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.