Registration　of　the　consecutive　frames　is　quite　essential　in　dynamic　video　super　resolution.　In　this　paper,　a　multi-scale　least　square　affine-based　block-match　method　is　proposed.　An　index　Dmv　is　defined　to　evaluate　global　and　local　matching　performances　of　the　images.　Then　a　multi-scale　scheme　is　designed　to　adjust　the　block　size　automatically　according　to　the　motions　between　frames,　which　guaranteed　well　performances　in　both　planar　and　un-planar　regions.　Different　from　the　traditional　block-match　method,　the　affine-based　least　square　estimation　algorithm　is　introduced　for　registration　of　each　pair　of　blocks.　Convergence　of　the　estimating　process　for　different　size　of　blocks　is　resolved　by　unification　of　the　update　step,　which　results　in　improvements　in　both　estimating　precision　and　speed.　Finally,　the　proposed　algorithm　is　evaluated　in　both　the　registration　performance　and　its　affects　to　the　performance　of　the　super　resolution　algorithm.　Experimental　results　show　that　the　proposed　algorithm　not　only　can　provide　more　accurate　motion　estimation,　when　be　applied　to　the　Maximum　A　Posterior　(MAP)　based　super　resolution　method,　it　shows　obvious　enhancement　in　both　reconstruction　performances　and　efficiencies.