Pseudo particles in the image data from the airborne Cloud Imaging Probe (CIP) and Precipitation Imaging Probe (PIP) measurements can degrade the quality of the measurement data. Utilizing three flights data in Taiyuan area from Shanxi Y-12 research plane, the causes and characteristics of the pseudo particles were analyzed and classified. A pseudo particle identification method was proposed based on the results, which includes the inter-arrival time threshold and the image processing identification technique. Using the algorithm proposed in this study, the image data were processed and analyzed statistically. It was found that the maximum occurrence probability of artifacts in each research flight could reach 45.2% with an average occurrence probability of 36.01% (CIP) and 8.64% (PIP). Among the artifacts, the occurrence probability of the shattered fragments was the highest, which accounted for more than 95% of the total number of pseudo particles; stripe shaped particles and the coexisting particles showed the second highest occurrence probability. Relatively speaking, the occurrence probability of blank particles and line shaped particles appeared to be relatively low. It was also found that the occurrence probability of each individual component of the pseudo particles could be influenced by the flight state of the airborne platform. By using the proposed method, the particle spectrum, particle concentration and ice water content from the probes were corrected, and results show that the artifacts could influence the particle spectrum, particle concentration and ice water content within the measuring range of the probe. Specifically, the effect on the particle spectrum lied on the portion less than 400 μm and greater than 1000 μm (CIP) and 2000 μm (PIP). The method and threshold proposed here provide some references for other flights data from CIP and PIP aboard the Y-12 research plane.