Sparse　representation　provides　a　new　method　of　generating　a　super-resolution　image　from　a　single　low　resolution　input　image.　An　over-complete　base　for　sparse　representation　is　an　essential　part　of　such　methods.　However,　discovering　the　over-complete　base　with　efficient　representation　from　a　large　amount　of　image　patches　is　a　difficult　problem.　In　this　paper,　we　propose　a　super-resolution　construction　based　on　multi-space　sparse　representation　to　efficiently　solve　the　problem.　In　the　representation,　image　patches　are　decomposed　into　a　structure　component　and　a　texture　component　represented　by　the　over-complete　bases　of　their　own　spaces　so　that　their　high-level　features　can　be　captured　by　the　bases.　In　the　implementation,　a　prior　knowledge　about　low　resolution　images　generation　is　combined　to　the　typical　base　construction　for　high　construction　quality.　Experiment　results　demonstrate　that　the　proposed　method　significantly　improves　the　PSNR,　SSIM　and　visual　quality　of　reconstructed　high-resolution　image.