This　paper　proposes　a　novel　equivalence　graph　cut　method　based　on　wavelet　transform　for　SAR　image　registration　in　order　to　improve　robustness　and　real-time　performance.　First,　the　equivalence　graph　cut　model　is　constructed　in　low-frequency　sub-images　after　wavelet　transform　of　image,　which　can　reduce　speckle　noise.　The　proposed　model　can　not　only　avoid　NP-complete　problems　but　also　provide　a　solution　to　the　choice　of　mapping　function.　Then,　scale　invariant　feature　transform　(SIFT)　is　exploited　to　find　the　feature　matching　in　the　object　accurately　segmented　from　the　original　image　so　as　to　reduce　the　feature　point　description　of　search　space　and　improve　real-time　performance.　Finally,　the　accurate　SAR　image　registration　is　achieved　based　on　the　transformation　parameters　found　by　matching　relationship.　The　experimental　results　show　that　the　proposed　method　can　achieve　fast　and　accurate　image　registration.