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.