To　solve　the　problem　of　sequence　to　sequence　super　resolution,　a　video　sequence　super　resolution　algorithm　based　on　a　frame　of　reference　high　resolution　image　is　proposed　in　this　paper.　The　algorithm　is　based　on　the　fact　that　in　most　cases,　the　vidicon　device　has　dual　mode:　HR　(High　Resolution)　still　and　LR　(Low　Resolution)　video.　In　the　algorithm,　a　HR　still　image　acquired　from　the　same　scene　is　used　as　an　example,　the　high　frequency　details　of　it　are　extracted　and　then　motion　compensated　and　reliability　weighted　for　super　resolution　of　the　corresponding　low　resolution　frames.　The　estimated　HR　frames　are　then　constraint　optimized　under　the　Maximum　A　Posteriori　(MAP)　framework　to　improve　its　fidelity.　Evaluated　by　several　sequences,　the　proposed　algorithm　shows　obvious　performance　improvements　compared　with　the　traditional　bilinear　interpolation　and　the　MAP　based　static　batch　method.　The　average　PSNR　(Peak　Signal-to-Noise　Ratio)　of　the　reconstructed　frames　are　improved　by　more　than　2.4　dB.