以水射流红外图像为研究对象，提出了一种 红外图像多步骤去噪方案，即先利用图像减法得到红外温度场的增量分布，然后通过自适应中值滤波去除具有高斯分布的白噪声，最后用高斯 高通滤波去除周期性噪声并对图像进行锐化处理。实验结果表明，本文提出的多步骤去噪法具有很好的去噪效果。经过处理的图像清楚地揭示了射流核心区、主体段和 扩散段的结构特征，以及由射流剪节层带动环境空气形成的湍流场中不同尺度涡旋的结构特征。通过对去噪后的红外图像进行分析，加深了我们对湍流射流机理 的认识。同时，该方案对类似的红外图像处理也具有一定的借鉴意义。

Taking the infrared images of water jet as the research object, a multistep denoising scheme for infrared images is proposed. Firstly, an image subtraction method is used to obtain the increment distribution of the infrared temperature field. Secondly, an adaptive median filter is used to remove the white noise with Gaussian distribution. Finally, a Gaussian high-pass filter is used to remove the periodical noise and sharpen the image. The experimental result shows that the proposed multistep denoising method is good in denoising. In the processed image, the structural characteristics of the jet core, main region, diffuse region and different turbulent jet in the turbulent flow composed of water mist and flowing air induced by the momentum exchange between the jet boundary and ambient air are revealed clearly. The analysis of the denoised infrared images helps us further understand the mechanism of turbulent jet. The scheme is of significance to the processing of similar infrared images, too.