研究并评价了单幅荧光图像的降噪方法, 以便真实、有效地获得用于瞬态流场测量的荧光图像的流场参数。分析了单幅荧光图像中的噪声来源, 根据对双线测温信息提取的影响程度, 确定米散射强噪声作为主要的滤波对象。分析了不同数字滤波方法的适用范围, 并对丙酮荧光显示的流场图像进行了降噪处理。通过检查荧光图像与滤波处理图像的差值图像中含有荧光图像结构信息的程度评价了降噪效果。比较表明, 形态学开运算图像重构滤波方法对荧光图像中米散射强噪声去除效果较好, 并可较好地保护图像中原有荧光信息的细节。采用形态学开运算图像重构滤波方法对Q2(11)线与P1(7)线激励甲烷/空气预混火焰获得的荧光图像进行处理, 得到了较为平滑的二维温度分布, 测量温度在2 000 K左右。结果表明, 形态学滤波方法在瞬态流场定量测量的PLIF图像降噪处理方面具有一定的应用潜力。

Noise removing methods were analyzed and assessed to obtain real and effective measurement parameters extracted from fluorescent images in flow field measurements. The fundamental principle of Planar Laser Induced Fluorescence(PLIF) quantitative measurement was introduced. On the basis of analyzing the sources and characteristics of noises, some noise removing methods were analyzed and the stronger noise from the Mie scattering was determined as the main filtering target. Different filter methods were analyzed, the flow field image from an acetone fluorescent display was processed by denoising, and the denoise results were assessed by checking the residual amount of fluorescent signals in the image. Analysis shows that the morphological grayscale reconstruction method can not only move the noise effectively, but also can remain detailed information of the fluorescent signal remains with highly fidelity. The fluorescent images of methane/air flame induced by Q2(11) andP1(7) lines were filtered and 2D distribution of temperature was obtained in 2 000 K. Results show that morphological grayscale reconstruction method has great potential applications to the noise removing of PLIF images in flow parameter measurements.