In　this　paper,　we　proposed　an　image-based　rendering　method　based　on　the　block　sparsity　of　epipolar　plane　image(EPI).　This　method　considers　the　structural　similarity　and　block　sparseness　features　of　scene　signal　described　by　EPI　model,　which　makes　it　possible　to　estimate　approximately　original　signal　with　less　measured　values,　and　reduces　the　complexity　of　signal　sampling　and　processing.　First,　we　choose　a　part　of　scene　EPI　images　as　samples　and　carry　on　sub-block　processing.　Furthermore,　we　train　the　sparse　representation　dictionary　by　KSVD　method,　and　use　the　low-frequency　part　of　Discrete　Cosine　Transformation　(DCT)　matrix　to　build　the　sampling　matrix.　Finally,　we　reconstruct　original　signal　by　orthogonal　matching　pursuit　method.　According　to　the　results　of　simulation　experiment,　compared　with　traditional　methods,　under　the　same　sample　rate,　the　proposed　method　promotes　both　the　subjective　and　objective　quality　of　complex　scene　with　regard　to　different　depths.　©　2017　IEEE.