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Detection and removal of rain is important in outdoor surveillance vision systems, since the appearance of rain strikes degrades the performance of various vision-based applications. The existing algorithms address the issue of detecting rain only in the irradiance light field, thus require dozens of successive frames to compute the temporal correlation of rain. Combining the properties of rain in irradiance light field and motion field, this paper presents a new approach for rain detection and removal using only three successive frames. In this approach, motion data are used to differentiate rain from other moving objects. A smoothing method based on anisotropic diffusion is proposed for rain removal. Experimental results verify the efficacy of our algorithm.