PDE　based　image　segmentation　methods　are　the　state-of-the-art　methods　due　to　the　high　accuracy　and　continuity　of　detected　edges.　Some　examples　are　the　region-scalable　fitting　(RSF)　model　and　the　local　image　fitting　energy　(LIF)　model.　But　they　suffer　from　the　high　computing　complexity　and　instability.　Recently,　the　globally　convex　method　and　the　split　Bregman　method　are　introduced　to　overcome　this　problem.　In　this　paper,　a　globally　convex　version　of　the　LIF　model　is　proposed　and　then　the　split　Bregman　method　is　used　to　solve　the　model.　Experiments　show　that　this　model　is　more　efficient　than　the　RSF　model　and　the　LIF　model　while　with　similar　segmentation　results.　©　2013　IEEE.