Infrared　(IR)　and　visible　(VI)　image　fusion　play　an　important　role　in　improving　the　sea　scene　perception　and　ship　target　detection.　Although　there　have　been　many　studies　on　image　fusion　considering　the　sea　scene　characteristics,　there　has　still　been　no　adequate　extraction　method　for　detailed　information　of　a　ship　target　in　a　sea　scene.　To　overcome　this　shortcoming,　this　paper　proposes　a　fusion　method　based　on　a　scale-aware　feature　decomposition,　which　can　accurately　extract　features　of　a　ship　target　at　different　scales.　First,　a　hybrid　feature　decomposition　method　based　on　the　scale-aware　structure-preserving　filter　and　Gaussian　filter　is　designed.　The　proposed　method　separated　source　images　into　region,　structure,　and　texture　layers,　and　thus　achieved　a　finer-scale　division　than　traditional　multiscale　decomposition　methods　in　the　sea-clutter　background.　Then,　further　decomposition　of　the　texture　layer　was　performed　by　the　shearlet　transform　to　obtain　the　directional　texture　feature.　According　to　the　characteristics　of　each　layer,　different　strategies　were　adopted　for　the　fusion,　and　the　weighting　factor　was　used　to　obtain　the　final　fusion　result.　Experimental　results　indicated　that　the　proposed　method　could　achieve　better　subjective　and　objective　results　than　current　state-of-the-art　methods.　This　method　introduces　a　scale-aware　edge　preserving　filter　to　improve　the　ability　of　detail　extraction　and　is　suitable　for　image　fusion　of　ship　targets.