The　detection　of　ship　wakes　in　SAR　images　is　helpful　not　only　for　estimating　the　speed　and　the　direction　of　moving　ships,　but　also　for　finding　ship　objects　which　are　far　smaller　than　ship　wakes.　Facing　the　problem　that　the　existing　detection　methods　based　on　the　line　detection　can　be　only　used　for　SAR　images　under　the　simple　sea　background　conditions,　a　novel　ship　wake　detection　method　for　SAR　images　with　the　complex　backgrounds　using　the　morphological　component　analysis　is　proposed.　Relied　on　the　basic　principle　that　each　component　can　only　be　sparsely　represented　by　a　specific　dictionary,　suitable　basis　functions　are　selected　for　the　dictionary　construction　according　to　the　＇line＇　singularity　of　ship　wakes　and　the　＇point＇　singularity　of　sea-surface　textures　respectively,　and　the　ship　wake　structure　component　and　the　sea-surface　texture　component　are　consequently　separated　in　the　sense　of　sparse　representation.　Then,　the　enhancement　of　ship　wake　structure　component　is　realized　through　the　reconstruction　of　the　high-frequency　coefficients　of　the　shearlets　transform.　And　finally,　the　ship　wake　lines　are　detected　by　using　the　Radon　transform.　Both　the　qualitative　and　the　quantitative　experimental　results　show　that,　the　proposed　method　conspicuously　outperforms　the　existing　methods　for　the　ship　wake　detection　in　SAR　images,　especially　under　the　complex　sea　background　conditions.　©　2016,　Beijing　China　Science　Journal　Publishing　Co.　Ltd.　All　right　reserved.