The estimation of optical flow suffers from its sensitivity to illumination variation, its high computational complexity and slow convergence property which severely compromise its performance. In order to tackle the aforementioned problems, a structure-texture decomposition technique based on ROF(RudinOsherFatemi) model was introduced to deal with the variation in illumination, and a multi-grid based optical flow hierarchy strategy was presented for a fast implementation. The iterative procedure was proposed to be distributed on several grid layers with different resolutions in order to obtain a fast convergence and, in turn, accelerated the optical flow computation. The finer grid promised to eliminate higher frequency errors while the coarser level was employed to cope with lower frequency components. It is revealed from the experimental results that the structuretexture decomposition is robust against the variation in illumination, and is beneficial for estimation accuracy. Additionally, the multigrid method offers an improved realtime performance, without deteriorating the optimization accuracy.