白图像，不适宜于人眼观察，提出一种利用局部线性映射方法(LLE)的红外成像彩色化方法。该方法寻求灰度空间到色彩空间的映射，实现红外图像到彩色红外图像的转变，先将目标红外图像和彩色模板图像转换至YUV颜色空间，分离亮度和色彩信息;然后将目标红外图像的每个像素及邻域像素的灰度值串接成矢量，并均匀从彩色模板图像选取部分像素按相同方法串接成矢量，采用欧氏距离搜索最近邻并计算最佳的匹配系数，经色彩值(即U和V分量)计算将模板图像的彩色传递给目标红外图像后搜索亮度最大值的像素邻域并经自动阈值伪彩色编码处理，突出显示重要目标，得到处理后的彩色红外图像。将算法应用于实验室自主开发的热像仪，算法作用后的红外图像不但有了适于人眼视觉的彩色信息，而且用红、黄等敏感色突出了重点热目标，提高了人眼发现和识别目标的速度，实验结果表明，算法有利于侦察人员长时间的目标观察和识别目标。

Aiming at the problem that the infrared image has the weakness of dim targets and poor details, is generally black-white image and not used for chroma subsampling, the paper introduces a new infrared imaging colorization algorithm based on local linear embedding(LLE). The method seeks the mapping for the gray space to the color space, achieves the transfer from infrared image to colorized infrared image. Firstly this paper transfers the object infrared image and source color image to YUV color space, separates the luminance and hue information, secondly it makes each pixel and the neighbor pixels connected to vector, chooses equally part pixels of reference color image and makes them become vector using the same principle, then accomplish matching pixels between the object and reference images, and highlights the brightest parts of the resulted infrared image based on auto-threshold pseudo-coding. Applying the method on infrared thermal imager of lab, it has color information that improves the visual effect, avoids visual fatigue, and makes the hot targets more noticeable using the sensitive color such as red and yellow, the experiment results show that it is advantageous to long-time observation and target distinguishing.