Till　now,　there　were　several　methods　of　fractal　texture　extraction　developed　for　high-resolution　remotely　sensed　images:　triangular　prism,　fractal　Brownian　motion,　DBC　(different　box-counting)　and　multi-fractal.　However,　one　proper　method　should　be　selected　in　application.　Upon　that,　in　the　paper,　taking　QuickBird　image　as　example,　based　on　a　rather　entire　classification　system　founded　for　the　image,　fractal　dimensions　and　correlative　parameter　were　utilized　to　analyze　features　of　those　methods;　mean,　variance　and　computation　time　were　utilized　to　compare　difference　of　them.　Then　several　conclusions　were　drawn　through　the　experiment:　fractal　texture　could　be　an　effective　feature　to　distinguish　ground　objects;　among　those　methods,　triangular　prism　couldn＇t　do　well　on　ground　objects＇　distinguishing,　FBM　wasn＇t　accurate　(without　no-scale　part),　but　DBC　and　multi-fractal　represented　better　on　distinguishing　ground　objects　and　computing　efficiency.　©　2012　IEEE.